25th Anniversary Conference
Geographic Information Systems Conference and Exhibition “GIS ODYSSEY 2018”
Conference proceedings
10th to 14th of September 2018, Perugia, Italy
25th Anniversary Conference Geographic Information Systems Conference and Exhibition “GIS ODYSSEY 2018”
Conference proceedings
10th to 14th of September 2018, Perugia, Italy
Scientific Committee: Prof. dr Elżbieta Bielecka, Military University of Technology, Warsaw, Poland Prof. dr Vlado Dadić, Institute of Oceanography and Fisheries, Split, Croatia Prof. Andrea De Montis, University of Sassari, Italy Prof. dr Karol Noga, The University of Life Sciences in Lublin, Poland Prof. dr Bonawentura Maciej Pawlicki, Cracow University of Technology, Poland Prof. dr Piotr Parzych, AGH University of Science and Technology, Cracow, Poland Prof. dr Oimahmad Rahmonov, University of Silesia in Katowice, Poland Prof. dr Katarzyna Sobolewska-Mikulska, Warsaw University of Technology, Poland Prof. dr Hrvoje Stančić, University of Zagreb, Faculty of Humanities, Zagreb, Croatia Prof. dr Ana Stoeva, University of Architecture, Civil Engineering and Geodesy, Sofia, Bulgaria Prof. dr Grażyna Szpor, Cardinal Stefan Wyszyński University, Warsaw, Poland Doc Dr Peter Blišťan, Technical University of Košice, Slovakia Doc. Dr Zvonko Gržetić, Scientific Centre of Law & Informatics, Warsaw, Poland Doc. Dr Pavlo Kolody, Agricultural Academy in Dublany, Ukraine Dr Romualda Bejger, West Pomeranian University of Technology in Szczecin, Poland Dr Giovanni Luca Bianco, University of Bari, Italy Dr Agnieszka Dawidowicz, University of Warmia and Mazury in Olsztyn, Poland Dr Ryszard Florek-Paszkowski, Kielce University of Technology, Poland Dr Giuseppe Modica, Mediterranean University of Reggio Calabria, Italy Dr Paweł Nicia, Agricultural University of Cracow, Poland Dr Marco Vizzari, University of Perugia, Italy Dr Paweł Zadrożny, University of Agriculture in Krakow, Poland Organising Committee: Chairman: Prof Davorin Kereković Vice-Chairman: Dr Anita Kwartnik-Pruc Secretaries: Dr Edyta Puniach, Dr Francesco Santaga Members: Prof. dr Małgorzata Chomicz, Dr Paweł Ćwiąkała, Dr Małgorzata Gajos-Gržetić, Dr Anna Kowalczyk, Dr Sebastian Stach, Dr Marco Vizzari, Dr Agnieszka Zwirowicz-Rutkowska The papers published in the Conference Proceedings GIS Odyssey 2018 have been given a favorable opinion by the Reviewers designated by the Scientific Committee. Published by: Croatian Information Technology Society – GIS Forum 10 000 Zagreb, Ilica 191e, Croatia Publication & Conference responsible person: Davorin Kereković. – GIS Forum Secretary Editors: Dr Paweł Ćwiąkała, AGH University of Science and Technology, Cracow, Poland Dr Anita Kwartnik-Pruc, AGH University of Science and Technology, Cracow, Poland Dr Edyta Puniach, AGH University of Science and Technology, Cracow, Poland The picture on the cover: Prof. dr Małgorzata Chomicz © Copyright Information Technology Society – GIS Forum, Croatia All rights reserved International standard serial number: ISSN 2623-5714 (Online) Nacionalna knjižnica, Zagreb, Croatia ISSN 2459-7619 (Print) Nacionalna knjižnica, Zagreb, Croatia ISSN 2459-7627 (CD-ROM) Nacionalna knjižnica, Zagreb, Croatia
CONTENTS 1.
THE RE-USE OF PUBLIC SPATIAL DATA IN THE LIGHT OF GERMAN LAW ........................................................ 7 Mateusz Badowski, Małgorzata Olszewska,
2.
GEOINFORMATION ANALYSIS AND MARKET VALUE OF SAFE SPATIAL – SAFE PLACE........................... 14 Tomasz Bajerowski
3.
THE IMPACT OF SURVEYING WORKS ON THE DEVELOPMENT OF SMART CITY ......................................... 20 Monika Balawejder, Katarzyna Matkowska, H. Ebru Colak
4.
ROBUST ESTIMATION FOR DETECTION OF FLATNESS DEFECTS ....................................................................... 33 Marek Banaś, Sorin Nistor
5.
ATTRIBUTE ‘MEAN ERROR OF THE BOUNDARY POINT POSITION’ IN THE ASPECT OF ACCURACY ASSESSMENT OF PARCEL SURFACE AREA...................................................................................................................... 40 Piotr Benduch, Agnieszka Pęska-Siwik
6.
SPATIAL PLANNING AS A TOOL FOR PROTECTION OF MINERAL SPRINGS IN POLAND .......................... 51 Agnieszka Bieda, Anna Bieda
7.
MONITORING OF SELECTED GEOHAZARDS BY USING UNMANNED AERIAL SYSTEMS (UAS) .............. 57 Peter Blistan, Ľudovit Kovanič, Matej Patera, Paweł Frąckiewicz, Marcin Gil
8.
RESEARCH OF THE MORPHOLOGY OF RIVER DNIESTER USING REMOTE SENSING AND CARTOGRAPHIC DATA ............................................................................................................................................................. 64 Khrystyna Burshtynska, Volodymyr Shevchuk, Andriy Babushka, Sofija Tretyak, Maksym Halochkin
9.
ONTOLOGY-BASED METHODS AND SYSTEMS SUPPORTING SITUATION AWARENESS IN HYBRID CONFLICTS UTILISING ONTOLOGY REASONING MECHANISMS AND GIS-BASED DISTRIBUTED SERVICES ........................................................................................................................................................................................ 73 Mariusz Chmielewski
10. FINANCIAL FRAUD RECOGNITION AND IDENTIFICATION METHOD USING REASONING AND QUANTITATIVE ASSOCIATION EVALUATION ............................................................................................................... 87 Mariusz Chmielewski, Maciej Kiedrowicz, Piotr Stąpor 11. AUGMENTED REALITY MECHANISMS IN MOBILE DECISION SUPPORT SYSTEMS SUPPORTING COMBAT FORCES AND TERRAIN CALCULATIONS - A CASE STUDY .................................................................... 98 Mariusz Chmielewski, Krzysztof Sapiejewski 12. THE CONCEPT OF CREATING RASTER ACCESSIBILITY MAPS FOR MULTI-STOREY BUILDINGS ....... 111 Piotr Cichociński 13. SELECTED ISSUES CONCERNING MANAGEMENT OF HISTORICAL IMMOVABLE PROPERTIES IN POLAND AND OTHER EUROPEAN COUNTRIES ................................................................................................... 120 Agnieszka Cienciała 14. RECORDING PROPERTY RELATIONS ON PIPELINE ROUTE IN GIS .................................................................. 133 Antun Ćurković, Igor Mlinarić 15. SECURITY OF GEOGRAPHICAL INFORMATION SYSTEMS - HOW TO ENSURE THEIR CONFIDENTIALITY, INTEGRITY, AVAILABILITY AND RESILIENCE? ................................................ 142 Kamil Czaplicki 16. OPTIMISATION OF THE UAV-BASED PHOTOGRAMMETRIC DATA COLLECTION PROCESS IN DOCUMENTATION OF LINEAR OBJECTS OF SUBSTANTIAL HEIGHT DIFFERENCES ......................... 146 Paweł Ćwiąkała, Edyta Puniach, Paweł Wdowiak 17. SWOT ANALYSIS IN THE JOB OF A REAL ESTATE APPRAISER ........................................................................... 157 Dorota Dejniak, Eva Hvizdová, Janusz Dąbrowski 18. INTER AND INTRA-PATCH LANDSCAPE CONNECTIVITY: A COMPARATIVE MEASUREMENT FOR ITALY AND THE UK ....................................................................................................................................................... 164 Andrea De Montis, Vittorio Serra, Antonio Ledda
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19. BUILDING OF TEXTURED MODELS OF CONSTRUCTIONS WITH IMAGING OF FACADES AND SIDEPIECES AT ORTHOPHOTOS ....................................................................................................................................... 169 Oleksandr Dorozhynskyy, Ihor Kolb 20. THE FUSION AND DIVISION OF LAND PARCELS FOR AN IMPROVEMENT OF THEIR INVESTMENT STRUCTURE ................................................................................................................................................................................ 176 Ryszard Florek Paszkowski 21. ANALYSIS OF IMPLEMENTATION OF THE ACT ON TRANSFORMATION OF RIGHT OF PERPETUAL USUFRUCT INTO PROPERTY OWNERSHIP TITLE .................................................................................................... 183 Teresa Front-Dąbrowska, Anna Trembecka, Anita Kwartnik-Pruc 22. PRICE MAPS AS A RISK LIMITING AND DECISION SUPPORTING FACTOR ON THE REAL ESTATE MARKET ....................................................................................................................................................................................... 198 Radosław Gaca, Svetlana Gercheva 23. APPLICATION POSSIBILITIES OF ADVANCED ANALYSIS OF PUBLIC DATA SOURCES IN THE FIGHT AGAINST CHILD MALTREATMENT .................................................................................................................................. 204 Maciej Kiedrowicz 24. MODEL OF AUTOMATED CONTROL AND MONITORING SYSTEM OF THE CURRENT LEVEL OF INFORMATION SECURITY .................................................................................................................................................... 212 Maciej Kiedrowicz, Jarosław Napiórkowski, Jerzy Stanik 25. ASSESSMENT OF THE USEFULNESS OF THE SECURITY CONFIGURATION .................................................. 225 Maciej Kiedrowicz, Jerzy Stanik 26. MULTICRITERIA OPTIMIZATION USED FOR THE INFORMATION SECURITY – IDEAL AND ANTI-IDEAL................................................................................................................................................................................. 237 Maciej Kiedrowicz, Jerzy Stanik 27. THE ROLE OF THE LAND ADMINISTRATION SYSTEM IN THE PROCESS OF DEVELOPING AND UPDATING THE LAND PARCEL IDENTIFICATION SYSTEM – A CASE STUDY OF HIGH NATURE VALUE FARMLAND IN NORTH-EASTERN POLAND ................................................................................................. 252 Katarzyna Kocur-Bera, Klaudia Piórkowska 28. THE IMPORTANCE OF GREEN INFRASTRUCTURE FOR THE INSURANCE RISK REDUCTION WITH PARTICULAR EMPHASIS ON URBANISED AREAS ....................................................................................... 261 Wiesław Koczur, Agnieszka Lorek 29. USE OF CROP-ZOOM OPPORTUNITIES FOR THE INVESTIGATION OF THE QUANTITY AND QUALITY OF AGRICULTURAL LAND ON THE TERRITORY OF VINNYTSIA REGION ...................................................... 273 Pavlo Kolodiy, Maryna Pidlypna, Vitalii Yanovych 30. INFLUENCE OF INTERNATIONAL REGULATIONS ON SPATIAL PLANNING POWER IN POLAND – SEA AND MEDIATION ......................................................................................................................................................... 279 Agata Kosieradzka-Federczyk, Wojciech Federczyk 31. TERRITORIAL SCOPE OF APPLICATION OF THE GENERAL DATA PROTECTION REGULATION ........ 285 Sylwia Kotecka-Kral 32. APPLICATION OF UAV DATA IN CITYGML DEVELOPMENT ................................................................................. 294 Filip Kovačić, Kristijan Krznarić, Petar Božičević 33. DEVELOPMENT AND ANALYSIS OF A COMMUNICATION NETWORK SYSTEM MODEL FOR FIRE SERVICE OPERATIONS ......................................................................................................................................................... .301 Anna Maria Kowalczyk 34. THE POSSIBILITIES OF USING DRONES IN ROAD ENGINEERING ..................................................................... 311 Kamil Kowalczyk, Roman Węglicki 35. PERFORMANCE THRESHOLD OF THE INTERACTIVE RASTER MAP PRESENTATION – AS ILLUSTRATED WITH THE EXAMPLE OF THE JQUERY JAVA SCRIPT COMPONENT ........................ 321 Karol Król 36. DESIGN AND IMPLEMENTATION OF THE SPATIAL DATABASE FOR THE ANALYSIS OF RESIDENTIAL ESTATE MARKET ....................................................................................................................................... 328 Janusz Kwiecień, Małgorzata Krajewska, Kinga Szopińska 4
37. THE HIERARCHIZATION OF NEEDS RELATED TO LAND CONSOLIDATION AND EXCHANGE IN RURAL AREAS IN THE VILLAGES OF THE GMINA OF POŚWIĘTNE IN CENTRAL POLAND ............. 334 Przemysław Leń, Monika Mika 38. PUBBLICO REGISTRO IMMOBILIARE AND CADASTER IN ITALY: HARMONISATION THROUGH DIGITALISATION? .................................................................................................................................................................... 341 Geo Magri 39. ACCURACY OF DETERMINATION OF THE RUNNING OF THE SHORE LINE ON ORTHOPHOTOMAP .......................................................................................................................................................................................................... 346 Aneta Mączyńska, Anita Kwartnik-Pruc 40. HISTORICAL-CULTURAL AND LEGAL ASPECTS OF THE RIGHT TO PRIVACY AND SPATIAL INFORMATION. CHALLENGES RELATED TO THE DEVELOPMENT OF TECHNOLOGY: CONSTITUTIONAL STANDARDS (POLISH CASE)………………………………………………………………………..354 Marek Michalski, Aleksandra Syryt 41. A GIS-BASED MULTI-CRITERIA MODEL FOR THE SUSTAINABLE MANAGEMENT OF GRAZING IN NATURAL PROTECTED AREAS. AN APPLICATION IN THE ASPROMONTE NATIONAL PARK………..364 Giuseppe Modica, Salvatore Di Fazio 42. THE USE OF RFID AND GPS TECHNOLOGY TO MANAGE THE INSPECTION OF ELEMENTS OF TECHNICAL STRUCTURES ................................................................................................................................................... 370 Jarosław Napiórkowski 43. BOUNDARY POINT AND BOUNDARY OF THE CADASTRAL PARCEL AS LADM OBJECTS BY THE EXAMPLE OF A POLISH REAL ESTATE CADASTRE ................................................................................. 375 Agnieszka Pęska-Siwik, Piotr Benduch 44. IMPACT OF GROUND CONTROL POINTS (GCPS) DISTRIBUTION AND UNMANNED AERIAL VEHICLE (UAV) FLIGHT PARAMETERS ON ACCURACY OF DIGITAL SURFACE MODEL (DSM) ............................... 387 Edyta Puniach, Paweł Ćwiąkała, Hubert Dec 45. SIMILARITY OF SELECTED RESIDENTIAL REAL ESTATE MARKETS IN BULGARIA AND POLAND .......................................................................................................................................................................................................... 397 Izabela Rącka, Ivo Kostov 46. ANALYSIS CONCERNING SUSTAINABLE DEVELOPMENT OF EU MEMBER STATES MEASURED BY GDP PER CAPITA ACCORDING TO AVAILABLE DATA ...................................................................................... 406 Andrzej Rączaszek 47. ANALYSIS OF THE VALUE OF PROPERTY TAX AFTER SWITCHING TO THE AD VALOREM SYSTEM IN POLAND .................................................................................................................................................................................. 412 Joanna Reczyńska, Piotr Parzych 48. APPLICATION OF GIS IN THE AREA OF SOCIAL SECURITY .................................................................................. 420 Katarzyna Roszewska 49. INTEGRATION OF GPS, GLONASS AND GALILEO SYSTEMS IN PRECISE REAL-TIME SATELLITE MEASUREMENTS...................................................................................................................................................................... 427 Zbigniew Siejka 50. ASSESSMENT OF INNOVATION AND INNOVATION RISK ON A LOCAL REAL ESTATE MARKET, IN THE CONTEXT OF THE NATIONAL MARKET ........................................................................................................ 435 Marcin Sitek 51. SMART METERING AS AN INSTRUMENT SHAPING ENERGY CONSUMERS' BEHAVIOURS ................... 443 Sylwia Słupik 52. ANALYSIS OF TRANSACTION PRICES OF RESIDENTIAL PREMISES LOCATED IN THE VICINITY OF TRANSPORTATION ROUTE – PART TWO ..................................................................................................................... 452 Kinga Szopińska, Małgorzata Krajewska, Janusz Kwiecień 53. THE SIGNIFICANCE OF GEOGRAPHICAL PERSONALITY DIVERSITY WITHIN THE EUROPEAN UNION FOR ITS LAWS ............................................................................................................................................................................ 462 Grażyna Szpor
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54. A GIS-MULTICRITERIA BASED MODEL FOR IDENTIFYING THE OPTIMAL LOCATION OF ROAD INFRASTRUCTURES ................................................................................................................................................................ 468 Marco Vizzari, Moreno Neri, Francesco Santaga, Maria Elena Menconi 55. LEGAL CONDITIONS FOR TRANSFORMATION OF THE LAND AND BUILDING REGISTER INTO A REAL ESTATE CADASTER ................................................................................................................................................ 475 Dorota Wilkowska-Kołakowska 56. THE IMPACT OF LINE INVESTMENTS ON THE SIZE OF THE PLOT PATCHWORK IN RURAL AREAS – A CASE STUDY ........................................................................................................................................................................ 484 Justyna Wójcik-Leń, Żanna Stręk 57. PUBLIC CONSULTATIONS AND ACCESS TO SPATIAL INFORMATION AS LEGAL INSTRUMENTS OF FLOOD RISK MANAGEMENT USING THE EXAMPLE OF THE ODRA RIVER BASIN .................................... 490 Monika Zakrzewska
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THE RE-USE OF PUBLIC SPATIAL DATA IN THE LIGHT OF GERMAN LAW Mateusz Badowski, M.Sc.
Faculty of Law European University Viadrina Frankfurt / Oder, Germany e-mail:
[email protected]
Małgorzata Olszewska, M.Sc. Faculty of Law and Administration Cardinal Stefan Wyszynski University Warsaw, Poland e-mail:
[email protected] Abstract The article characterizes public spatial data and discusses the principles of its use on the example of German law. It presents the cross relationships of access and re-use of public spatial data, with particular emphasis on data referred to in the INSPIRE Directive. Keywords: spatial data, public information, re-use Public data Public data is data processed in connection with the implementation of tasks of public administration bodies, regardless of their legal name, i.e. regardless of whether the subject of access is referred to as data or information. In the context of German law, the public data category should primarily include public information (German amtliche Informationen, IFG § 2 point 1), information concerning environment (German Umweltinformationen, UIG § 2 para. 3 UIG), consumer information (German Verbraucherinformationen, VIG § 2 para. 1), as well as spatial data to which access is regulated by the INSPIRE Directive (Article 3 point 2). Therefore, it is possible to distinguish public data from private data in relation to the type of activity of entities that process data (their disposers), taking into account the type of access to it. If there is a public legal claim (request) for access to particular type of data, then surely what is meant is public data. However, with regard to German regulations, due to the federal nature of the legal system and the recognition of the so-called "law of information " among the individual competences of federal states, it can not be assumed that if there is no claim to provide certain data, then this data is not automatically public data. The principle of access to general public data (public record) can only be discussed with reference to the public authorities of federation and federal states that have passed relevant laws. The provisions of the German Constitutional Law (Article 5 (1) GG) guarantee only the freedom of access to data, and not the right of access (OVG (NRW), 2014; WIEBE, AHNEFELD, 2015). Regulations on general access to public information are currently in force in Baden-Württemberg (LIFG (BW)), Berlin (IFG (BE)), Brandenburg (AIG (BB)), Bremen (BremifG), Hamburg (HmbTG), Mecklenburg-Vorpommern (IFG MV), North Rhine-Westphalia (IFG NRW), Rhineland-Pallatinate (LTranspG (RP)), Schleswig-Holstein (IZG-SH), Saarland (SIFG), Saxony-Anhalt (IZG LSA) and the Free State of Thuringia (ThürIFG). In other federal states there is only a presumption of access to data regulated on the federation level as well as belonging to the properties of federal states, to which access has been defined by European Union law. An example of data belonging to the first group is consumer information. It is recognized that the competence to enact the provisions on access to them is derived from the law of the federation (see Art. 74 para. 1, No. 1 and 20 in connection with Art. 72 (2) of the GG; BT-Drs.16/1408). The second category, that is public data, access to which has been determined by the EU law, includes primarily environmental information and spatial data to which access is regulated by the INSPIRE Directive. Public spatial data The definition of spatial data contained in art. 3 point 2 of the INSPIRE Directive, as any data with a direct or indirect reference to a specific location or geographic area, should be treated as widely accepted in both German literature, jurisprudence and legislation (cf. § 3 Abs.1 GeoZG; Article 3 para. 1 BayGDIG; § 3 para. 1 BbgGDIG; § 3 para. 1 LGeoZG (BW); § 3 para. 1 GeoZG Bln; § 3 para. 1 BremGeoZG; § 2 para. 1 7
GeoVermG MV; § 4 point 4 HmbGDIG; § 3 para. 1 NGDIG; § 3 para. 1 GeoZG NRW; § 3 para. 1 LGDIG (RP); § 3 para. 1 GDIG (SH); § 3 para. 1 SGDIG; § 2 para. 1 SächsGDIG; § 3 para. 1 GDIG LSA; § 3 para. 1 ThürGDIG). In Germany, only HVGG § 31 para. 1 defines spatial data as spatial information. In literature, there are rare attempts to move away from defining the concept of spatial data as particular data, describing it as phenomena (German Phänomene, e.g. TWAROCH, 2011). However, this does not affect the meaning of the concept itself. The use of the terms spatial data and infrastructure of “spatial data”, and not “spatial information” is conscious and deliberate, because, on the one hand, infrastructure refers to spatial data which is defined in the directive itself and acts implementing it. On the other hand, the use of the concept of data allows to move away from using the concept of information. Information as a transferable good that reduces uncertainty (SZPOR, 2016) is a subjective concept, i.e. it depends on the recipient's cognitive abilities, and should not be used as a legal term in such sense (BADOWSKI, 2015). Nevertheless, in legal acts, jurisprudence and literature on the subject, the concepts of spatial data and spatial information are used interchangeably as synonyms (BERNARD et al., 2005). Such action should, however, be criticized in relation to the aforementioned postulate of abandoning the use of the notion of information as a legal term with reference to public data, as well as in connection with defining the already legal scope of spatial data as "data". Using different concepts to designate the same subject is inconsistent with the principles of good legislation (BMJ, 2008). Spatial data is data that can be displayed on a map; hence, their most important characteristic feature is spatial reference (SEIFERT, 2008). This reference can be expressed in a variety of ways, e.g. as coordinates, place names or postal addresses (BBG, 2006; ÖROK,2002; TWAROCH, 2011). In this sense, spatial data is "comprehensive data", which can take the form of various other named types of data, in particular, public information, environmental information, consumer information, but also personal data and all named types of secrecy. There is also the possibility of accepting only the element combining specific data, e.g. public information with a specific location, as spatial data. Such a conjunction of data on a specific location and additional data would always be a combination of two types of data: spatial data with a different type of data, in the given example public information. Spatial data would therefore only be an element connecting other data with a particular location. This assumption would actually create a new data category in the form of spatial data. Spatial data could not at the same time be any other type of data; it would only be a designation of a location, devoid of other cognitive elements. Thus understood spatial data would only answer the question "where", while other types of data would answer the question "what" (is located). Such interpretation of the spatial data concept would, on the one hand, result in the alignment of spatial data, e.g. with coordinates, and, on the other hand, it would not give any cognitive effect. Therefore, the distinction of spatial data as a connector in the form of spatial reference only seems to be pointless. Accordingly to the law in force, public spatial data are spatial data processed in connection with the implementation of tasks of public administration bodies. The processing itself should be interpreted broadly (Article 4 (2) of the GDPR) as any operation or set of operations which is performed on data, unless specific provisions state otherwise. At the same time, the specification of the concept of processing, e.g. spatial data, and paying particular attention to the correlation (combination) of data and spatial data services as an element of processing (cf. § 3 para. 9 GDIG (SH)) do not seem to be necessary. The exegesis of the concept of "processing" indicates an extremely wide scope of meaning, and in the case of doubts allows its expansive interpretation. Therefore, it is unnecessary to additionally emphasize that the correlation between data and spatial services is processing because combining all kinds of data, not only items of spatial data, already meets the defining criteria for processing. This technique was used, for instance, in Hamburg (cf. HmbGDIG § 10 para. 2) while referring directly only to the provisions on personal data protection (BADOWSKI, 2016). From among all public spatial data, it is necessary to distinguish the specific type of public spatial data regulated by the INSPIRE directive: "INSPIRE spatial data", access to which is defined by the said directive and acts implementing it to the legal systems of the Member States of the European Union. This includes broadly understood • thematic data (themes included in Annexes I-III of the INSPIRE Directive were literally transferred to all acts transposing this directive into the German legal order), which contains references to a specific location or area, • and which characterizes a given type of access in the form of spatial data services (in relation to the characteristics of spatial data services in Germany, see BADOWSKI, 2014). • Thematic data is available through the geo-portal (Article 3 point 8 of the INSPIRE Directive), that is to say, a point of access to the data on the spatial data infrastructure (Article 3 point 1 of the INSPIRE Directive).
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The data to which access can be obtained in the described way must meet the criteria specified in individual statutes as to the electronic form and must also be at the disposal of public administration bodies (Article 4 point 1 of the INSPIRE Directive). At the same time, public administration body (German Behörde) within the meaning of Article 3 point 9 of the INSPIRE Directive should be interpreted broadly. This term is synonymous to the public administration body referred to, e.g. Article 2 point 2 of Directive 2003/4 /EC and to the authority obliged to provide information (German informationspflichtige Stelle) within the meaning of § 2 point 1 of the German Federal act on environmental information (UIG, see also HOFFMANN, SCHULZ, 2014; BT-Drs. 15/3406). The concept of spatial data is a basic term for determining the thematic scope of the so-called "spatial data infrastructure law" distinguished in Germany. The separation of such an area could be indicated, for example, by the title of the monograph "Spatial data infrastructure law in federations and federal states" (VON JANOWSKY, 2010). "Spatial data infrastructure law", however, should not be treated as a separate branch of law, although the basic elements characterizing these provisions are noticed in the German doctrine (MARTINI, DAMM, 2013) against other types of public data. In fact, spatial data stands out, above all, due to its value and versatile possibilities of use. It is estimated that, on average, about 80% of all decisions made in private and professional life, but also by public administration, are characterized by reference to a specific point or geographic area (LANDSBERG, 2004; IMAGI, 2010; SPIER, 2010; KLAR, 2012). However, this is not enough to recognize spatial data, whether public or private, for constituting a new branch of law. The use of public spatial data By re-use (German Weiterverwendung) of "information" at the disposal (German vorhanden) of public administration bodies one should understand any use (German Nutzung) of data for commercial and non-commercial purposes that exceeds the use associated with the performance of public tasks. Taking note of information and making use (German Verwertung) of knowledge acquired in this way do not constitute a re-use in accordance with § 2 point 3 of the IWG- Federal act on the re-use of information of public administration bodies transposing the REUSE directive into the German legal system. Despite the existence of definitions of legal access and re-use of public data, the relationship between the two concepts has not yet been sufficiently explained in literature (SCHULZ, 2014), and seems to be necessary (DREIER et al., 2016), if only due to the fact that the legislator used different terms to define them. It should therefore be assumed that they have different scopes of meaning (BMJ, 2008). There are differences in the legal consequences of using these powers (DREIER et al., 2016), although their purpose might also be identical (STEFANOWICZ, 2011). However, the German legislator explicitly wanted to separate these two concepts due to the fact that the acts on access to public data do not sufficiently regulate the rules of their use (BR-Drs. 358/06). Therefore, the principle of re-use of unconditionally released public data was also introduced (§ 2a IWG; see also BT-Drs.18/4614). This principle, although already confirmed in earlier judicial decisions (see, for example, OVG (NRW), 2014), was clearly regulated only in the IWG amendment of 2013 through the introduction of § 1 point 2a IWG (see also FUHRMANN et al., 2014; MARTINI, DAMM, 2013). Theoretically, there should be no common areas for access and re-use of public data (DREIER et al., 2016). However, there are interdependencies between these powers, because the very principle of re-using public data is not unconditional. The right to re-use certain data depends on the existence of the right to unconditional access. If the right to access does not exist, requires a legal or factual interest or is a discretionary decision of the public administration body, the right of unconditional re-use of data does not exist. Such data cannot be unconditionally re-used - even if as a consequence access will be granted (see, for example, § 3 point 2 VIG regarding consumer information). Powers to re-use of public data are therefore dependent on criteria both limiting and excluding access to this data (WIEBE, AHNEFELD, 2015a). As a consequence, it can be considered that access to public data and its re-use are the successive elements of one process. The unconditional right to re-use public data access itself is not, however, the decisive factor, but rather it is the existence of the right to unconditional access (SCHULZ, 2014). If data is made accessible in a pro-active way by public administration bodies, that is, published without request and made available to an unspecified public, there is also an unconditional right to process such data (BT-Drs.18/4614), unless specific provisions regulate this matter differently. For example, general provisions on the re-use of public data do not relate to information concerning environment and "spatial data". The German federal act on the re-use of public sector information contains a clear subject exclusion and does not apply to information on the environment and spatial data (so explicitly § 1 point 2 no. 8 IWG). At the same time, it should be noted that the German legislator, when
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writing about spatial data, incorrectly identifies it with spatial data to which access is regulated by the INSPIRE Directive, and to which he refers de facto in the said paragraph. IWG is lex generalis in relation to specific laws on access to public data that regulate the re-use of this data. Such acts include the aforementioned laws regulating access to information concerning environment (UIG) and INSPIRE spatial data (e.g. GeoZG, cf. BT-Drs.18/4614). For this reason, the provisions on the use of this particular public data are directly regulated by these special laws. It seems, therefore, that the provision of § 1 point 2 no. 8 of the IWG is unnecessary, because the common conflict-oflaw rules exclude the application of general IWG principles to special laws that regulate the re-use of this data. In addition, the aims of the REUSE directive are to complement, for instance, the objectives of the INSPIRE Directive (point 8 of the preamble to the INSPIRE Directive). Hence, where only the data form permits this spatial data can be used freely (Article 14 point 3 of the INSPIRE Directive). Conclusions The main criterion for the division of spatial data is the distinction between spatial private and public data. Distinguishing public spatial data from private spatial data is possible in relation to the type of activity of entities that administer this data, taking into account the type of access to them. If there is a public-law claim (request) for access to data of a specific type, it is referred to as public spatial data, although the lack of such a claim or the denial of access do not cause the loss of the "public" attribute of certain data. Public spatial data is not only the data access to which is regulated by the INSPIRE Directive. It can also correspond to all types of named public data, in particular public information, environmental information and consumer information. The right to use public data unconditionally depends on the existence of an unconditional right to access this data. As a consequence, it can be considered that access to public data and its re-use are the successive elements of one process. Regulations on the re-use of public data are lex genarlis in relation to the provisions on the use of public data contained in the Access Acts, e.g. in relation to the INSPIRE spatial data. It results from common conflict-of-law rules, so there is no need for special regulation in this respect. References BADOWSKI, M. 2014. Implementacja dyrektywy INSPIRE w ujęciu prawno porównawczym. (Implementation of the INSPIRE directive in a comparative legal perspective). In: M. Jankowska, M. Pawełczyk (Editors). Geoinformacja prawo i praktyka, Warszawa, p. 73–74. BADOWSKI, M. 2015. Legal limitations of public access to spatial data in Germany. In: G. Szpor, A. Gryszczyńska, (Editors). Access to spatial data and its limitations. Legal aspects, Zagreb, p. 40-49 (41). BADOWSKI, M. 2016. Wpływ przetwarzania danych przestrzennych w smartcity na bezpieczeństwo publiczne. Perspektywa polsko-niemiecka. (The impact of spatial data processing in smartcity on public safety. Polish-German perspective). In: G. Szpor (Editor). Internet rzeczy. Bezpieczeństwo w Smart City, Warszawa, p. 245–258 (249-250). BBG (Botschaft zum Bundesgesetz über Geoinformation), 2006. chBBl 2006 from 06.09.2006, p. 7817– 7886 (7843). BERNARD, L., CROMPVOETS, J., FRITZKE, J. 2005. Geodateninfrastrukturen - ein Überblick (Spatial data infrastructures - overview). In: L. Bernard, J. Fritzke, R. Wagner, R (Editors). Geodateninfrastruktur: Grundlagen und Anwendungen, Heidelberg, p. 3–8 (3). BMJ (Bundesministerium der Justiz), 2008. Handbuch der Rechtsförmlichkeit. Empfehlungen des Bundesministeriums der Justiz für die rechtsförmliche Gestaltung von Gesetzen und Rechtsverordnungen nach § 42 Absatz 4 und § 62 Absatz 2 der Gemeinsamen Geschäftsordnung der Bundesministerien (Book of principles of legislative technique), Ed. 3, Köln (nb. B.74). /http://hdr.bmj.de/page_b.1.html (access 31.03.2018). BR-Drs. 358/06 (Deutscher Bundesrat, Drucksache 358/06) from 26.05.2006, p. 18. /http://dipbt.bundestag.de/dip21/brd/2006/0358-06.pdf (access 31.03.2018). BT-Drs. 15/3406 (Deutscher Bundestag, Drucksache 15/3406) from 21.p6.2004, p. 12. /http://dip21.bundestag.de/dip21/btd/15/034/1503406.pdf (access 31.03.2018). BT-Drs. 18/4614 (Deutscher Bundestag, Drucksache 18/4614) from 15.04.2015, p. 12-13. /https://dip21.bundestag.de/dip21/btd/18/046/1804614.pdf (access 31.03.2018). DREIER, T., FISCHER, V., VAN RAAY, A., SPIECKER GEN. DÖHMANN, I. 2016. Informationen der öffentlichen HandZugang und Nutzung (Public information – access and use), Baden-Baden, p. 252, 253, 261. 10
FUHRMANN, S., KLEIN, B., FLEISCHFRESSER, A. 2014. Arzneimittelrecht. Handbuch für die pharmazeutische Rechtspraxis, (Pharmaceutical law), Ed. 2, Baden-Baden, § 44 nb. 7. HOFFMANN, CH., SCHULZ, S., 2014. Open Data für Kommunen (Open Data dla gmin). KommJur, 4: 126–132 (128). IMAGI (Interministerieller Ausschuss für Geoinformationswesen), 2010. Geoinformation und moderner Staat. Eine Informationsschrift des Interministeriellen Ausschusses für Geoinformationswesen (Geoinformation and modern state. Information brochure of the Interministerial group for geoinformation), Berlin, pp. 9. JANOWSKY VON D., LUDWIG, R., ROSCHLAUB, R., STREUFF, H. 2010. Geodateninfrastrukturrecht in Bund und Ländern (The law on spatial data infrastructure in Federation and Federal States), Wiesbaden. KLAR, M. 2012. Datenschutzrecht und die Visualisierung des öffentlichen Raums (Data protection law and visualisation of public space), Berlin, p. 23. LANDSBERG, W. 2004. eGovernment in Kommunen. Grundlagen und Orientierungshilfen (eGovernment in municipalities. Basics and advice), Heidelberg, p. 154. MARTINI, M., DAMM, M. 2013. Auf dem Weg zum Open Government: Zum Regimewechsel im Geodatenrecht (On the way to Open Government: changes in spatial data law). DVBl, 1: 1–9 (3). ÖROK (Österreichische Raumordnungskonferenz), 2002. Empfehlung Nr. 51 zur Führung Geographischer Informationssysteme. Aktualisierung und Erweiterung hinsichtlich einer österreichischer Geodatenpolitik (Recommendation no. 51 on the operation of geographical information systems), p. 8. /http://www.oerok.gv.at/fileadmin/Bilder/5.Reiter-Publikationen/OEROK-Empfehlungen /oerok_empfehlung_51.pdf (access 31.03.2018). OVG (NRW), 2014. Judgment of the Higher Administrative court of North Rhine Westphalia), Sygn. 8 A 1129/11, nb. 51-53, 101. SEIFERT, M. 2008. Wissenschaftlicher Beitrag für den Aufbau einer Geodateninfrastruktur zur Lösung von Aufgaben des E-Government (Scientific contribution to building spatial data infrastructure for fulfilling eGovernment tasks), Zurich, p. 20. SPIER, S. 2010. Wie persönlich ist persönlich? (How personal is personal?) Acquisa 5: 70–72 (70). STEFANOWICZ, J. 2011. Opinia do ustawy o zmianie ustawy o dostępie do informacji publicznej (Opinion on the act amending the act on access to public information), Polski Senat, Druk nr 8/1352 z 3.9.2011, p. 5-6. /http://ww2.senat.pl/k7/dok/opinia/2011/op60911.pdf (access 31.03.2018). SZPOR, G., 2016. Jawność i jej ograniczenia. Tom I. Idee i pojęcia (Transparency and its limitations. Volume 1. Ideas and concepts), Warszawa (Rozdz. 2, § 3, pkt II). TWAROCH, C. 2011. Geoinformation und Recht (Geoinformation and law), Wien-Graz, p. 21, 22. WIEBE, A., AHNEFELD, E., 2015. Zugang zu und Verwertung von Informationen der öffentlichen Hand- Teil IZugang zu Informationen und IFG (Access to and use of public information, part 1: access to information and IFG), CR 2, p. 127–136 (128). WIEBE, A., AHNEFELD, E. 2015a. Zugang zu und Verwertung von Informationen der öffentlichen Hand- Teil IIWeiterverwendung von Informationen- Open Government und Open Data (Access to and use of public information, part 2: re-use of information – Open Government and Open Data), CR 3, p. 199–208 (205). List of legal acts AIG (BB)
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BayGDIG
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BbgGDIG
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BremGeoZG
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BremIFG
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Akteneinsichts- und Informationszugangsgesetz (AIG) vom 10.3.1998 (GVBl.I 1998, 46, zuletzt geändert:GVBl.2013 I Nr. 30) (Brandenburg) (Act on file revision and access to information in Brandenburg) Bayerisches Geodateninfrastrukturgesetz (BayGDIG) vom 22.7.2008 (GVBl.2008, 453, zuletzt geändert:GVBl.2014, 286) (Bavarian act on spatial data infrastructure) Gesetz über die Geodateninfrastruktur im Brandenburg (Brandenburgisches Geodateninfrastrukturgesetz- BbgGDIG) vom 13.4.2010 (GVBl.I 2010, Nr.17) (Act on spatial data infrastructure in the Federal State of Brandenburg) Gesetz über den Zugang zu digitalen Geodaten des Landes Bremen (Bremisches Geodatenzugangsgesetz- BremGeoZG) vom 24.11.2009 (Brem.GBl.2009, S. 531, zuletzt geändert:Brem.GBl.2016, S. 803) (Law on access to digital spatial data in the Federal State of Bremen) Gesetz über die Freiheit des Zugangs zu Informationen für das Land Bremen (Bremer InformationsfreiheitsgesetzBremifG) vom 16.5.2006 (Brem.GBl.2006, S. 263, zuletzt geändert:Brem.GBl.2015, S. 274) (Act on freedom of access to information in the Federal State of Bremen) 11
Directive 2003/4 /EC
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The INSPIRE Directive
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REUSE directive
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GDIG (SH)
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GDIG LSA
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GeoVermG MV
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GeoZG
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GeoZG Bln
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GeoZG
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GG
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HmbGDIG
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HmbTG
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HVGG
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IFG
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IFG (BE)
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IFG MV
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IFG NRW
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Directive 2003/4 / EC of the European Parliament and of the Council of 28 January 2003 on public access to environmental information and repealing Council Directive 90/313 / EEC, Official Journal L 041, 14.2.2003, p. 26-32 Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE), Official Journal L 108, 25.4.2007, p. 1-14 Directive 2003/98/EC of the European Parliament and of the Council of 17 November 2003 on the re-use of public sector information, Official Journal L 345, 31.12.2003, p. 90–96 Geodateninfrastrukturgesetz für das Land Schleswig-Holstein (GDIG) vom 15.12.2010 (GVOBl.2010, S. 717, zuletzt geändert: GVOBl.2017, S. 218) (Act on spatial data infrastructure in the Federal State of Schleswig-Holstein) Geodateninfrastrukturgesetz für das Land Sachsen-Anhalt (GDIG LSA) vom 14.7.2009 (GVBl.LSA 2009, 368) (Act on spatial data infrastructure in the Federal State of Saxony-Anhalt) Gesetz über das amtliche Geoinformations- und Vermessungswesen (Geoinformations- und Vermessungsgesetz- GeoVermG MV) vom 16.12.2010 (GVOBl.MV 2010, S. 713) (Act on official geoinformation and geodesy in Mecklenburg-Vorpommern) Gesetz über den Zugang zu digitalen Geodaten vom 10.2.2009 (BGBl.2009 I S. 278, zuletzt geändert: BGBl.2012 I S. 2289) (Federal Act on Access to Digital Spatial Data) Gesetz über den Zugang zu digitalen Geodaten im Land Berlin (Geodatenzugangsgesetz Berlin- GeoZG Bln) vom 3.12.2009 (GVBl.2009, 682, zuletzt geändert: GVBl.2016, 100) (Act on access to digital spatial data in the Federal State of Berlin) Gesetz über den Zugang zu digitalen Geodaten Nordrhein-Westfalen (Geodatenzugangsgesetz-GeoZG NRW) vom 17.2.2009 (GV.NRW.2009, 84) (Act on access to digital spatial data in North Rhine-Westphalia) Grundgesetz für die Bundesrepublik Deutschland vom 23.5.1949 (BGBl.1949, S. 1, zuletzt geändert: BGBl.2017 I, S. 2347) (Basic Law for the Federal Republic of Germany) Hamburgisches Geodateninfrastrukturgesetz (HmbGDIG) vom 15.12.2009 (HmbGVBl.2009, S. 528, zuletzt geändert: HmbGVBl.2017, S. 348) (Hamburg act on spatial data infrastructure) Hamburgisches Transparenzgesetz (HmbTG) vom 19.6.2012 (HmbGVBl.2012, S. 271) (Hamburg transparency act) Hessisches Gesetz über das öffentliche Vermessungsund Geoinformationswesen (Hessisches Vermessungsund Geoinformationsgesetz - HVGG) vom 6.9.2007 (GVBl.I 2007, S. 548, zuletzt geändert: GVBl.2012 S. 290) (Hessian act on public geodesy and geoinformation) Gesetz zur Regelung des Zugangs zu Informationen des Bundes (Informationsfreiheitsgesetz - IFG) vom 5.9.2005 (BGBl.2005 I S. 2722, zuletzt geändert: BGBl.2013 I S. 3154) (Act regulating access to Federation information) Gesetz zur Förderung der Informationsfreiheit im Land Berlin (Berliner Informationsfreiheitsgesetz - IFG) vom October 15, 1999 (GVBl.1999, S. 561, zuletzt geändert: GVBl.2018, S. 160) (Law supporting freedom of information in the Federal State of Berlin) Gesetz zur Regelung des Zugangs zu Informationen für das Land Mecklenburg-Vorpommern (Informationsfreiheitsgesetz- IFG MV) vom 10.7.2006 (GVOBl.MV 2006, S. 556, zuletzt geändert: GVOBl.MV 2011, S. 277) (Act regulating access to information in the Federal State of MecklenburgVorpommern) Gesetz über die Freiheit des Zugangs zu Informationen für das Land Nordrhein-Westfalen (Informationsfreiheitsgesetz Nordrhein-Westfalen - IFG NRW) vom 27.11.2001 (GV.NRW.2001, S. 806, zuletzt geändert: GV.NRW.2014, S. 622) (Act on the freedom of access to information in the Federal State of 12
IWG
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IZG LSA
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IZG-SH
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LGDIG (RP)
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LGeoZG (BW)
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LIFG (BW)
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LTranspG (RP)
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NGDIG
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SächsGDIG
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SGDIG
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SIFG
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ThürGDIG
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ThürIFG
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UIG
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VIG
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North Rhine-Westphalia) Informationsweiterverwendungsgesetz (IWG) vom 13/12/2006 (BGBl.2006 I S. 2913, zuletzt geändert: BGBl.2015 and S. 1162) (Federal act on the re-use of information) Informationszugangsgesetz Sachsen-Anhalt (IZG LSA) vom 19.6.2008 (GVBl.LSA 2008, S. 242, zuletzt geändert: GVBl.LSA 2018, S. 10, 12) (Act on access to information in Saxony-Anhalt) Informationszugangsgesetz für das Land Schleswig-Holstein (IZG-SH) vom 19.1.2012 (GVOBl.2012, S. 89, zuletzt geändert GVOBl.2017, S. 279, ber.S. 509) (Act on access to information in the Federal State of Schleswig-Holstein) Landesgeodateninfrastrukturgesetz (LGDIG) vom 23.12.2010 (GVBl.2010, S. 548, zuletzt geändert: GVBl. 2011, S. 427, 428) (Rheinland-Pfalz) (Domestic act on spatial data infrastructure in Rhineland-Palatinate) Gesetz über den Zugang zu digitalen Geodaten für Baden-Württemberg (Landesgeodatenzugangsgesetz - LGeoZG) vom 17.12.2009 (GBl.2009, S. 802, zuletzt geändert: GBI.2017 S. 99, S. 105) (Act on access to digital spatial data in Baden-Württemberg) Gesetz zur Regelung des Zugangs zu Informationen in Baden-Württemberg (Landesinformationsfreiheitsgesetz- LIFG) vom 17.12.2015 (GBl.2015, S. 1201) (Act regulating access to information in Baden-Württemberg) Landestransparenzgesetz (LTranspG, Rheinland-Pfalz) vom 27/11/2015 (GVBl.2015, S. 383) (Domestic transparency act for Rhineland-Palatinate) Niedersächsisches Geodateninfrastrukturgesetz (NGDIG) vom 17/12/2010 (Nds.GVBl.2010, S. 624) (Act on spatial data infrastructure in Lower Saxony) Sächsisches Geodateninfrastrukturgesetz vom 19.5.2010 (SächsGVBl.2010, S. 134, zuletzt geändert:SächsGVBl.2016, S. 507, 508) (Saxon act on spatial data infrastructure) Saarländisches Geodateninfrastrukturgesetz (SGDIG) vom 1.7.2009 (ABl.2009 I S. 1426, zuletzt geändert:ABI.2015 I S. 790) (Act on spatial data infrastructure in Saarland) Gesetz Nr.1596 Saarländisches Informationsfreiheitsgesetz (SIFG) vom 12.7.2006 (ABl.2006 I S. 1624, zuletzt geändert: ABI.2015 and S. 790) (Act no. 1596 on freedom of information in Saarland) Thüringer Geodateninfrastrukturgesetz (ThürGDIG) vom 8.7.2009 (GVBl.2009, S. 574, zuletzt geändert: GVBl.2016, S. 525) (Act on spatial data infrastructure in Thuringia) Thüringer Informationsfreiheitsgesetz (ThürIFG) vom 14/12/2012 (GVBl.2012, S. 464, zuletzt geändert: GVBl.2014, S. 529, 544) (Act on freedom of information in Thuringia) Umweltinformationsgesetz vom 22.12.2004 (BGBl.2014 I S. 1643, zuletzt geändert: BGBl.2017 and S. 2808) (Federal act on environmental information) Verbraucherinformationsgesetz vom 5.11.2007 (BGBl.2012 I S. 2166, 2725, zuletzt geändert: BGBl.2013 I S. 3154) (Federal act on consumer information)
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GEOINFORMATION ANALYSIS AND MARKET VALUE OF SAFE SPATIAL – SAFE PLACE Prof. Tomasz Bajerowski Institute of Geoinformation and Cartography Faculty of Geodesy, Geospatial and Civil Engineering University of Warmia and Mazury in Olsztyn Olsztyn, Poland e-mail:
[email protected] Abstract The marked value of spatial identified with the market value of real estate, in addition to many other factors, is also determined by the safety status of the spatial (place), and the safety of place is determined by the state of its features. The analysis of the status of spatial features that determine its safety lies in their geoinformation inventory and subsequent evaluation and valorisation allowing for the development of, inter alia, hazard maps and comparative analysis, as a result of which we can determine the share of space safety in the market value of real estate located in it. The article presents theoretical considerations on space safety leading to proposals for the practical use of known methods for estimating the value of non-market goods to assess the market value of a safe space based on data obtained from geoinformation analysis. Key words: market value, spatial safety, value of spatial safety Introduction Determining the state of spatial safety, which provides the basis for rational, optimal development of the planning space, is similar (from a methodological point of view) to assessment and valuation of any qualitative good. For this reason, it would be worthwhile to try to adapt for this purpose some already established methods for evaluating such goods - for instance, an evaluation of landscape value or assessment of the environmental condition (BAJEROWSKI et al., 2007; BIŁOZOR et al., 2018; KOWALCZYK, 2015, 2016, 2017). The useful value of a safe space is generally unquestionable - it is obvious. People want to live in and be surrounded by an environment with high safety status. Undoubtedly, space, demonstrating a high useful value, also has a high market value from the perspective of its safety, which is expressed, in its simplest dimension, in high real estate prices. Therefore, apart from the problems of assessment and valuation of spatial safety, it is also necessary to carry out (not less important) an evaluation of spatial safety, the useful value of which must have a market value. It becomes important to evaluate how much it can cost to plan and then to implement a spatial design project that would be considered safe, although in the general meaning safety is “priceless”, since it is one of the basic conditions of human existence. Definition: Spatial safety is the characteristics of a specific place and time which, with a specific likelihood, which favour the occurrence (emergence) of specific crisis events (phenomena) or, with a specific likelihood, relatively continuously keeps this space in a condition of unacceptable perception of specific risks. With safety thus defined, its condition in space is the function of the configuration (or a group) of characteristics (geo-information), as a set of features occurring in a given area in correlation with the perception of safety in the general meaning of this term (BAJEROWSKI, 2003). However, spatial safety does not result directly from the state of its characteristics - it results from the competence and experience of a human being being in this space. Isolated, dehumanised space is neutral - it is neither safe nor dangerous. Two people with different history can perceive the same space in a quite a different manner. This is an intuitive assessment, but it gives rise to expert evaluation. This means that experts on the entire range of specific risks resulting from the configuration of spatial characteristics should participate in the evaluation of safety status and that there is no general notion for spatial safety – it can be considered only in the context of specific risks. Identification of specific risks resulting from a specific configuration of spatial features can be conducted by experts, since “common” people do not perceive important correlations that can be observed by experts as a result of their knowledge and, above all, experience. Expert opinions also contain 14
an intuitive load, but expert knowledge often replaces still imperfect, although objectivised knowledge gathered through analytical software. Is safety a feature and characteristic of space or is it a psychological and sociological category independent of the safety status of space? It cannot be a category separated from spatial conditions, although the state of safety felt in a specific place directly depends on those spatial conditions. However, as it was emphasized above, the same characteristics of space cause fear and anxiety in some people, while in others they do not, or do, but to a much lower degree. In other words, it is also the result of life experience and knowledge of people evaluating this status. The same situation concerns quality criteria. For example, the esthetical value of a landscape is something that is absolutely determined by the features of space, but also, and on equal basis, by the perception of aesthetic values by specific persons, and each person has his or her own history, knowledge and aesthetic experience. Consequently, there is nothing unusual or difficult in the evaluation of landscapes, and likewise, there should not be any major problems in evaluating the condition of spatial safety (or perhaps the status of human safety in space). Approaches of this type must be useful. Therefore, the monetary evaluation of the spatial safety status, e.g. using the replacement cost method, willingness to pay, etc. also must have useful application for evaluation of spatial safety status. Value of spatial safety A claim could be made that safety has a value, which can be expressed in two dimensions - a useful value and a market value, with the latter obviously resulting from the former. Spatial safety clearly has a value. In caring about its status, we are willing to bear both the direct and indirect costs of restoring the expected condition of space and costs of maintaining it in this state. However, since safety cannot be bought, it does not have a market measure of value, i.e. a price. Spatial safety is a feature of space which, like other quality features, is not directly traded in the market - nobody sells a landscape value or spatial safety – but those values directly contribute to the value of a real estate demonstrating specific landscape condition or spatial safety state. However, since properties are traded, they have a market value and prices. People are willing to pay more for high values of such features while buying real estates with such characteristics, and they are ready to make regular payments to keep those features in a higher value state. Therefore, for spatial safety, as one of its key features, market transactions do not exist. Consequently, pursuant to the theory of economics, it is a public good. The spatial safety in a given area is used by anybody who lives or stays there. For this reason, it is possible to attempt to evaluate spatial safety, applying methods corresponding to those applied to determine the value of other spatial characteristics operating as non-market goods. Safety, and its state in a specific location, is therefore a non-market good, which does imply that it is not an economic good. Its economic value results from the fact that people are ready to pay for this good indirectly, paying for purchased properties or for the right to stay in a specific place. Four systems (formats) for evaluating non-market resources (WOŚ, 1995), which undoubtedly include the value of spatial safety (just like, for example, the aesthetic value of this space, identified with landscape quality and, consequently, its value) can be distinguished: 1. The format of individual preferences - if people have any preferences with regard to any resources, this means that in attributing any importance to them, they value them. The more important are given resources for satisfying our needs and higher preferences are assigned to them, which directly translates into an increase in its value. Such an evaluation is of a subjective nature, but in relation to the fact that preferences of individuals are revealed in their choices, which become mass choices, the evaluation of such resources is objectivised. Consequently, it can be claimed that such resources have prices because people give prices to them according to their own preferences. The main principle of this format - a resource is worth as much as somebody is willing to pay for it, i.e. the safety of a specified fragment of space has a market value equal to how much people living or using this space are willing to pay for the state of characteristics describing this space that guarantees to them safety at the expected level. 2. The hedonistic format – results from the hedonism theory, according to which pleasure is the only aim of the human being and the motive of his behaviour. Man strives for consumption of all available pleasures. Spatial safety is strictly related to quality of life, and achieving pleasure requires being in a safe environment. Using appropriate statistical techniques, the hedonistic approach aims at: a) determining what part of the variance in the safety state depends on differences in the characteristics of this space, b) determining how much people are able to pay to improve spatial safety and to live in better conditions. 15
3.
Format of conditional valuations - based on sociological studies on human behaviour in hypothetical situations. The question can be posed: how much are people ready to pay for a given benefit or good and is there anything to compensate for the expenses (costs) they bear? This method is based on the personal (unit) assessments of respondents and their reaction to an increase or decrease in the quality of a certain good in the condition of a hypothetical market. This method assumes that the respondent knows what is a benefit and what is a cost. The value is determined in an iterative process. Gradually increasing prices, the respondent stops at the price level he is ready to pay. Similarly, a readiness to pay the minimum price is established. 4. The form of the alternative cost assumes that each choice involves resignation from something else. The most precious unit that we are ready to abandon in order to acquire another good determines its alternative cost. If the values of spatial safety cannot be directly determined, or such determination is very difficult, the methods applying intermediate pricing can be used for this purpose. Some of them can be useful. The first of them is the Hedonic Pricing Method - HPM. The Hedonic Pricing Method is also referred to as a method for determining the price of pleasure. The main assumption underlying hedonic prices is the claim that the price for a specific market good - real estate, related to a non-market good spatial safety, can be split into the sum of attributes making up this good. For real estate, the attributes could also include the state of spatial safety (FOLMER et al., 1996; WINNPENNY, 1995). The concept of hedonic prices is the result of observations, which show that the price for some goods depends on their non-market characteristics that can be isolated, including those related to space. Based on the transactions made, the value of the features of our interest is indirectly established. Nonmarket prices are evaluated on the basis of observed market transactions concerning properties characterized by various intensity levels of those features. The value of a non-market good (e.g. spatial safety) is determined through the application of statistical methods. Using econometric techniques, the function of the hedonic price is determined, explaining property prices resulting from various features of space occurring in various places. As a result of applying the statistical analysis method, the coefficients determining how, with the highest probability, the market value of the property will change if the quality or level of one of the factors included in the model is changed (e.g. the spatial safety state). The coefficient corresponding to the “quality” of spatial safety determines the amount of an additional payment that the purchasers are willing to make for the property situated in the area characterized with higher safety values in comparison to the price of a comparable property located in an area of lower spatial safety values. Consequently, this is the value attributed by potential purchasers to the value of spatial safety in the context of a real estate market. The Contingent Valuation Method – CVM is a method based on survey questionnaires developed for the purposes of analysing the demand for goods (opportunities) and services that are not present in the market, in cases when direct observations are not possible (FOLMER et al., 1996; WINNPENNY, 1995). The respondents are asked to specify the maximum amount they would be willing to pay for a given good - including spatial safety, as if they were to purchase this good in an imaginary market. Two formulas of this method are used, describing: • How much the consumers are willing to pay for a given good - Willingness To Pay (WTP). It is assumed that spatial safety is worth as much as much people are ready to pay to use a safe space. • How much consumers are willing to accept in order to maintain a given good at the specified level of quality - Willingness To Accept (WTA). The readiness of the consumer to accept a certain amount in exchange for maintaining the space in a specific state of safety. Geo-information analysis of spatial features. Risk matrix (BAJEROWSKI et al., 2015) combines the characteristics of space identified as significant from the perspective of spatial safety and the likelihood of specific risks in a given area. The lower the likelihood of those risks, the safer is the space, for obvious reasons. Estimating the probabilities requires: • creating risk matrix Mz, created according to the idea of probabilistic causality - a preceding event contributes to a later event since it belongs to its history, but it is not certain whether it causes this later event (BAJEROWSKI, 2003); • identification of those places and taking an inventory of features generating risks - creating an inventory matrix I ; • multiplication of matrix I by matrix Mz to obtain the resulting matrix, directly coinciding with the digital elevation map. 16
Estimating the values of the above-mentioned likelihoods is the most important issue. This can be achieved by analysing historically observed events or using the expert method. The cell located at the intersection of the row with the column shows the numerical representation of the likelihood that describes "to what extent" a given feature of space in a specific state favours a given type of risk. There are many features in space, and many types of risks can be taken into account. Therefore, the accumulation of various features also favours various risks to a various degree the likelihood of risk depends on the accumulation of those features in a given place (in a given area) and, of course, increases along with an increase in the number of those features. The inventory of those features in real space will therefore allow the use of a matrix of risks to identify the areas (places) characterized by an increased (and varied) likelihood of various risks affecting the state of spatial safety. A sample form of a risk matrix is presented below (Table 1). The sample matrix does not include, for obvious reasons, either a full or a real list of characteristics, or all possible risks - it is of an illustrative nature only. Table 1. Risk matrix. Risk type
Item
K
R
P
W
S
(...)
Features of space
1.
Multi-family housing
0.10
0.33
0.09
0.10
0.05
0.33
1
2.
Single-family housing
0.05
0.08
0.07
0.07
0.01
0.72
1
3.
Administrative buildings
0.33
0.33
0.20
0.07
0.05
0.02
1
4.
Underground station
0.50
0.08
0.15
0.20
0.03
0.04
1
5.
Shopping centre
0,25
0,58
0.03
0.03
0.03
0.08
1
6.
Railway station
0.30
0.10
0.08
0.10
0.10
0.32
1
7.
Bus stop
0.33
0.09
0.07
0.05
0.01
0.45
1
8.
Tram stop
0.33
0.08
0.08
0.05
0.01
0.45
1
9.
One-level intersection (three roads)
0,62
0.10
0.11
0.13
0.01
0,03
1
10.
One-level intersection (four roads)
0,62
0.10
0.11
0.13
0.01
0,03
1
11.
Multi-level intersection
0.45
0.05
0.11
0.13
0.01
0.25
1
12.
Petrol station
0.03
0.10
0,60
0.15
0.01
0,11
1
13.
Open area
0,45
0,05
0.22
0.11
0.01
0.16
1
n.
(...)
...
...
...
...
...
...
1
1/(...)
1/(...)
1/(...)
1/(...)
1/(...)
1/(...)
1
LIKELIHOOD P(Z) (for n characteristics)
Key: Denotations: K – communication risk R – criminal risks, P – fire risks, W – flood risks, S – weather risks, n – number of space characteristics, (...) – other characteristics, other types of attacks. P(Z) – likelihood of a specific type of attack in a given place. Source: (BAJEROWSKI, KOWALCZYK, 2013).
Therefore, if, for example, one place accumulates such characteristics as administrative buildings, an underground station and a multi-level intersection (which is not something unique in a large city) then the likelihood of specific types of terroristic attacks, calculated as a sum of likelihoods in individual columns and weighted by a number of surveyed features amounts to (Table 2): Table 2. Risk matrix. Item
Type of attack (risk)
K
R
P
W
S
(...)
Features of space 3.
Administrative buildings
0.33
0.33
0.20
0.07
0.05
0.02
1
4.
Underground station
0.50
0.08
0.15
0.20
0.03
0.04
1
11.
Multi-level intersection
0.45
0.05
0.11
0.13
0.01
0.25
1
PROBABILITY P(Z) (for 3 features)
0.42
0.16
0.16
0.13
0.03
0.10
1
Key: Denotations: K – communication risk R – criminal risks, P – fire risks, W – flood risks, S – weather risks, n – number of space characteristics, (...) – other characteristics, other types of attacks. P(Z) – likelihood of a specific type of attack in a given place. Source: (BAJEROWSKI, KOWALCZYK, 2013).
(0.42).
The analysed place is characterized by the lowest likelihood of communication risks (accidents) 17
Inventory matrix I – an inventory of characteristics can be prepared in many ways. An inventory matrix combines the basic field of the analysis with the presence (1) or absence (0) of the analysed space characteristics. A sample inventory matrix can take the form presented below (Table 3). Table 3. Example of inventory matrix. Item
Basic field numbers
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
(...)
Features of space 1.
Multi-family housing
1
0
1
0
1
1
1
0
0
0
0
0
0
0
0
...
2.
Single-family housing
0
1
1
1
1
1
1
1
0
0
1
0
1
0
1
...
3.
Administrative buildings
1
0
1
0
1
0
1
0
0
0
0
1
1
0
1
...
4.
Underground station
1
0
0
0
1
1
1
0
0
1
1
1
0
0
0
...
5.
Shopping centre
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
...
6.
Railway station
1
0
1
0
1
0
0
1
1
0
0
1
1
0
0
...
7.
Bus stop
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
...
8.
Tram stop
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
...
9.
One-level intersection (three roads)
1
0
0
0
0
0
0
0
0
0
1
0
0
0
0
...
10.
One-level intersection (four roads)
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
...
11.
Multi-level intersection
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
...
12.
Petrol station
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
...
Open area
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
...
(...)
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
(...)
13. n.
Source: (BAJEROWSKI, KOWALCZYK, 2013).
The analysis of this simple example of inventory matrix (Table 3) shows that there are basic fields with an accumulation of characteristics that we considered significant from the perspective of generating specific risks in space. At the sites corresponding to those areas in reality (in the physical location), such risks are more probable than in other places. Finding out how high this probability is requires taking into account the information contained in the risk matrix, which assigns a specific unit likelihood to each spatial characteristic (geo-information). The real value of likelihoods, taking into account the occurrence of all features in a given basic field, can be obtained only as a result of multiplying matrix I by matrix Mz, which will give us, in effect, the resulting matrix assigning the value of likelihoods to specific sites within the limits of individual basic fields. As the final step of this analysis, we can develop an isarithmic or zone map of risks to help identify areas of a similar spatial safety state (Fig. 1). Information on market transactions concerning the sale of property drawn on such a map will help to carry out an evaluation which will result in estimating the market value of space in categories in specific safety state levels – therefore, determining the market value of spatial safety. The analysis conducted pursuant to the ceteris paribus principle will produce the values of comparative properties, resulting from adjusting their prices as a result of comparing other characteristics of importance for the local market of properties. The differences in values will result only from the location within specific spatial safety zones - i.e. they will directly indicate the market value of the space where those properties are located. Consequently, by comparing prices obtained in the market in transactions concerning properties that differ only in the value of safety, we can obtain the market value of the spatial safety status. Finally, after application of statistical methods, we will also be able to determine proper coefficients adjusting the market value of properties resulting from their location in areas with specific safety states. Conclusions The state of safety, as the spatial characteristics resulting from a specific set of characteristics of a given space, make specific places more attractive than other locations, and is of significant importance for the market value of real estate located there. Since safe areas are more desired, the demand for properties situated in such areas can be observed in the market. This can be determined using geo-information analysis of the above-mentioned spatial characteristics and, especially, a risk matrix producing a risk map or a map of spatial safety.
18
It is very important, for practical reasons, that the analysis of spatial characteristics which are significant for generating specific safety states can be carried out as desk studies, using information provided in regularly updated geoportals, both specialist and public.
Fig. 1. Fragment of a sample isarithmic map of criminal risk (robberies). The status of safety is determined within the 0.00 – 1.00 range, where 0.00 stands for a safe area, while 1.00 – the most dangerous area (probability of assault close to certain). Source: Own work.
References BAJEROWSKI, T. 2003. Niepewność w dynamicznych układach przestrzennych (Uncertainty in dynamic spatial systems). Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego w Olsztynie. Olsztyn. BAJEROWSKI, T., KOWALCZYK, A. 2013. Metody geoinformacyjnych analiz jawnoźródłowych w zwalczaniu terroryzmu (The methods of Geoinformation open-source analysis in combating terrorism). Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego w Olsztynie. Olsztyn. BAJEROWSKI, T., CHOJKA, A., GERUS-GOŚCIEWSKA, M., GOŚCIEWSKI, D., KOWALCZYK, A., KRAJEWSKA, M., PARZYŃSKI, Z., SZOPIŃSKA, K., ŚWITAŁA, K. 2015. GIS and various approaches of safety management. Croatian Information Technology Society. Croatia. BAJEROWSKI, T., BIŁOZOR, A., KOWALCZYK, A. M. 2018. Theory of Scale-Free Networks as a New Tool in Researching the Structure and Optimization of Spatial Planning. Journal of Urban Planning and Development, 144: 2. FOLMER, H., GABEL, L., OPSCHOOR, H. 1996. Ekonomia środowiska i zasobów naturalnych (Economics of the environment and natural resources). Wyd. Krupski i S-ka. Warszawa. KOWALCZYK, A. 2014. The analysis and creation of landscape aesthetic value network models as important elements of sustainable urban development. In: 9th International Conference on Environmental Engineering, Sustainable Urban Development, Vilnius, Lithuania. KOWALCZYK, A. M. 2015. The use of scale-free networks theory in modeling landscape aesthetic value networks in urban areas. Geodetski vestnik. 59(1): 135–152. KOWALCZYK, A. 2016. Geospatial analysis according to CPTED concept for the safe space designing and management. In: Geographic Information Systems Conference and Exhibition. GIS Odyssey 2016. Croatian Information Technology Society. WINNPENNY, J.T. 1995. Wartość środowiska. Metody wyceny ekonomicznej (The value of the environment. Economic valuation methods). PWE. Warszawa. WOŚ, A. 1995. Ekonomika odnawialnych zasobów naturalnych (Economics of renewable natural resources). PWN. Warszawa.
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THE IMPACT OF SURVEYING WORKS ON THE DEVELOPMENT OF SMART CITY Monika Balawejder, Ph.D. The Bronisław Markiewicz State Higher School of Technology and Economics in Jarosław Institute of Technical Engineering Jarosłw, Poland e-mail:
[email protected]
Katarzyna Matkowska, Ph.D. The Bronisław Markiewicz State Higher School of Technology and Economics in Jarosław Institute of Technical Engineering Jarosłw, Poland e-mail:
[email protected]
H. Ebru Colak, PhD, Assoc. Prof. Karadeniz Technical University Faculty of Engineering Department of Geomatics Engineering, GISLab Trabzon, Turkey e-mail:
[email protected] Abstract The purpose of this article is to determine the impact of surveying works on the development of the Smart City on an example of City Rzeszow. The City of Rzeszow was chosen for detailed research, because Rzeszow ranks 55 in the European Smart Cities ranking. It is worth noting that on the 77 cities assessed from all over Europe, the list included 6 Polish cities, including the City of Rzeszow. In Rzeszow Smart City the research was carried out on 20 districts of cadastral registration. Geodetic works submitted to the Geodesy and Cartographic Documentation Center in Rzeszow in the years 2011-2015 were subject to analysis. The work focused on the group of works most frequently reported to the Center, constituting the following assortment of surveying works: division of real estate, delimitation of real estate, maps for design purposes, geodetic as-built inventory. The article is of research nature, hence a lot of attention was devoted to the analysis of particular assortments of surveying works performed in the Rzeszow Smart City and on the graphic presentation of results. Keywords: Smart City, real estate management, real estate cadastre, spatial planning Introduction The current times are undoubtedly the period of urban development. The process of migration to urban centers is continuously increasing throughout the world. It is estimated that, in a few years, 75% of the population around the globe will have been living in cities (BIEDA et al., 2016). European cities face the challenge of combining competitiveness and sustainable urban development in connection with economic and technological changes caused by globalization and the integration process. Very evidently, this challenge is likely to have an impact on issues of Urban Quality such as housing, economy, culture, social and environmental conditions (PAPADOPOULOU, GIAOUTZI, 2017). Therefore, you meet and create a smart city. The attempt to define the city of smart city, among other things, took place: GIFFINGER et al. (2007); CALAGLIU, DEL BO, NIJKAMP (2009); LOMBARDII (2011); BATTY et al. (2012); DAMERI (2013); MANVILLE et al. (2014); GLASMEIER, CHRISTOPHERSON (2015). A Smart City is a city well performing in 6 characteristics (Smart Economy, Smart People, Smart Governance, Smart Mobility, Smart Environment, Smart Living), built on the smart combination of endowments and activities of self-decisive, independent and aware citizens (STRATIGEA et al., 2015). This 6 parameters also contains multidisciplinary issues like quality of living space. Some examples of these aspects in Smart Environment and Smart Living context could be find in (BAJOREK-ZYDROŃ, WĘŻYK, 2016). Among other things, Smart Living and precisely such features as: cultural facilities, health conditions, individual security, housing quality, education facilities, economic welfare are closely related to the development of real estate management and surveying work.
20
The surveyors are obliged to carry out these works in a reliable manner and in accordance with applicable regulations and technical standards. The geodetic land division is stage an indispensable of the investment process (NOGA et al., 2018). However, the delimitation of land consists in establishing the course of the boundaries of real estate, in a situation when they have become disputable and the legal state cannot be established. In turn, if we want to start building a house or other building object, it is necessary for the surveyor to create a situational map for design purposes. However, in accordance with the Construction Law (ACT, 1994), construction works requiring a building permit. After completion of construction, should be measured carry out field surveying inventory. Therefore, inventory is the last geodetic activity performed in the investment process. It can be stated that geodetic works are an inherent element of real estate management and the investment process in the city. Among other things, this topic was considered, among others, by: KWARTNIK-PRUC, HANUS (2014); BALAWEJDER et al. (2015); BUŚKO, PRZEWIĘŹLIKOWSKA (2016); KUKULSKA et. al. (2017); BALAWEJDER, WÓJCIAK (2017); WOLNY et al. (2017) and others, but no research was conducted in the context of Smart City. Therefore, the purpose of the article is to determine the impact of surveying works on the development of the Smart City on the example of the City of Rzeszow. Characteristics of the research object The city of Rzeszow was selected for detailed research, as Rzeszow occupies 55th place in the ranking of European Smart Cities (PLEEC project studies). It is worth noting that on the 77 cities assessed from all over Europe, the list included 6 Polish cities, including the City of Rzeszow (Fig 1).
Fig. 1. The European Smart Cities v. 3.0 project from 2014. Source: PLLEC.
The city of Rzeszow is located in the south-eastern part of Poland, on the Wisłok River. Rzeszow is the capital of the Podkarpackie Voivodeship. It is the central academic, economic and cultural center of this region. The city of Rzeszow is divided into 20 cadastral districts: Śródmieście, Nowe Miasto, Zalesie, Biała, Zwięczyca, Staroniwa, Baranówka, Staroniwa II, Przybyszówka, Staromieście, Pobitno, Wilkowyja Pn, Wilkowyja Pd, Rzeszow – Załęże, Rzeszow – Słocina, Przybyszówka II, Rzeszow – Zwięcz, Biała II, Budziwój, Miłocin, Bzianka. The layout of cadastral districts in the city is shown in Figure 2. Rzeszow covers an area of 120.4 km2. This is 9.9% of the entire county's area. It has more than 188,000 inhabitants. The average population density is 1562 people/km2. The advantage of Rzeszow is its attractive location, well-developed road network, public transport and natural values. The city undertakes various efforts to continuously improve the natural environment. Rzeszow plays an important point on the map of Europe. It has an international airport. There are also intersecting international routes of road and railway communication (NOGA et al., 2017). Rzeszow focuses on educated youth. In the city there are two large state universities, such as: the University of Rzeszow and the Rzeszow University of Technology as well as several private ones. Many enterprises and production plants prosper in the city, with around 100,000 employees. Constant development of Rzeszow and receiving the title of Smart City, forced somewhat city authorities to expand the borders of their territory by acquiring new areas. Beginning from 2006 to the present, Rzeszow joined a new cadastral district every year, thanks to which it increased its area. Over the past few years, they have been attached: 2006 – Słocina and Załęże; 2007 – part of Przybyszówka; 2008 – part of Przybyszówka and Zwięczyca;
21
2009 – Biała; 2010 – part of Miłocin and Budziwój; 2017 – Bzianka.
Fig. 2.The division of the city of Rzeszow into cadastral districts. Source: Own study.
The acquired areas and the possibility of their utilities can be evidence of further investments, and thus the creation of new jobs, as well as the development of residential construction. Among other things, residential housing has an impact on Smart Living in the city of Rzeszow, as detailed in Figure 3.
Fig. 3.Domains Smart Living in the city of Rzeszow. Source: PLLEC.
Overall, the city of Rzeszow has the 55th place in the ranking of European Cities. In the Smart Living category, on the other hand, it was 50th. As we note in Figure 3, Smart Living is influenced by: cultural facilities, health conditions, individual security, housing quality, education facilities, touristic attractiveness and economic welfare. In addition to the smart living feature, the overall ranking in
22
European cities is also influenced by 5 features: Smart Economy, Smart People, Smart Governance, Smart Mobility and Smart Environment that correlate with each other.
Fig. 4. Smart City profiles: Rzeszow, Perugia and Kielce. Source: PLLEC.
The mutual correlation of features is presented in Figure 4. We see how Smart City Rzeszow ranks as compared to another Polish Smart City Kielce or Smart City Perugia in Italy. We observe that it differs little from the average of 77 cities in Europe. Therefore, geodetic works may influence the better result of the city of Rzeszow in the next study of European Cities. Spatial planning and surveying works Spatial planning is an extremely powerful tool with which the development of even the largest space can be shaped (BIEDA, PARZYCH, 2013).There is a very large link between spatial planning and surveying work. Both of them relate to information about the site. The geodetic works are based on real information about the area (BALAWEJDER, WÓJCIAK, 2017). In turn, spatial planning determines the state of the designed site. Existing planning materials can influence the initiation of real estate processes (BIEDA et al., 2015). This is especially noticeable when the land dividing. Namely, the land division can be made when it is in accordance with the arrangements of the local plan. The local spatial development plan is an act regulating issues related to the destination, development conditions and land development as well as matters related to the deployment of a public purpose investment. Pursuant to the Act on Spatial Planning and Development (ACT, 2003), each commune should have its own spatial plan. Such a plan consists of two basic parts: the text part (resolution) and the graphic part (attachment to the resolution). A local plan is a document constituting the basis for spatial planning in each municipality. It is also the basis for issuing an administrative decision (no such study exists). In the case of a change in the use of agricultural and forest land for non-agricultural and non-forestry purposes, such changes are made in the local plan. The plan is drawn up within the administrative boundaries of municipalities and cannot go beyond it. There may be more than one plan in the municipality, but they cannot overlap. The current coverage of the city of Rzeszow, applicable and being under development with local spatial development plans, is shown in Figure 5 from the Public Information Bulletin. A local plan is an important document in the process of investment preparation.The area on which the investment project is planned, consisting in the construction of the building, must be designated for development in the local plan. In addition, the local plan contains information on: the minimum size that a plot must have, so that you can build a house, distance from the road, dimensions of the building, and even the color of the roof. Otherwise, we will not get a building permit. One of the basic materials for the needs of spatial planning are basic maps and topographic maps. Basic maps are used in the 23
development of local plans, and topographic maps in the study of conditions. The information contained in the basic maps, in particular construction objects with the indication of their use, property boundaries, land development elements, land use designation, underground and aboveground technical infrastructure allow for a thorough analysis of the existing development status (BALAWEJDER et al., 2016).
Fig. 5.Areas of the city of Rzeszow covered and being in the development of the local land development plan. Source: bip.erzeszow.pl/ (access 12.05.2018).
The table 1 below presents the number of local plans adopted from 2011 to the present and the number of plans developed. Table1. The number of approved and planned local land development plans for the city of Rzeszow. Year
Local spatial development plans in preparation
Approved local spatial development plans
quantity
%
quantity
%
2011
10
30.3
9
17.6
2012
8
24.2
7
13.7
2013
9
27.3
6
11.8
2014
1
3.0
3
5.9
2015
3
9.1
13
25.5
2016
2
6.1
11
21.6
2017
0
0.0
2
3.9
Total
33
100.0
51
100.0
Source: Own study.
Based on Table 1 and Figure 6, we see that in the years from 2011 to 2017, as many as 51 local spatial development plans were approved at the site. However, in the examined facility still 33 local
24
spatial development plans are under development. Therefore, in a situation where in the area where the investment is planned there is no valid development plan or the permit has not been adopted there, we will obtain a building permit by way of a decision on land development and development conditions. The investment will then be implemented based on this decision. Pursuant to the Act on spatial planning and development (ACT, 2003), we distinguish two types of decisions on building and land development conditions. One of them is the decision to locate a public goal. The second of them is the decision on building conditions for other investments. These decisions are issued by the municipality's executive body. 1000 800
942
600
777
733
733
709
2012
2013
2014
2015
400 200 0 2011
Fig. 6.Number of decisions on development conditions issued in 2011-2015. Source: Own study.
On the basis of information obtained from the Faculty of Architecture of the city of Rzeszow, the number of issued decisions on land development and development conditions in the years 2011 -2015 is in total 3894. Figure 6 shows the number of decisions on building conditions in particular years. It is easy to see that they have a downward trend. Most decisions on building conditions were issued in 2011 for the areas of Budziwój and Przybyszówka II. They are the largest in terms of surface area. It can be concluded that the reason for this is probably the dynamic development of these areas. These areas have the largest number of areas previously undeveloped, which draws the attention of Smart City investors. Analysis and the influence of geodetic works on the development of the city Surveyor plays a very important role in building processes. He draws up the geodetic documentation necessary for the development of the construction project. The first geodetic stage in the construction process is the development of a map for design purposes, and the last inventory measurement. The determination of the impact of surveying works on the development of the city of Rzeszow was made on the basis of data provided by the Center for Geodetic and Cartographic Documentation in Rzeszow. In Rzeszow, a large number of works related to the preparation of maps for design purposes and as-built inventory are performed. The analysis covered geodetic works from 2011 to 2015. During this period 5 373 maps for design purposes and 11 087 inventory field surveying were implemented. It can therefore be concluded that interest in this kind of work is high. The Figure 7 below presents the overall number of maps made for design purposes and inventory field surveying for each year. 3000
2739
2654
2790
2500 2000
1416 1359
981
1000 500
1474 1545
1289
1500
Map for design purposes Inventory field surveying
213
0 2011
2012
2013
2014
2015
Fig. 7.Number of maps for design purposes and inventory field surveying made in 2011-2015. Source: Own study.
The most maps for project purposes as many as 1474 were made in 2014, which gives 27.4% of all works carried out in 2011-2015. A little less 1416 fell in 2015, which gives 26.4% of all works.
25
However, they were the least in 2011 because only 4% (213) in relation to the whole. It can be noticed that year by year the number of developed maps for project purposes is increasing. This is probably due to the continuous development of Rzeszow Smart City. In addition, by conducting detailed research, Figure 8 was presented showing the intensity of maps for design purposes, broken down into Rzeszow Smart City. 207 Śródmieście 208 Nowe Miasto 209 Zalesie 210 Biała 211 Zwięczyca 212 Staroniwa 213 Baranówka 214 Staroniwa II 215 Przybyszówka 216 Staromieście 217 Pobitno 218 Wilkowyja Pł. 219 Wilkowyja Płd. 220 Rzeszów Załęże 221 Rzeszów Słocina 222 Przybyszówka II 223 Rzeszów Zwięcz 224 Biała II 225 Budziwój 226 Miłocin
150
100
50
0 2011
2012
2013
2014
2015
Fig. 8. Number of maps for design purposes carried out in individual districts of Rzeszow in 2011-2015. Source: Own study.
As shown in Figure 8, maps for design purposes have been made in all cadastral districts. The most maps were made in the outer areas of Rzeszow Smart City. The most maps were made in 2014. In order to better illustrate, a cartogram was prepared (Figure 9) showing the intensity of maps for design purposes with the cadastral district in 2014.
Fig. 9.Strength of maps for design purposes in 2014 in particular districts. Source: Own study.
26
As can be seen from figure 9, the most maps for project purposes were performed in district 222 and 225. The least in 226 and 217. In 207-Śródmieście, a moderate number of maps for design purposes was performed, which indicates the development of the investment towards Smart City development. In the case of inventory field surveying, a downward trend can be observed. As shown in Figure 7, in the first three years, the number of such works has remained almost at the same level. However, in 2014 and 2015 there was a decrease. Additionally, while conducting detailed research, Figure 10 was presented showing inventory field surveying intensity divided into a district in the city of Rzeszow Smart City. 350 300 250 200 150 100 50
0 2011
2012
2013
2014
2015
207 Śródmieście 208 Nowe Miasto 209 Zalesie 210 Biała 211 Zwięczyca 212 Staroniwa 213 Baranówka 214 Staroniwa II 215 Przybyszówka 216 Staromieście 217 Pobitno 218 Wilkowyja Pł. 219 Wilkowyja Płd. 220 Rzeszów Załęże 221 Rzeszów Słocina 222 Przybyszówka II 223 Rzeszów Zwięcz 224 Biała II 225 Budziwój 226 Miłocin
Fig. 10. Number of inventory field surveying carried out in individual districts of Rzeszow in 2011-2015. Source: Own study.
As shown in Figure 10, inventory fielding was performed in all districts. The most inventory was made in external Rzeszow Smart City. The most inventory was made in 2012. For better illustration, Figure 11 was presented showing the cartogram of the inventory field surveying volume divided in districts in 2012.
Fig. 11. Strength of inventory field surveying in 2012 in particular districts. Source: Own study.
27
As shown in Figure 11, most inventory field surveying was also performed in districts 222 and 225. The least in the areas of 226 and 217. In 207-Śródmieście, a moderate inventory field surveying was performed, which indicates the development of investments towards Smart City. As far as real estate management is concerned, it has a very large impact on shaping space in accordance with the arrangements contained in the local land development plan and in the decisions of WZZT (KWARTNIK-PRUC, HANUS, 2014). Among the tasks of the real estate management, the divisions of land can be mentioned as the most frequently executed ones. However, much less land delimitations are carried out. In the analyzed period, a total of 2,662 divisions and only 142 delimitations of land were recorded. Below is a figure 12, which presents the total number of land divisions made and land delimitation for each year. Due to the very small number of delimitations made, they were not subjected to detailed analysis, while the numerous divisions of land were elaborated in detail. 1200 983
1000 800 512
600
Land division
456
446
Land delimination
400
265
200
39
37
30
21
15
0 2011
2012
2013
2014
2015
Fig. 12. Number of divisions and delimitation of land completed in 2011-2015. Source: Own study.
As shown in Figure 12, the most divisions up to 983 were made in 2015, which gives 36.9% of the total work done in 2011-2015. A lot less only 512 fell in 2011, 456 in turn in 2013, and 446 in 2012. However, the least was in 2014, because only 265 divisions of land in relation to the whole. It can be noticed that year by year the number of developed divisions of design real estate decreased, and in 2015 it increased three times. This is probably due to the arrival of the city of Rzeszow on the Smart City list. It may be caused by the investment development of the city, the planning of numerous smart construction projects, as well as the development of road infrastructure. Additionally, while conducting detailed research, Figure 13 was presented showing the intensity of property divisions divided into cadastral districts in Rzeszow Smart City. 140
207 Śródmieście 208 Nowe Miasto
120
209 Zalesie 100
210 Biała 211 Zwięczyca
80
212 Staroniwa 213 Baranówka
60
214 Staroniwa II 215 Przybyszówka
40
216 Staromieście 217 Pobitno
20
218 Wilkowyja Pł. 0 2011
2012
2013
2014
2015
219 Wilkowyja Płd.
Fig. 13. Number of property divisions carried out in individual cadastral districts of the city of Rzeszow in 2011-2015. Source: Own study.
28
As shown in Figure 13, property divisions have been made in all districts. The most divisions of land were made in external Rzeszow Smart City. The most divisions of land were made in 2015. For the purpose of better illustration, an additional illustration was prepared, showing the intensity of property divisions divided into districts in 2015.
Fig. 14. Strength of land division in 2012 in particular districts. Source: Own study.
As can be seen from figure 14, the most divisions of land were also made in districts 222 and 225. The smallest in districts 213, 214, 216 and 217. The 207-Śródmieście, a moderate number of property divisions was performed, which indicates the development of investments towards Smart City development. In the last stage of the analysis, as a summary, a tabular summary (tab.2) was prepared, in which the number of discussed types of works for each year was placed. A figure 15 was also drawn up showing the distribution of the number of individual works in the examined period. Table 2. A summary of the total number of surveying works carried out in individual years. Year 2011
Year 2012
Year 2013
Year 2014
Year 2015
Total
Quantity
%
Quantity
%
Quantity
%
Quantity
%
Quantity
%
Quantity
%
512
11,5
446
1,9
456
2,0
265
1,1
983
4,2
2662
11,5
2.Land delimination
37
0,2
39
0,2
21
0,1
30
0,1
15
0,1
142
0,6
3.Map for design purposes
213
0,9
981
4,2
1289
5,6
1474
6,4
1416
6,1
5373
23,2
4.Inventory field surveying
2739
11,8
2790
12,0
2654
11,5
1545
6,7
1359
5,9
11087
47,9
5.Decisions of the WZZT
942
4,1
777
3,4
733
3,2
733
3,2
709
3,1
3894
16,8
Total
4443
19,2
5033
21,7
5153
22,3
4047
17,5
4482
19,4
23158
100,0
1.Land division
Source: Own study.
Among the analyzed works, the most inventory field surveying were carried out, as much as 47.9% of all works carried out in the analyzed period. The rare occurrence of the works are the delimitation of only 0.6% of the total geodetic tasks performed. As regards the decisions of the WZZT, their number since 2012 has remained more or less at the same level (16.8%). It is also easy to notice that the number of inventories has dropped significantly. This is due to the fact that probably the number of planned investments was completed in 2015. The European Smart Cities v. 3.0 project from 2014 showed that Rzeszow was placed on the list of Smart Cities. This caused a sudden interest in land in Rzeszow Smart City. Investors started the investment process due to the number of property divisions in 2015
29
increased. In summary, the development of real estate management and surveying work have a significant impact on the development of Smart Cities, including Smart Living. 3000 2500 2000
1 2 3 4 5
1500 1000 500
Podziały Rozgraniczenia Mapy do celów projektowych Pomiary inwentaryzacyjne Decyzje WZZT
0 2011
2012
2013
2014
2015
Fig. 15. The total number of surveying works carried out in individual years. Source: Own study.
Conclusions This article specifies the impact of geodetic works on the development of the Smart City on the example of Rzeszow. Rzeszow ranks 55th in the ranking of European Smart Cities (PLEEC project studies). The ranking includes 6 Polish cities, including the city of Rzeszow. 1. Detailed research was conducted on 20 city districts of the City of Rzeszow. Such a large area covered by the analysis allowed for a precise interpretation of the phenomenon. The data was obtained from the Center for Geodetic and Cartographic Documentation in Rzeszow. The article focuses primarily on surveying works related to real estate management and construction processes that have an impact on the development of Smart City. The analysis covered geodetic works in the field of: land divisions, land delimitations, maps for design purposes and inventory field surveying. This kind of work is very often carried out while executing most investments. 2. Overall, the City of Rzeszow has the 55th place in the ranking of European Cities. In the Smart Living category, on the other hand, it was 50th. The following factors influence Smart Living: cultural facilities, health conditions, individual security, housing quality, education facilities, touristic attractiveness, and economic welfare.In addition to the smart living feature, the overall ranking in European Cities is also influenced by 5 features: Smart Economy, Smart People, Smart Governance, Smart Mobility and Smart Environment that correlate with each other. The article shows the mutual correlation of features against the background of another Polish Smart City Kielce or Smart City Perugia in Italy. We observe that it differs little from the average of 77 cities in Europe. Therefore, geodetic works may influence the better result of the City of Rzeszow in the next study of European Cities. 3. Among the analyzed works, the most inventory measurements were carried out, as much as 47.9% of all works carried out in the analyzed period. As regards the decisions of the WZZT, their number since 2012 has remained more or less at the same level (16.8%). It is also easy to notice that the number of inventories has dropped significantly. This is due to the fact that probably the number of planned investments was completed in 2015. The European Smart Cities v. 3.0 project from 2014 showed that Rzeszow was placed on the list of Smart Cities. This caused a sudden interest in land in Rzeszow Smart City. Investors started the investment process due to the number of property divisions in 2015 increased. In summary, the development of real estate management and surveying work have a significant impact on the development of Smart Cities, including Smart Living. Summing up, based on the data provided, it was found that the most works were carried out related to building processes. This only proves that Rzeszow Smart City is constantly growing. It is constantly attracting new investors, and thus new investments are being made all the time, which has an impact on the development of the Smart City.
30
References BAJOREK-ZYDROŃ, K., WĘŻYK, P., (red.) 2016. Atlas pokrycia terenu i przewietrzania Krakowa (Atlas of land cover and ventilation in Krakow), Kraków, p. 56-57. BALAWEJDER, M., ADAMCZYK, T., CYGAN, M. 2016. The problem of adjusting Polish Spatial Information Resource to the standards of the INSPIRE. Geographic Information Systems Conference and Exhibition - GIS ODYSSEY 2016, Conference proceedings, Perugia, Italy, p. 14-24. BALAWEJDER, M., BUŚKO, M., CELLMER, R., JUCHNIEWICZ-PIOTROWSKA, K., LEŃ, P., MIKA, M., SZCZEPANKOWSKA, K., WÓJCIAK, E., WÓJCIK-LEŃ, J., ŹRÓBEK, S. 2015. Aktualne problemy gospodarki nieruchomościami w Polsce na tle przemian organizacyjno-prawnych (Current problems of real estate management in Poland against the background of changes of organizational and legal). WSI-E, Rzeszów, p. 144. BALAWEJDER, M., WÓJCIAK, E. 2017. Application of GIS tools in analysing a road network providing access to cadastral parcels in the project concerning land consolidation and exchange. Geographic Information Systems Conference and Exhibition “GIS ODYSSEY 2017”, 4th to 8th of September 2017, Trento–Vattaro, Italy, Conference proceedings, p. 13-21. BATTY, M., AXHAUSEN, K., FOSCA, G., POZDNOUKJV, A., BAZZANI, A., WACHOWICZ, M., OUZOUNIS, G., PORTUGALI, Y. 2012. Smart cities of the future (Paper No. 188). London, United Kingdom: University College London (UCL), Centre for Advanced Spatial Analysis (CASA). BIEDA, A., ADAMCZYK, T., BIEDA, A. 2016. The energy performance of buildings directive as one of the solutions for smart cities. Geographic Information Systems Conference and Exhibition “GIS ODYSSEY 2016”, Conference proceedings, Perugia, Italy, p. 44-49. BIEDA, A., GLANOWSKA, M., HANUS, P., PĘSKA, A. 2015. Rozgraniczenie jako proces wspomagający procedury gospodarki nieruchomościami oraz planowania przestrzennego (Delimination as a process supporting real estate management procedures and spatial planning). Infrastruktura i Ekologia Terenów Wiejskich, IV(1):1068-1080. BIEDA, A., PARZYCH, P. 2013. Development of spatial politics of monumental towns based on Krakow example. International Multidisciplinary Scientific GeoConference: SGEM: Surveying Geology & mining Ecology Management, 2, p. 143. BUSKO, M., PRZEWIĘZLIKOWSKA, A. 2016. The problem of demonstrating cadastral changes in surveying documentation. 5th–9th September 2016, Perugia, Italy : conference proceedings. Zagreb: Croatian Information Technology Society, GIS Forum, p. 50–62. CARAGLIU, A., DEL BO, C., NIJKAMP, P. 2009. Smart cities in Europe (Series Research Memoranda 0048). Amsterdam, Netherlands: VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics. DAMERI, R. P. 2013. Searching for smart city definition: A comprehensive proposal. International Journal of Computers & Technology, 11(5): 2544–2552. GIFFINGER, R., FERTNER, C., KRAMAR, H., KALASEK, R., PICHLER-MILANOVIC, N., MEIJERS, E. 2007. Smart cities – Ranking of European medium-sized cities(Final report): Vienna University of Technology, Vienna, Austria. GLASMEIER, A., CHRISTOPHERSON, S. 2015. Thinking about smart cities. Cambridge Journal of Regions. Economy and Society, 8(1): 3–12. KUKULSKA, A., CEGIELSKA, K., SALATA, T., SZYLAR, M. 2017. Wpływ ośrodka miejskiego na kształtowanie się obszarów inwestycyjnych (The influence of the urban center on the development of investment areas). Acta Sci. Pol. Administratio Locorum, 16(2): 97–110. KWARTNIK-PRUC A., HANUS P. 2014.Geodezyjne aspekty rozgraniczeń i podziałów nieruchomości (Geodetic aspects of real estate demarcation and divisions). Wydawnictwa AGH, Kraków pp.137. LOMBARDI, P. 2011. New challenges in the evaluation of smart cities. Network Industries Quarterly, 13(3): 8– 10. MANVILLE, C., COCHRANE, G., CAVE, J., MILLARD, J., PEDERSON, J. K., THAARUP, R. K., LIEBE, A., WISSNER, M., MASSINK, R., & KOTTERINK, B. 2014. Mapping smart cities in the EU (Study – Document requested by the European Parliament’s Committee on Industry, Research and Energy). Brussels, Belgium: Directorate General for Internal Policies, Policy Department A: Economic and Scientific Policy. NOGA, K., BALAWEJDER, M., NOSEK, G., 2018. Ways of Acquiring Land Property for the Construction of Province Roads. Real Estate Management and Valuation, 26(1): 108-121. NOGA, K., BALAWEJDER, M., MATKOWSKA, K. 2017. Dimensions of the destruction of road network providing access to cadastral parcels resulting from the motorway construction. Geomatics and Environmental Engineering, 11(4): 65-81. PAPADOPOULOU, CH.-A., GIAOUTZI, M. 2017. Crowdsourcing and Living Labs in Support of Smart Cities’ Development. International Journal of E-Planning Research, 6(2): 22-38.
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PLLEC–Ranking of European cities (Final report): Vienna University of Technology, Vienna, Austria. www.smart-cities.eu. STRATIGEA, A., PAPADOPOULOU, CH.-A., &PANAGIOTOPOULOU, M. 2015. Tools and Technologies for Planning the Development of Smart Cities. Journal of Urban Technology. THE ACT of 7 July 1994 Construction law (Official Jurnal 2018 No. 1202- consolidated text, as amended). THE ACT of 23 March 2003 on planning and spatial development (Official Jurnal 2017 No. 1073consolidated text, as amended). WOLNY, A., DAWIDOWICZ, A. ŹRÓBEK, R., 2017. Identification of the spatial causes of urban sprawl with the use of land information systems and GIS tools. In: Rogatka, K. and Szymańska, D. (eds.) Bulletin of Geography. Socio-economic Series, 35, Toruń, Nicolaus Copernicus University, p. 111–122.
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ROBUST ESTIMATION FOR DETECTION OF FLATNESS DEFECTS Marek Banaś, Ph.D.
Institute of Technical Engineering The Integrated Geodesy Unit The Bronisław Markiewicz State Higher School of Technology and Economics in Jarosław Jarosław, Poland e-mail:
[email protected] – contact person
Sorin Nistor, Ph.D.
Faculty of Civil Engineering and Architecture Department Cadastre-Architecture University of Oradea Oradea, Romania e-mail: sonistor@ uoradea.ro Abstract Shape verification is a common task in engineering, geodetic practice and rely on fitting the theoretical model describing the object in its actual shape. The theoretical model (e.g. plane) is defined in the design documentation, while the actual shape of the object is determined by points that are defined as a result of geodetic measurements. The shape verification is determined at the moment when the measurement was performed. The paper concerns the use of robust estimation methods to the study of flatness of the object measured by geodetic methods. Conducted studies involving the simulation of displacements (imperfections) of a known size and their detection by fitting a plane surface model using the weighted least squares method and robust estimation methods. The conducted research indicates the predominance of robust estimation methods to the classic method of least squares in the matter of resistance to incidental values of deviations from the plane surface that may have a source both in the actual imperfection and in the errors of the measurement nature. Key words: robust estimation methods, modelling, least squares method, deformation Introduction A common task in geodetic practice is to control the geometry of an engineering object. Levelness, verticality or flatness of structural elements are checked (WYCZAŁEK et al., 2015; RINALDO et al., 2016). Measurements and their analysis are carried out both during construction and subsequent operation stages. As a result of geodetic measurements we get a set of points representing the shape of a given object. Level control is carried out for objects such as ceilings, floors, foundation slabs, as well as bridge and viaduct slabs. In some cases, there is a need for regulatory or repair work. Classical methods used in surface approximation of such an object are often sensitive to outliers or gross errors in the sets of points representing the shape. In order to minimize costs, labour consumption and working time, to better fit the object model, it would be advisable to use methods minimizing the impact of outliers on the final parameters of the estimated model. The verticality control is performed for such objects as walls and elevations of buildings, elevator shafts, pillars' surfaces, bridge abutment. Prefabricated elements of the facade of large commercial and service buildings became popular in recent years. Their correct assembly requires verticality control of the walls on which they are installed. In the case of elevator shafts, verticality measurements usually concern the calculation of wall position deviations (with door openings) from the vertical position with reference to the wall on the lowest storey (MUSZYŃSKI, 2007; MUSZYŃSKI, 2008). Failure to keep the vertical position of structural elements of buildings and structures affects their proper operation and safety. Also in the case of this type of work, it would be optimal to apply calculation methods that minimize residuals of the model obtained at individual points representing the object from the theoretical plane. The measurement of the points’ grid on the celling of settling building can be used to fit into the set of points of the best fitted plane and thus determine the building's inclination. Local shape anomalies may disturb the results of the object's inclination and it would be desirable to use the method suppressing the local geometrical imperfections reflected in the measurement results.
33
The classic least squares method used to minimize the sum of weighted deviations may turn out to be less effective than the robust estimation methods. Significant local deformations of the measured surface may cause false orientation of reference plane as well as raised values of residuals. The paper attempts to test the appropriateness of using robust estimation methods in plane approximation. The wall of the building was measured and its shape was approximated. Obtained results were referenced to the classic method of least squares. Robust estimation methods used in research Huber Method The Huber method was developed by Professor P. J. Huber (HUBER, 1964). In order to derive a robust M-estimator, he applied a probability density function consisting of two different functions. The centre of the set is ruled by normal distribution, while moving away from the centre it goes into Laplace, i.e. a particular form of exponential distribution. The weight function can be represented in the form (GÖTZELMAN et al., 2006):
1 w (e) = k e
for
e k
for
e k
()
In literature, we find many suggestions for choosing k parameter. Huber reports that its value adjusts the magnitude of robustness and states that a good choice is between 1 and 2. The control parameter k, which is responsible for determining the limits of the acceptable range for corrections, can be set, among others empirically. In this work, the parameter value for this method has been selected to achieve 95 % efficiency of the estimator with reference to standard normal distribution. Hampel Method The function responsible for modifying weights in the Hampel method is more extensive than in the Huber method and is presented as follows (HAMPEL, 1974; HOAGLIN et al., 1983):
1 a e w (e) = a (c − e ) ( c − b) e 0
for
e a
for
a e b ()
for
b e c
for
e c
The parameters a, b, c that appear in the form of functions define the limits of intervals in which the value of the correction may be found. In the literature, one can find the definitions that the Hampel function is an extension of the Huber function with two additional intervals introduced, i.e. to the left and right of the range acceptable for corrections in the Huber function (MUSZYŃSKI, 2007). In the literature, many suggestions for selecting control parameters can be found. In the paper (HOGG, 1979) we find that the reasonable choice is a = 1.7, b = 3.4, c = 8.5. These parameters have been accepted for calculations in this study. They provide 95% efficiency of the estimator with reference to standard normal distribution. Danish Method The sensitivity of the least-squares method to gross errors was reflected in the work of the Danish Geodetic Institute. The Danish method was introduced by T. Krarup, an outstanding Danish surveyor. He proposed it in 1967 and was used since then in the automatic search for outliers in the observation sets. The weighting function in this method is (KRARUP, 1980; WIŚNIEWSKI, 2009):
1 w ( e ) = − l( e −k )g e
for
e −k;k
for
e k
34
()
Parameters l and g should be chosen experimentally. Usually the value of l is chosen from the range from 0.01 to 0.1, while g = 2. Linear Method The method was proposed by Professor E. Osada in 2002 (OSADA, 2002). The idea of the linear method differs significantly from the other methods presented in this work. Assigning new weights to observations is based on the analysis of the values of corrections for observations after each iteration of alignment. The average errors of observations, used to construct weights, are subject to modification. The average error of a given observation is increased iteratively by the value of the excess of the standard deviation from the set of corrections. The first step of the iterative calculation process is weighting least squares. The method of weight modification is presented in the expression (MUSZYŃSKI, 2008; BANAŚ, 2017):
mi mi( j+1) = ( j) mi + vi
for
vi( j ) ki( j ) m
for
vi( j ) ki( j ) mi
(4)
In the above formula ki( j ) = ( j ) / mi and i is the number of observations. Geodetic inspection of wall flatness The object to control was the wall in room W-21 in the Department of Integrated Geodesy, located on the campus of the State Higher School of Technology and Economics in Jarosław. The room in which the measurements were taken serves as a lecture hall for students and PWSTE employees. The wall was selected in such a way that a regular grid of squares could be displayed on it with the help of a multimedia projector. Geometry of measured net of points and technique of surveying In order to obtain the surplus observations necessary to control and obtain the assumed accuracy, it was decided to measure from two measurement stations. They were located at a distance of about 1m from the wall opposite the wall covered by the measurement (Fig. 1). The distance of the measuring stations from each other was 4.198m. This value was determined during the measurements. On the right side of the examined object there was a position marked as ST.1, while on its left a ST.2 station. Control points for locating stations were marked on the floor with a small cross made of permanent ink. To set the measuring equipment (total station, reflector) above the marked points, wooden tripods where used which ensured stability of the station. Before the measurement, the instrument and reflector were levelled and centred over the point. Surveying activities were performed with using Leica TS02 total station and Leica GRZ4 360 prism. From two stations in a room, angles and distances where measured to each of 112 points marked on the wall (Fig. 2). In the first, original survey, the points reflecting the actual shape of the wall were measured, i.e without intentionally simulated displacements. Empirical tests of robust estimation methods Preparing contaminated set of coordinates for numerical tests The wooden blocks of rectangular shape were used to disturb the actual shape of the measured wall. Their task was to simulate displacements of chosen points. Blocks were covered with white selfadhesive paper. Small crosses where marked on them to allow precise aiming. These blocks have been carefully measured using a calliper to get to know their actual size, and hence the size of the marked imperfections. Then, before making the measurement, they were glued to the wall with a strong doublesided tape (Fig. 3). As displaced points, 9 nodes were adopted with the following numbers: 44, 45, 46, 67, 68, 69, 72, 73, 74. The dimensions of the blocks measured with the calliper are summarized in Table 1. The right-hand side of Fig. 3 presents a disturbed wall model with deformation of exactly known size.
35
Fig. 1. Localization of control points during measurements. Source: Own study.
Fig. 2. Grid with marked points on which displacements were simulated (inside a red rectangle). Source: Own study.
Fig. 3. Wooden blocks simulating displacements (left) and deformation model (right). Source: Own study.
36
Table1. Values of simulated displacements. Point number
Simulated displacement [mm]
44
29
45
33,8
46
22,5
67
17
68
37,5
69
32,3
72
33,5
73
23,2
74
23,4
Source: Own study.
Robust estimation The initial, i.e. original set of observations and contaminated set was adjusted using classical least squares adjustment and robust estimation methods. Simple method to obtain robust estimates is to use IRLS, i.e. Iteratively Reweighted Least Squares Method (BANAŚ, LIGAS, 2014). The MATLAB software was used to implement IRLS algorithm and individual weighting function of Huber, Hampel, danish and linear method. We can notice that when we apply robust estimation to intentionally contaminated datasets we get more reliable results than from least squares estimation (Tab. 3). The reference to show how Mestimators reduce influence of outliers in contaminated datasets were coordinates obtained from least squares adjustment applied to datasets without contamination. We can notice that classical least squares adjustment is not robust to outliers in dataset.
Fig. 4. Contour map of points’ deviations from original surface estimated with using least squares method (without simulated outliers). Source: Own study.
Conclusions The study presents effect of numerical tests of performance of four robust estimation methods applied to find parameters of flat surface (approximation). Paper presents obtained values of displacements which were intentionally introduced. To estimate them there was used least squares method and 4 robust estimation methods. The paper shows the advantage of robust estimation methods to reduce the influence of outliers on plain surface parameters over the ordinary least squares adjustment. Robust estimation methods allow to estimate parameters of the surface from a set with outliers which are far more close to the parameters estimated with using the original coordinates from measurement of the wall (without contamination). Residuals of the model obtained in points which are free of outliers are smaller than in case of using ordinary least square adjustment for wall with simulated displacements. The model of surface is „closer” to points which are free of blunders than in case of using least square adjustment. Obtained values of simulated displacements as a result of robust estimation are very close to their real values. Each robust method gave very similar results. At the same time, these are results that deviate from
37
those obtained from the least square method (Tab. 3). As the main conclusion, it should be stated that application of robust estimation methods allow to obtain real, local imperfections without spreading big local imperfections to the neighbouring points of the wall.
Fig. 5. Contour map of points’ deviations (Huber method). Source: Own study. Table2. Values of simulated displacements. Point number
Values of simulated displacements from calliper [mm]
Original wall imperfections [mm]
Values of simulated displacements reduced by original wall imperfections [mm]
44
29,0
-1,9
27,1
45
33,8
-0,7
33,2
46
22,5
0,3
22,8
67
17,0
-1,8
15,2
68
37,5
-1,5
36,0
69
32,3
-2,9
29,4
72
33,5
0,0
33,5
73
23,2
0,7
23,9
74
23,4
0,1
23,5
Source: Own study. Table3. Values of estimated displacements in simulated points. Point number
Huber method [mm]
Hampel method [mm]
Danish method [mm]
Linear method [mm]
Least Squares [mm]
Values of simulated displacements reduced by original wall imperfections [mm]
44
27,0
26,9
27,0
26,8
21,4
27,1
45
32,9
32,8
32,9
32,7
27,9
33,2
46
22,7
22,7
22,8
22,6
18,4
22,8
67
15,6
15,6
15,7
15,5
11,1
15,2
68
35,9
35,8
35,9
35,7
30,7
36,0
69
30,4
30,3
30,4
30,2
24,5
29,4
72
33,5
33,5
33,6
33,4
27,6
33,5
73
24,1
24,0
24,1
23,9
18,7
23,9
74
24,1
24,1
24,1
24,0
19,4
23,5
Source: Own study.
38
References BANAŚ, M. 2012. A review of robust estimation methods applied in surveying. Geomatics and Environmental Engineering, 6(4): 13-22. BANAŚ, M., LIGAS, M. 2014. Empirical tests of performance of some M – estimators. Geodesy and Cartography, 63(2): 127–146. BANAŚ, M. 2017. Application of Robust Estimation Methods to Displacements Determination of Geodetic Control Network of Dam. 2017 Baltic Geodetic Congress (BGC Geomatics), Gdansk, 2017, p. 89-94. GÖTZELMAN, M., KELLER, W., REUBELT, T. 2006. Gross Error Compensation for Gravity Field Analysis Based on Kinematic Orbit Data. Journal of Geodesy, 80(4): 184-198. HUBER, P. J. 1964. Robust Estimation of a Location Parameter. The Annals of Mathematical Statistics, 35(1): 73-101. HAMPEL, F. 1974. The Influence Curve and Its Role in Robust Estimation. Journal of American Statistical Association, 69(346): 383-393. HOAGLIN, D. C., MOSTELLER, F., TUKEY, J. W. 1983. Understanding robust and exploratory data analysis. New York: Wiley. HOGG, R. V. 1979. Statistical Robustness: One View of its use in Applications Today. The American Statistician, 33(3): 108-111. KRARUP, T., JUHL, J., KUBIK, K. 1980. Gotterdammerung over least squares adjustment. Proceedings of 14the Congress of the ISPRS, B3, p. 369-378. MUSZYŃSKI, Z. 2008. Zastosowanie metod estymacji odpornej do geodezyjnego opisu deformacji obiektu budowlanego. Acta Scientiarum Polonorum – Geodesia et Descriptio Terrarum, 7(4): 3–14 (in Polish). MUSZYŃSKI, Z. 2007. Zastosowanie metod estymacji odpornej do identyfikacji obiektów budowlanych na podstawie pomiarów geodezyjnych. Rozprawa doktorska, Politechnika Wrocławska. RINALDO, P., MARENDIĆ, A., GRGAC, I., JAKOPEC, I. 2016. Determination of the Concrete Slab Flatness Using the Linear Regression Modelling. TS 3 – Engineering Geodesy for Construction Works, Industry and Research, SIG 2016 – International Symposium on Engineering Geodesy, 20–22 May 2016, Varaždin, Croatia, /http://www.geof.unizg.hr/pluginfile.php/7437/mod_book/chapter/173/ TS3_3.pdf (access 10.08.2018). WIŚNIEWSKI, Z. 2009. Rachunek wyrównawczy w geodezji. Olsztyn: Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego (in Polish). WYCZAŁEK, I., JAMROŻY, P., WYCZAŁEK, M. 2015. Application of geodetic methods for measuring flatness and fall of surfaces. Archiwum Instytutu Inżynierii Lądowej, 20: 77-92.
39
ATTRIBUTE ‘MEAN ERROR OF THE BOUNDARY POINT POSITION’ IN THE ASPECT OF ACCURACY ASSESSMENT OF PARCEL SURFACE AREA Piotr Benduch, M.Sc. AGH University of Science and Technology Department of Geomatics Krakow, Poland e-mail:
[email protected]
Agnieszka Pęska-Siwik, Ph.D. AGH University of Science and Technology Department of Geomatics Krakow, Poland e-mail:
[email protected] Abstract Standardized values of boundary points’ attributes add up to useful element in the scope of land properties features description. Assumedly, these attributes should, inter alia, make an accuracy assessment of parcel’s surface area analytical determination possible. One of the boundary point attributes is mean error of the boundary point position in reference to the first-order geodetic control (the Polish acronym: BPP). This attribute has six possible values, complying with specific intervals of boundary point position accuracy. Taking into account, that according to the polish legal regulations concerning real estate cadastre, the surface area of parcel may be determined on the basis of boundary points coordinates included in numerical description of boundaries, the primary factor affecting the accuracy of analytical determination of parcel’s surface area is the mean error of the boundary point position. The capabilities of standardized values for boundary point attributes used for parcel’s surface area accuracy assessment were analyzed in the article. The constraints of such an approach were outlined in this work as well. Analyses were concurred by empirical examples. Finally, basing on the results of control surveying activities, the BPP attribute usefulness assessment for parcel’s surface area mean error estimation was carried out. Keywords: real estate cadastre, cadastral parcel, boundary, boundary point, surface area, evaluation Introduction The Register of land and buildings, referred to as the real estate cadastre, is a collection of data on parcels, buildings and premises. Under the provisions of the Geodetic and Cartographic Law (Act 1989), this data is used e.g. for the purposes of tax and consideration assessment, spatial and economic planning, or real property denotation in land and mortgage registers, which are a record of the legal status of real estate. The cadastral parcel is considered to be the leading object of the cadastre (HANUS et al., 2013). Its boundaries, defining the extent of property rights, are the most important of the spatial attributes of the parcel. The surface area of the parcel, which is a metric measure defining the size of a specific object, is a derivative of its boundaries. Due to its extensive use, data on the surface areas of the parcels should be of adequate accuracy and reliability (BENDUCH, 2017). The data on the surface areas of the parcels have been obtained by various methods. Initially, the results of the surveys, carried out on the existing cartographic materials, formed the basis for the data capture (FROLOV, MALING, 1969). The two approaches which could be distinguished here are the graphical and mechanical methods. The surface areas which had been captured in this way, were burdened with errors resulting from the application of the then surveying techniques, delineation of boundary lines on the map, as well as from the deteriorating quality of the cartographic materials (HANUS, 2006). For this reason, the analytical method for determining surface areas of parcels is currently the most popular one (SHIH, 1995; PĘDZICH, KUŹMA, 2012). This method is based on the coordinates of turn points of parcel boundaries in accordance with the algorithms proposed by Carl Friedrich Gauss. So far, numerous research studies have been performed regarding the broadly defined accuracy and reliability of surface areas of parcels, and they have been described in literature (GHILANI, 2000; HEJMANOWSKA et al., 2005; DESKA, 2006; ALKAN, SOLAK, 2010; DOSKOCZ, 2011; KWINTA, 2012; DOSKOCZ, 2014; HANUS et al., 2014; BENDUCH, 2016a; MIKA, LEŃ, 2016; BAJTALA et al., 2017; BERK, FERLAN, 2018). A number of publications on the use of remote sensing and photogrammetry for the purpose of determining surface 40
areas of parcels have been reported (PLUTO-KOSSAKOWSKA et al., 2007; PLUTO-KOSSAKOWSKA et al., 2008; NOWAK DA COSTA, WALCZYNSKA, 2010; OLOFSSON et al., 2014; ZHAO, PEI, 2016). The Authors analyzed the way in which the mean errors of the surface areas of the parcels propagate to the final result of valuation of land properties (BENDUCH, 2016b). The influence of changes in surface areas of parcels on land taxation was also assessed. These changes resulted from the need to adapt the cadastral data to the applicable technical requirements (BENDUCH, PĘSKA, 2016). The mean errors of boundary points (PREWEDA, JASIŃSKA, 2014; BENDUCH, PĘSKA-SIWIK, 2017) as well as the accuracy of boundary lines of parcels (HANUS, 2013) were analyzed as key factors for the correct determination of their surface areas (OGECHI, ODERA, 2015; HANUS et al., 2018). In the research studies carried out in Poland, the attribute of the boundary point which is the most frequently referred to, is: “The mean error of boundary point location in relation to the 1st-order geodetic control network”. So far, however, no analyzes have been carried out to assess the suitability of this attribute for estimating the accuracy of surface areas of parcels included in the real estate cadastre. The authors of this research paper undertook this task. The theoretical considerations were complemented by the results of empirical tests performed on the selected objects. Boundary Point Location Error Attribute (Polish abbreviation: BPP) Recent changes introduced into the real estate cadastre in Poland have contributed to the increased amount of data collected in this public register (PIETRZAK et al., 2012). It has become necessary to record selected attributes of individual objects in a standardized form (MIKA, 2017; BIELECKA, ZWIROWICZRUTKOWSKA, 2013). This also applies to the accuracy of determining the location of a boundary point. This information is currently entered using the boundary point attribute: Boundary Point Location Error [BPP]. In the Land Administration Domain Model [LADM], the estimatedAccuracy attribute for the LA_Point class is the equivalent of this attribute (ISO, 2012). The current list of permissible values of the BPP attribute with the corresponding definitions is demonstrated in Table 1. Table 1. Permissible values of Boundary Point Location Error [BPP] attribute and their definitions. BPP
Mean error relative to first-order geodetic control [m]
1
0.00 – 0.10
2
0.11 – 0.30
3
0.31 – 0.60
4
0.61 – 1.50
5
1.51 – 3.00
6
> 3.00
Source: Own study based on (REGULATION, 2001).
An important problem is the lack of uniform rules for determining the value of the mean error of boundary point location relative to the first-order geodetic control when using various, legally acceptable, surveying techniques, especially photogrammetric methods which are becoming increasingly popular. The BPP is usually attributed subject to the type of actions which are aimed at determining the location of boundary points. Accuracy assessment is usually not carried out. In other words, the value of the BPP attribute is strongly correlated with the source of the data on the boundary point location. It was pointed out in the literature that the values of the BPP attribute entered into the modernized cadastre are frequently inconsistent with the actual status (BENDUCH, PĘSKA-SIWIK, 2017). This issue is of key importance in the context of using this attribute for the purpose of assessing the accuracy of surface areas of parcels. Surface area of the parcel in the real estate cadastre Pursuant to §62 section 1 of the Regulation on the register of lands and buildings (REGULATION, 2001), the surface area of the parcel, constituting one of its spatial attributes, is determined using the rectangular coordinates of boundary points included in the numerical description of boundaries. Under this provision, a necessary condition to determine the surface area using the analytical method is to define the location of all boundary points of the parcel with a mean error not greater than 0.30 m relative to the firstorder geodetic control, which corresponds to the value of the BPP attribute equal to 1 or 2. Otherwise, the surface areas of the parcels previously entered into the register of land and buildings remain valid. Therefore, in many regions of Poland, there is a lack of uniformity in the methods used for calculating surface areas of parcels. Consequently, in addition to the varying levels of accuracy and reliability, the cadastral data describing surface areas of parcels is recorded with unequal precision. Pursuant to the regulations that are no longer in force (ORDINANCE, 1969), surface areas of parcels located outside cities and 41
housing estates were additionally rounded to one are. Currently, the surface area of any parcel should be expressed in hectares with the accuracy of one square meter, regardless of the circumstances. Therefore, it may be presumed that the procedure for estimating the accuracy of surface areas of parcels using the values of the BPP attribute registered in the cadastre can not be carried out for all objects in a given area. If any of boundary points of the parcel are characterized by the BPP attribute with a value greater than or equal to 3, then there are no grounds for calculating the surface area by the analytical method. Nevertheless, according to the Authors of this research paper, even in such a situation, determining the mean error of the surface area in the manner provided for analytical calculations (Formula 3) should be a good approximation of the actual level of accuracy of these data. It is worth reminding that the surface area of the parcel, regardless of the method used for its determination, is always the resultant attribute of the parcel boundaries (HYCNER, HANUS, 2007). Currently, neither the database of the real estate cadastre nor the reports generated from this database contain information on the accuracy with which the surface area of the parcel was determined. Such information could be a valuable clue both for landowners and potential buyers, as well as public administration bodies, including tax authorities. Assessment of accuracy of the surface area of the parcel In order to calculate the surface area of the parcel by the analytical method, the following Formulas (which can be used interchangeably) are used: n
2S = X i ( Yi +1 - Yi −1 )
(1)
i =1 n
−2S= Yi ( X i +1 - X i −1 )
(2)
i =1
where: S – the surface area of the parcel; n – the number of parcel boundary points; Xi, Yi – the coordinates of the i-th parcel boundary point. Basing on the Gaussian law of propagation of mean errors and carrying out the transformations of Formula 1 or Formula 2, it is possible to derive the correct formula for the estimation of the mean error of the surface area of the parcel:
mS =
1 8
n
2 2 m2pi ( Yi +1 − Yi −1 ) + ( X i −1 − X i +1 ) i =1
(3)
where: mS – the mean error of the analytical determination of the surface area; m pi – the mean error of the position of the i-th parcel boundary point; n – the number of parcel boundary points; Xi, Yi – the coordinates of the i-th parcel boundary point. Implementation of Formula 3 requires the knowledge of errors of the location of all boundary points of the parcel. It sometimes happens that this Formula is subject to additional simplification by adopting the same location error for all boundary points of the parcel. Such simplification, as discussed e.g. in (HANUS, 2006; BENDUCH, 2016a), may eventually lead to results that will be significantly divergent from those obtained in the direct implementation of Formula 3. This may occur when boundary points of the parcel are characterized by a large diversity as regards the accuracy which their location has been determined with. While analyzing Formula 3, it can be concluded that the accuracy of determining the surface area of the parcel is influenced by the three basic factors: errors of boundary point location, distribution of these points and their number. However, regardless of the geometry of the parcel, if errors of the boundary point location tend to zero, the mean error of the surface area of the parcel also tends to zero. A similar situation will occur if the number of boundary points is increased, although the function of the mean error of the parcel surface area will then tend to zero at a significantly slower pace, especially when the boundary points are located close to each other - unevenly. The most significant factor when determining the surface area of the parcel are therefore boundary point location errors.
42
BPP attribute and accuracy of the parcel surface area In the real estate cadastre in Poland, the information about boundary point location errors is conveyed through the values of the BPP attribute, which correspond to the intervals demonstrated in Table 1. Therefore, to estimate the mean error of the surface area of the parcel, it is the most reasonable to take the maximum possible value of the boundary point location error for the specified value of the BPP attribute, which, to some extent, protects against making a second-order statistical error (the so-called false negative) in the inference. If BPP=6, theoretically, any value greater than 3.00 m can be adopted. For the calculations to be unified, it is reasonable to use the same, predetermined value of the boundary point location error. The value for BPP=6 recommended by the Authors of this research paper is 4.65 m, which results from the interpolation carried out with the quartic polynomial. It should be emphasized that the BPP=6 attribute occurs sporadically. Its entering into the database of the real estate cadastre requires the consent of the Surveyor General of Poland. For the analyzed research objects, no such cases were identified. It should be noted that using the boundary point location error and Formula 3, it is only possible to determine the confidence interval which the surface area is located within at a given probability level. Due to the lack of data on the direction and sense of the vector of individual boundary point location errors, it is impossible to determine what the actual influence of this factor on the accuracy of determining the surface area will be. It is only possible after a control survey of the boundary points for which there is a reasonable presumption that their location is in conformance with the legal status of the land. Then, it is also possible to compare the record surface area [SEWID], entered into the database of the real estate cadastre, with the geodetic surface area [SGEOD] obtained as a result of the performed surveys. Figure 1 illustrates the basic variants of the influence of the boundary point location errors on the surface area of the parcel. It is important to note that even if there are large values of the BPP attribute, the surface area of the parcel may eventually turn out to be determined correctly, i.e. in a way that is consistent with the actual status [Variant C].
a)
b)
c)
Fig. 1. Possible influence of boundary point location errors on parcel surface area: a) [SEWID > SGEOD]; b) [SEWID < SGEOD]; c) [SEWID = SGEOD]. Source: Own study.
Nevertheless, the assessment of the accuracy of surface areas of the parcels entered into the real estate cadastre based on the BPP attributes seems to be a solution that allows to obtain relevant information about the uncertainty of the parcel surface area in the comprehensive and automated manner. However, it is necessary to ensure an appropriate level of reliability of the BPP attribute values declared by the contractors. Research methodology and description of test objects In order to assess the suitability of the BPP attribute for estimating the accuracy of surface areas of the parcels entered into the real estate cadastre, a control survey was performed using the GNSS RTN method, which covered 80 test objects - cadastral parcels located in three different cadastral districts in southern Poland, where works related to the modernization of the registers of land and buildings have been carried out in recent years. The survey included a total of 440 boundary points identifiable directly in the 43
field, for which there was a reasonable presumption that their location was in conformance with the legal status of the land. In the case of urban parcels, these were most often corners of fences, and in the case of agricultural parcels – boundary strips and the so-called tripoints. Basic information about the research objects is illustrated in Figure 2.
440 boundary points
80 parcels 3 cadastral districts • Białka Tatrzańska • Lubień • Zawoja
•63 points (field survey) •364 points (photogrammetric survey) •13 points (cartometric survey)
•46 urban parcels •22 agricultural parcels •12 parcels acquired for roads
BPP attribute •360 points (BPP=1) •61 points (BPP=2) •18 points (BPP=3) •1 point (BPP=5)
Fig. 2. Research objects in numbers - graphic presentation. Source: Own study.
The number of boundary points for the analyzed parcels ranged from 3 to 23. Only in the case of several agricultural parcels in Lubień cadastral district, the same boundary points were used in the calculations more than once. According to Figure 2, the spatial data on the location of most of the controlled boundary points were captured using photogrammetric techniques. The least (only 13) boundary points were recorded in the cadastre after the performance of cartometric surveys. 421 of the surveyed boundary points, which accounted for almost 96% of the sample size, were included in the numerical description of the boundaries (BPP=1 or BPP=2). This means that the accuracy of the location of these boundary points declared by the contractors of the surveying works allowed to use their coordinates for the calculation of the surface areas of the parcels by the analytical method. The results of the GNSS RTN control surveys were compared with the corresponding coordinates of the boundary points entered into the real estate cadastre. The linear deviation dL was obtained, which was calculated from the following Formula:
dLi = (X pi − X ei )2 + (Ypi − Yei )2
(4)
where: dLi – linear deviation at the i-th control point; Xpi, Ypi – coordinates of the i-th boundary point, captured during the performed GNSS RTN surveys; Xei, Yei – coordinates of the i-th boundary point, entered into the modernized real estate cadastre. According to Formula 4, the coordinates of boundary points captured from control surveys [Xpi, Ypi] were treated as error-free values. However, the spatial data contained in the real estate cadastre regarding the location of boundary points [Xei, Yei] and the values of the BPP attribute assigned to these points were subject to verification. Then, based on the coordinates of the control points [Xpi, Ypi], using Formulas 1 and 2, the geodetic surface area [SGEOD] of the analyzed parcels was determined. The results were confronted with the corresponding surface areas [SEWID], entered into the cadastral database. The mean errors of the surface areas of individual parcels estimated in accordance with Formula 3 were compared using the declared values of the BPP attribute and the linear deviations dL. It was verified whether the calculated geodetic surface areas [SGEOD] fell within the constructed confidence intervals for the surface areas entered into the cadastre [SEWID] at the probability levels of 68%, 95% and 99%. The results of the research were presented in the analytical and graphical forms. Research results Table 2 demonstrates the basic statistics on the results of field surveys carried out by the GNSS RTN method at controlled boundary points. The obtained average value of the linear deviation dL i at the level of 0.43 m, calculated for 440 control points was 2.8 times higher than the mean value of the error of the analyzed boundary point 44
locations, estimated based on the BPP attributes entered into the cadastre. The same situation occured in the case of standard deviation. This proved a significantly greater differentiation in the accuracy of the location of individual boundary points in relation to the information declared in the real estate cadastre after the modernization. The minimum and the maximum values of the linear deviation dLi and of the mean error of the boundary point location declared through the BPP attribute, relative to the first-order geodetic control, were similar to each other. Table 2. Basic statistics for control points. Description
Linear deviation dLi [m]
Mean error according to BPP attribute [m]
Average value
0.43
0.15
Standard deviation
0.52
0.18
Minimum value
0.01
0.10
Maximum value
3.55
3.00
Source: Own study.
The values of the dLi linear deviations at the control points were also analyzed depending on the source of capture of the data on the boundary point location (ZRD attribute). Table 3. Average value of linear deviation dLi and boundary point location error according to BPP attribute depending on source of capture of data on boundary point location (ZRD attribute). ZRD
Definition
Number of control points
Average value of Average value of mean linear deviation error according to dLi [m] BPP attribute [m]
1
Land surveys preceded by property delimitation, restoration of boundary markers, determination of boundary points or determination of their location in a different mode, including the one specified in §39 sections 1 and 2 of the regulation (REGULATION, 2001)
53
0.24
0.25
3
Photogrammetric surveys of boundary points, the location of which has been previously determined under §37 section 2 (REGULATION, 2001), as well as photogrammetric surveys of boundary markers depicted in aerial photographs or on the orthophotomap as a result of their labelling before taking pictures
348
0.43
0.11
5
Approved projects of land subdivision or consolidation and subdivision.
10
0.24
0.26
8
Screen vectorization of the raster map without the use of field survey results
13
1.11
0.60
9
Data sources other than ZRD1 - ZRD8, including the results of findings and analyses referred to in §39 section 3 (REGULATION, 2001)
16
0.63
0.46
Source: Own study based on (REGULATION, 2001).
It follows from Table 3 that the biggest discrepancies were obtained for the boundary points whose location was determined during the modernization using photogrammetric methods (ZRD=3 and ZRD=9). For photogrammetric surveys preceded by the determination of boundaries (ZRD=3), the average value of the linear deviation dLi turned out to be 4 times greater than the average value of the mean boundary point location error according to the declared BPP attribute, and in the case of cartometric surveys on the ortophotomap (ZRD=9 for the studied area) it was 1.4 times higher, respectively. Also for the boundary points, whose location was determined using the screen vectorization of the raster cadastral map (ZRD=8), there were significant discrepancies in this respect. Therefore, it can be concluded that the values of the BPP attribute of the boundary points declared by the contractors of geodetic works proved to be too low in the considered cases. It is worth noting that for 343 out of 348 analyzed boundary points whose location during the modernization was determined using photogrammetric surveys preceded by the determination of the boundaries (ZRD=3), the BPP=1 attribute was assigned. This was also the case in agricultural areas, where the possibilities of identifying the course of the parcel boundary are very limited. For geodetic field surveys preceded by the determination of boundaries (ZRD=1), as it was in the case of approved real estate subdivision projects (ZRD=5), a good consistency was obtained between the results of control surveys and the data entered into the real estate cadastre.
45
Because the mean linear deviation dLi at the level of 0.43 m, contained in Table 2, exceeds the value of the mean boundary point location error which is permissible for the numerical description of the boundaries (0.30 m), it can be assumed that the analyzed sample contains a significant percentage of boundary points whose use for the analytical calculation of the parcel surface area should not occur. This is confirmed by the results presented in Table 4. Table 4. Percentage of boundary points meeting the requirements of the numerical description of boundaries. Description
Percentage
BPP ≤ 0.30 m
95.7%
dLi < 0.30 m
60.7%
dLi < 0.40 m
70.2%
Source: Own study.
The linear deviation dLi, treated as true value of the boundary point location error in relation to the first-order geodetic control, is less than 0.30 m for 60.7% of the analyzed control points. Assuming an additional adjustment of 0.10 m due to the identification of boundary points directly in the field during control surveys, this percentage increases to 70.2%. However, this value is still distant from the one obtained from the analysis of the BPP attributes of the considered boundary points. The difference of 35 and 25 percentage points corresponds to 154 and 112 boundary points, respectively, which according to the adopted research methodology should not be used for the analytical calculation of surface areas of the parcel, contrary to the information contained in the cadastre. This proves the average level of reliability of the declared values of the BPP attribute. In case of merely 101 control points, the obtained value of the linear deviation dL i was found to be consistent with the value of the BPP attribute assigned to a given boundary point (dLi ≤ BPP), which accounted for 23.0% of the sample. Taking into account the aforementioned adjustment for the identification at the level of 0.10 m, this percentage increases to 46.8%. This is not a satisfactory value, though. In view of the above, it can be assumed that the mean errors of the surface areas of the parcels determined using the BPP attributes of boundary points contained in the real estate cadastre will be underestimated. The calculations, the results of which are contained in Table 5 and Figure 3, confirm this thesis. Table 5. Basic error statistics of mean surface areas of parcels calculated according to dLi and BPP. Description
Calculations according to dLi
Calculations according to BPP
Difference
Average value of mean error of surface area of parcel [m2]
32.30
9.03
23.27
Average value of relative error of surface area of parcel
3.5%
0.9%
2.6%
Source: Own study. 120,00 100,00 80,00 60,00 40,00 20,00 0,00 Mean error of parcel surface area acc. to BPP
Mean error of parcel surface area acc. to dLi
Fig. 3. Comparison of mean errors of surface areas of test objects [m2] calculated according to BPP and dLi. Source: Own study.
46
The mean errors of the surface areas of the analyzed parcels, estimated using Formula 3 and linear deviations dLi, turned out to be greater in 75 out of 80 considered cases, which accounted for 93.8% of the sample. According to the information contained in Table 5, the average value of the mean error of the surface area was almost four times higher for the calculations performed using the linear deviations dLi of the control points than for the calculations taking into account the value of the BPP attribute. An analogous situation occurs with regard to relative errors of surface areas. The largest discrepancies were noted for agricultural parcels, which is illustrated in the middle part of Figure 3. The maximum difference between the mean error of the surface area according to dLi and BPP was 95.03 m2. For a relative error, these were as many as 24 percentage points. These discrepancies relate to other objects. Then, the surface areas of the test objects were compared, based on the results of control surveys [SGEOD], with their surface areas entered into the real estate cadastre [S EWID]. The results were presented in the analytical form (Table 6) and graphical form (Fig. 4). Table 6. Basic statistics on the comparison of surface areas of parcels. Description
Result
Average value of difference modulus [SGEOD] - [SEWID] Average percentage share of difference modulus
[m2]
[SGEOD] - [SEWID] in [SEWID]
30.37 3.4%
Source: Own study. 200,00 150,00 100,00 50,00 0,00 -50,00 -100,00 -150,00 -200,00
-250,00 -300,00
Fig. 4. Differences [SGEOD] - [SEWID] of analyzed test objects [m²]. Source: Own study.
It is worth noting in the first place, that the test results contained in Table 6 almost coincide with the average value of the mean error and the relative error of the surface areas of the parcels estimated based on the linear deviation dLi (Table 5). They deviate from the average value of these errors obtained for the calculations taking into account the BPP attribute. It can be assumed therefrom that the mean errors of the surface areas of the parcels calculated with the use of linear deviations dL i of individual control points are more reliable. In the case of 40 test objects, it was found that the surface area determined as a result of the control surveys [SGEOD] was greater than the surface area in the real estate cadastre [S EWID], which accounted for exactly 50% of the sample. Therefore, there is no basis for the hypothesis that the survey results would be subject to a systematic error. The total geodetic area [SGEOD] of the test objects turned out to be 718 m² larger than the cadastral area [SEWID]. For 37 test objects, the difference between [SGEOD] and [SEWID] did not exceed 1%, and in the case of 8 objects, it did not exceed 0.1%. Thus, individual cases were identified where, despite significant linear deviations dLi at the controlled boundary points, the geodetic surface area [SGEOD] turned out to be consistent with the cadastral area [SEWID]. This possibility was suggested in Fig. 1. The percentage of test objects was also verified, where the difference between the surface areas calculated after the performance of the control survey [SGEOD] and the surface area entered into the real estate cadastre [SEWID], did not exceed the estimated value of the error of the mean surface area.
47
The results presented in Table 7 demonstrate that only in 35.0% of the analyzed cases, the mean error of the surface area determined using the BPP attribute was found to be less than or equal to the difference between [SGEOD] and [SEWID]. Better calculation results were ensured by using the linear deviations dLi. This is yet another proof that the mean errors of the surface areas of the parcels located in the analyzed study area, determined using the values of the BPP attribute of the boundary points, may be underestimated. Table 7. Number and percentage of analyzed parcels where the difference [SGEOD] - [SEWID] is less than or equal to the estimated value of mean error of surface area. Description
Number of parcels
Percentage
[SGEOD] - [SEWID] < Mean error of surface area acc. to BPP [SGEOD] - [SEWID] < Mean error of surface area acc. to dLi
28
35.0%
50
62.5%
Difference
22
27.5%
Source: Own study.
Finally, it was verified whether the calculated geodetic surface areas [S GEOD] were within the constructed confidence intervals for surface areas of the parcels entered into the cadastral database [SEWID] at the probability level of 68%, 95% and 99%. Table 8. Number and percentage of test objects whose [SGEOD] falls within the confidence interval for [SEWID]. Description
Calculations based on linear deviations dLi
Calculations based on value of BPP attribute
Number of objects
Percentage
Number of objects
Percentage
P = 68%
50
62.5%
28
35.0%
P = 95%
75
93.8%
39
48.8%
P = 99%
78
97.5%
51
63.8%
Source: Own study.
The performed analysis confirmed that according to the research methodology adopted for the sample of 80 objects, the mean errors of the surface areas of the parcels calculated based on the BPP attribute of boundary points were too low. At the probability level of 95%, the geodetic surface area [S GEOD] of 41 test objects did not fall within the confidence interval constructed for the cadastral surface area [S EWID]. Having increased the probability level to 99%, that was the case for 29 studied objects. This means that the information on the mean errors of the surface areas of the parcels determined based on the values of the BPP attribute assigned to boundary points, which would be entered into the cadastral database, could lead to erroneous conclusions. The level of reliability of this information would be unsatisfactory for the specified cases. Conclusions • •
•
•
The performed research studies allowed to formulate the following conclusions: The main factor influencing the mean error of the surface area of the parcel is the accuracy which the location of the boundary points was determined with. Currently, the information on the estimated accuracy of surface areas of parcels is not entered into the real estate cadastre in Poland. In theory, the introduction of such an attribute could contribute e.g. to the improved protection of property rights of the parties being part of real estate transactions. It would also be a step towards ensuring that the subject data contained in the database of the real estate cadastre was under warranty. However, the attribute determining the mean error of the surface area of the parcel would have to be legally approved beforehand, by amending relevant provisions. A comprehensive assessment of the accuracy of surface areas of parcels can be carried out thanks to the values of the BPP attribute of boundary points entered into the cadastre. This also applies to surface areas that have been determined by a method other than the analytical method. In calculations, for the specified value of the BPP attribute, it is recommended to adopt the maximum possible value of the boundary point location error in relation to the first-order geodetic control. The reliability of the mean errors of the surface areas of the parcels estimated using the BPP attribute is strongly dependent on a reliable assignment of the appropriate values of this attribute to the individual boundary points. The research studies revealed numerous cases where the mean errors of the surface areas of the parcels were proven to have been underestimated due to the incompatibility 48
•
•
of the value of the BPP attribute declared by the contractors with the actual state, especially in the case of the data on the location of boundary points captured using photogrammetric methods and cartometric surveys. As regards the estimation of the mean errors of the surface areas of the parcels, significantly more reliable results were obtained when using the values of the linear deviations dL i identified at the controlled boundary points. This approach also allows for a series of additional analyzes related to the quality of the recorded data describing surface areas. However, it is more time-consuming and requires higher expenditures. In view of the above, there is a need to specify uniform rules for assigning individual values of the BPP attribute to specific boundary points. Only then this attribute could be fully used for the analyzes related to the estimation of the mean error of the surface areas of the parcels without the need for additional verification.
Acknowledgments This paper is the result of research carried out within Dean’s Grant no. 15.11.150.516 in AGH University of Science and Technology, Krakow, Poland References ALKAN, M., SOLAK, Y. 2010. An investigation of 1: 5000 scale photogrammetric data for cadastral mapping uses: A case study of Kastamonu-Taskopru. African Journal of Agricultural Research, 5(18): 2576–2588. BAJTALA, M., HUDECOVA, L., SOKOL, S. 2017. The reliability of parcel area. In the 17th International Multidisciplinary Scientific GeoConference SGEM 2017, 29 June - 5 July, Vol. 17, Issue 22, p. 689696. BENDUCH, P. 2016a. The assessment of the influence of cadastral parcel boundary points location errors on the accuracy of analytical determination of their surface area. Geomatics and Environmental Engineering, 10(1): 17-31. BENDUCH, P. 2016b. The assessment of the influence of average errors of parcels' surface areas on the final result of land properties' valuation process. Geomatics and Environmental Engineering, 10(4): 2738. BENDUCH, P. 2017. Problematic aspects of determining the surface area of grounds, buildings and premises for cadastre and real estate taxation purposes. In the 10th International Conference “Environmental Engineering”: selected papers. Vilnius Gediminas Technical University, Lithuania, April 27–28, 2017. BENDUCH, P., PĘSKA, A. 2016. The influence of the cadastre modernization on the real estate tax base assessment. Infrastructure and Ecology of Rural Areas, III/1: 787-800. BENDUCH, P., PĘSKA-SIWIK, A. 2017. Assessing the usefulness of the photogrammetric method in the process of capturing data on parcel boundaries. Geodesy and Cartography, 66(1): 3-22. BERK, S., FERLAN, M. 2018. Accurate area determination in the cadaster: Case study of Slovenia. Cartography and Geographic Information Science, 45(1): 1-17. BIELECKA, E., ZWIROWICZ-RUTKOWSKA, A. 2013. Organisational aspects of spatial information infrastructure in Poland. Geodesy and Cartography, 62(1): 85-95. DESKA, K. 2006. Analiza dokładności określenia powierzchni działek rolnych na potrzeby systemu IACS. Przegląd Geodezyjny, 78(1): 3-9. DOSKOCZ, A. 2011. Dokładność obliczania pola powierzchni ze współrzędnych płaskich prostokątnych. Acta Scientiarum Polonorum. Geodesia et Descriptio Terrarum, 10(3): 29-43. DOSKOCZ, A. 2014. About Accuracy of Analytical Determination of Areas for Cadastre and Other Purposes. In the 9th International Conference “Environmental Engineering”, 22–23 May 2014, Vilnius, Lithuania. GHILANI, C. D. 2000. Demystifying Area Uncertainty: More or Less. Surveying and Land Information Systems, 60(3): 183–189. FROLOV, Y. S., MALING, D. H. 1969. The accuracy of area measurement by point counting techniques. The Cartographic Journal, 6(1): 21-35. HANUS, P. 2006. Ocena przydatności dokumentacji byłego katastru austriackiego dla potrzeb prac geodezyjnych. Unpublished PhD thesis, AGH University of Science and Technology, Kraków. HANUS, P. 2013. Correction of location of boundaries in cadastre modernization process. Geodesy and Cartography, 62(1): 51-65.
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HANUS, P., HYCNER, R., KWARTNIK-PRUC, A. 2013. Analiza terminologiczna wybranych problemów katastru i zagadnień pokrewnych. Cz. 1, Działka, granica, nieruchomość. Magazyn Geoinformacyjny Geodeta, 10: 26–31. HANUS, P., JASIŃSKA, E., PREWEDA, E. 2014. Analysis of the accuracy of determining the coordinates property borders. In the 9th International Conference “Environmental Engineering”, 22–23 May 2014, Vilnius, Lithuania. HANUS, P., PĘSKA-SIWIK, A., SZEWCZYK, R. 2018. Spatial analysis of the accuracy of the cadastral parcel boundaries. Computers and Electronics in Agriculture, 144: 9-15. HEJMANOWSKA, B., OSZCZAK, S., CIEĆKO, A. 2005. Validation of methods for measurement of land parcel areas. Final Report. HYCNER, R., HANUS, P. 2007. Wykonawstwo geodezyjne. Wydawnictwo Gall, Katowice. ISO 19152:2012. Geographic information - Land Administration Domain Model (LADM). KWINTA, A. 2012. Accuracy of land parcel area measurement. Geomatics and Environmental Engineering, 6(2): 71-83. MIKA, M. 2017. Interoperability cadastral data in the system approach. Journal of Ecological Engineering, 18(2). MIKA, M., LEŃ, P. 2016. The research of dependency between the size of the cadastral plots and the measurement error of their areas using a handheld GPS receiver. Geomatics and Environmental Engineering, 10(4): 71-80. NOWAK DA COSTA, J., WALCZYNSKA, A. 2010. Kompsat-2 Geometric Quality Assessment for Measuring the Area of European Land Parcels. Proceedings of the ISPRS WG VII/5 Workshop on on Remote Sensing Methods for Change Detection and Process Modelling. University of Cologne, Germany, 18-19 November 2010. OGECHI, B. O., ODERA, P. A. 2015. Improvement of area accuracy in general boundary areas in Kenya. Case study of Juja Kiambu County. Kabarak Journal of Research & Innovation, 3(1): 54-64. OLOFSSON, P., FOODY, G. M., HEROLD, M., STEHMAN, S. V., WOODCOCK, C. E., WULDER, M. A. 2014. Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148: 42-57. ORDINANCE of the Ministers of Agriculture and Municipal Economy of 20 February 1969 on land registry (OJ of 1969, No. 11, item 98). PĘDZICH, P., KUŹMA, M. 2012. Application of Methods for Area Calculation of Geodesic Polygons on Polish Administrative Units. Geodesy and Cartography, 61(2): 105–115. PIETRZAK, L., HOPFER, A., CEGIELSKI, S. 2012. Reforms of a real estate cadastre in Poland. Geodesy and Cartography, 61(2): 117-126. PLUTO-KOSSAKOWSKA, J., GRANDGIRARD, D., KERDILES, H. 2007. Assessment of parcel area measurement based on VHR SAR images. In Proceedings of the 2007 Annual Conference of the Remote Sensing and Photogrammetry Society (RSPSoc2007) – Newcastle upon Tyne, p. 11-14. PLUTO-KOSSAKOWSKA, J., GRANDGIRARD, D., ZIELIŃSKI, R., KAY, S. 2008. Assessment of the area measurement on Cartosat-1 Image. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 37: 1315-1322. PREWEDA, E., JASIŃSKA, E. 2014. Effect the accuracy of benchmarks to establish of the determination of geodetic network. In the 9th International Conference “Environmental Engineering”, 22–23 May 2014, Vilnius, Lithuania. REGULATION of the Minister of Regional Development and Construction of 29 March 2001 on the register of land and buildings (Official Journal 2016, No. 0, item 1034 – consolidated text, as amended). SHIH, T. Y. 1995. Area Computation by Coordinates. Journal of Surveying Engineering, 121(4): 145–154. THE ACT of 17 May 1989 Geodetic and Cartographic Law (Official Journal 2017, No. 0, item 2101 – consolidated text, as amended). ZHAO, H., PEI, Z. 2016. Area accuracy analysis for investigation of rural land contractual management right. Transactions of the Chinese Society of Agricultural Engineering, 32(18): 241-246.
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SPATIAL PLANNING AS A TOOL FOR PROTECTION OF MINERAL SPRINGS IN POLAND Agnieszka Bieda, Ph.D. AGH University of Science and Technology Faculty of Mining Surveying and Environmental Engineering Department of Geomatics Krakow, Poland e-mail:
[email protected] – contact person
Anna Bieda, M.Sc.
AGH University of Science and Technology Faculty of Drilling, Oil and Gas Department of Drilling and Geoengineering Krakow, Poland e-mail:
[email protected] Abstract There is a growing interest in the intake and use of mineral springs. Although their deposits are largely renewable, they should be managed in a rational way. There is no denying the fact that the proper management and protection of mineral springs is significantly facilitated by the possibility of utilizing available tools ensured by spatial planning. It provides the possibility of introducing certain restrictions imposed by the Act on health resort treatment, health resorts and protected health resort areas as well as on health resort communes into the acts of local law, such as local land use plans. The purpose of this research paper is to describe the role of spatial planning at the local level in the protection of mineral spring deposits. It analyzes local land use plans which are in force in health resort communes. The research was carried out in the health resorts of Lesser Poland Province. Key words: local land use plan, health resort, mineral springs, Lesser Poland Province Introduction Pursuant to (ACT, 2011), mineral spring is groundwater, which is not contaminated chemically or microbiologically, which is characterized by natural variability of physical and chemical properties and contains: • dissolved solid minerals − not less than 1000 mg/dm³, or • ferrous ion − not less than 10 mg/dm³ (ferruginous waters), or • fluoride ion − not less than 2 mg/dm³ (fluoride water), or • Iodine ion − not less than 1 mg/dm³ (iodide waters), or • divalent sulfur − not less than 1 mg/dm³ (sulphide waters), or • metasilic acid − not less than 70 mg/dm³ (silicon waters), or • radon − not less than 74 Bq/dm³ (radon waters), or • unbound carbon dioxide − not less than 250 mg/dm³. Groundwater, which has been recognized as mineral springs with healing properties, is assigned very high value by the Polish legislation (DOWGIAŁŁO, 2004). Therefore, these deposits are the property of the State Treasury and are subject to special protection (ACT, 2011). This protection is very often manifested by the establishment of health resorts in the areas where mineral springs occur (ACT, 2005). It is aimed at preventing negative consequences which both industrial activities and improper management may have on mineral spring deposits (CIĘŻKOWSKI et al., 2010). As it is the case with other niche, but extremely important spatial conditions, such as deposits of renewable energy sources (BIEDA, BIEDA, 2017) or landslides (BYDŁOSZ, HANUS, 2013), this protection should be implemented using spatial planning tools (KORELESKI, 2008). There are 45 towns (or their parts) in Poland that have the status of a health resort. The region with the largest number of health resorts (11) is Lower Silesian Province. The second place is taken by Lesser Poland Province (9). The distribution of health resorts in Poland is illustrated in Figure 1.
51
Fig. 1. Distribution of health resorts in Poland. Source: (www.healthresort.pl, access: 15.02.2018).
Since the use of all mineral resources depends largely on proper management of space and compliance with restrictions related to the protection of their deposits (GOŁAŚ, 2017; KRYZIA, KRYZIA, 2017), and because rational management of deposits and securing current and future needs of mineral spring extraction requires cooperation of various public administration authorities (PTAK, PARASZCZUK, 2017), the purpose of this research paper is to describe the role that spatial planning documents implemented at the local level have in the protection of mineral spring deposits. Methodology and materials Mineral springs are a national treasure and their protection is a basic obligation of commune bodies (ACT, 2005). This obligation is implemented by introducing various restrictions, which are enforced by the local land use plan (KORELESKI, 2009). Therefore, part of the research studies involved a comparative analysis of the provisions included in local land use plans which are in force in the health resort communes of Lesser Poland. Due to the fact that the mineral spring deposits located in Lesser Poland constitute 1/3 of the country's total deposits, and their flow is 1,566.2 m³/h (RESOLUTION, 2003), the research area has been narrowed down to one region. The mineral springs occur in the southern part of Lesser Poland and the concentration of their intakes occurs in the border area of the Province in the Nowy Sącz sub-region. Their distribution in the Province has been presented against other mineral deposits (Figure 2). The mineral spring deposits located in Lesser Poland resulted in the establishment and development of the health resorts such as Krynica, Muszyna, Piwniczna, Rabka-Zdrój, Szczawnica, as well as Wapienne near Sękowa, Wysowa near Uście Gorlickie and Swoszowice. The characteristics of these health resorts are summarized in Table 1.
52
Fig. 2. Location of main mineral deposits relative to areas of natural value in Lesser Poland: − mineral springs. Source: (RESOLUTION, 2003). Table 1. Characteristics of health resorts in Lesser Poland Province. No.
No. in Fig. 1
Name of health resort
Commune
Type of health resort
1
18
Krynica-Zdrój
Krynica-Zdrój
mountain
2
19
Muszyna
Muszyna
piedmont
3
20
Piwniczna-Zdrój
Piwniczna-Zdrój
piedmont
4
21
Rabka-Zdrój
Rabka-Zdrój
mountain
5
22
Swoszowice
Kraków
lowland
6
23
Szczawnica
Szczawnica
mountain
7
24
Wapienne
Sękowa
piedmont
8
25
Wysowa-Zdrój
Uście Gorlickie
mountain
9
26
Żegiestów-Zdrój
Muszyna
mountain
Source: Own study.
1. 2. 3.
The analyzed local land use plans are included in the following resolutions (as amended): Resolution No. XV/181/2004 of the Town and Health Resort Commune Council of Muszyna of March 12, 2004 on the local land use plan for Żegiestów in the Commune of Muszyna. Resolution No. XVII/112/2004 of the Commune Council of November 26, 2004 on the adoption of the local land use plan for the Commune of Sękowa Resolution No. XVII/100/2004 of the Town Council of Szczawnica of July 26, 2004 on the adoption of the local land use plan for the town of Szczawnica for the mining area “SZCZAWNICA I”, extended with the adjacent investment areas within the survey limits set out in § 2. 53
4. 5. 6. 7. 8. 9.
Resolution No. XL/489/2006 of July 20, 2006 of the Town and Health Resort Commune Council of Muszyna on the local land use plan for the area in the town of Muszyna in the Commune of Muszyna. Resolution No. XLIII/333/06 of the Town and Commune Council of Piwniczna-Zdrój of July 28, 2006 on the adoption of the local land use plan for the town and commune of Piwniczna-Zdrój, Structural Unit “A.II” - Zawodzie. Resolution No. XLVIII/457/2010 of the Commune Council of Uście Gorlickie of November 10, 2010 on the adoption of the local land use plan for the commune of Uście Gorlickie I “Wysowa - Blechnarka - Ropki – Hańczowa”. Resolution No. XXVII.165.2012 of the Town Council in Krynica-Zdrój of June 27, 2012 on the adoption of the local land use plan for Krynica-Zdrój Health Resort (area 1 – Zdrój). Resolution No. XII/130/11 of the Krakow City Council of April 13, 2011 on the adoption of the local land use plan for the area “Swoszowice – Uzdrowisko”. Resolution No. LIV/367/14 of the Town Council in Rabka-Zdrój of October 10, 2014 on the adoption of the local land use plan for the “A” protection zone of the health resort Rabka-Zdrój.
Results There are three types of protection zones in health resorts, marked with the letters “A”, “B” and “C” (ACT, 2005). Their characteristics are demonstrated in Table 2. Table 2. Characteristics of protection zones in health resorts. Denotation
A
B
Ground cover not less than 65% of green areas
Located facilities
health resort treatment facilities and devices; there is an obligation facilities for health resort treatment or for patient or to develop a local land tourist service, to the extent not hampering use plan for the whole the functioning of health resort treatment (especially zone boarding houses, restaurants or cafes).
1)
facilities that do not affect adversely the healing properties of health resort or its protection zones, as well as service and tourist facilities that are unobtrusive for patients (including hotels or recreation, sports and communal facilities); residential facilities; other facilities associated with satisfying the needs of people staying in this area.
area adjacent to “A” zone, constituting its surroundings
affecting the preservation of landscape and climatic values as well as protection of natural resources of raw materials with healing properties.
area adjacent to “B” zone, constituting its surroundings
not less than 50% of green areas 2) 3)
C
not less than 45% of biologically active areas
Remarks
1) 2)
1)
Source: Own study based on (ACT, 2005).
Local land use plans for individual zones contain restrictions defined by the Act (ACT, 2005). Of course, most of them concern the “A” zone (Table 3). All the restrictions presented in Table 2 can be found in the analyzed local land use plans developed for the health resort communes of Lesser Poland Province. In the plan prepared for the Swoszowice health resort, it was even contained that in the health resort protection zones there are restrictions, orders, limitations and permissions resulting from separate regulations regarding health resort treatment and health resorts, as well as from the statute of a health resort. In Rabka-Zdrój on the other hand, investments allowed by the plan's settlements may be implemented provided that the conditions set out in the separate regulations, in particular the regulations relating to the “A” zone specified in the Act on health resort treatment, health resorts and protected health resort areas as well as on health resort communes, are taken into account. There are situations when, for some reason, communes allow some minor deviations from statutory provisions. In Krynica, for example, it is allowed to earmark part of the service development area, located within the historic urban layout of the town of Krynica-Zdrój, entered into the register of monuments “A”-278/M, denoted with the symbol 1.Uz.1, for the water bottling plant, pending its transfer outside the “A” health resort protection zone.
54
Table 3. Restrictions resulting from the Act on health resort treatment, health resorts and protected health resort areas as well as on health resort communes. No. Restrictions
„A”
„B”
„C”
1
construction of industrial plants
X
X
X
2
construction of single-family and multi-family residential buildings
X
3
construction of freestanding garages
X
4
construction of commercial facilities with a surface area of more than 400 m²
X
X
5
construction of petrol stations and distribution points of petroleum products
X
X1
6
construction of motorways and expressways
X
7
construction of above-ground car parks
X2
X3
8
construction of base stations for mobile telephony, radio and television broadcasting stations, radiolocation stations and other stations emitting electromagnetic waves, excluding communication devices for the needs of public safety and rescue services
X
X
9
construction of building structures that may always have significant environmental impact 4
X
10
construction of water impounding structures on rivers as well as hydroelectric power plants and wind farms
X
11
opening landfills of solid and liquid waste, scrap metal yards and collection points for agricultural products, chemical fertilizer depots, chemical agent depots and fuel depots
X
12
opening camping sites, construction of chalets and bungalows
X
13
running open-air markets, with the exception of souvenir shops, sale of folk products, regional products, in the forms and places determined by the commune
X
14
conducting farming activity
X
15
keeping livestock
X
16
organizing car and motorcycle rallies
X
17
organizing mass events
X
18
recovering mineral raw materials other than natural raw materials with healing properties
X
X
X
19
felling of forest and park trees, with the exclusion of maintenance cuts
X
X5
X5
20
carrying out drainage works and other activities causing unfavorable change of existing water conditions
X
X
X
21
carrying out activities that have a negative impact on the physiography of health resort and its urban layout or healing properties of the climate
X
X
X
X
Closer than 500 m from the boundary of the “A” zone. With the number of parking spaces exceeding 15% of beds in spa hospitals, sanatoriums and boarding houses, however, not exceeding 30 parking spaces; and above-ground car parks in front of service facilities with a number of parking spaces not exceeding 10. 3 With the number of parking spaces exceeding 50, except for underground and above-ground multi-level car parks. 4 Including in particular: car service workshops, smokehouses, tanneries, with the exception of building facilities aimed at improving the sanitary state of the health resort, in particular water and sewage system, gas network, gas boiler rooms, drilling for the intake of mineral springs 5 And felling specified in forest development plans. 1 2
Source: Own study based on (ACT, 2005).
Conclusions There is a growing interest in the intake and use of mineral springs, which is mainly resulting from their increasingly common application in recreation and bottling industries, as well as from the growing interest in therapies of illnesses and nourishing treatments. Their deposits are largely renewable, but their management should be conducted in a rational manner, with the use of modern organizational and technical solutions, in accordance with formal and legal conditions and based on results of performed research studies. Reasonable use of these resources can trigger the development of the economies of regions where their deposits occur, and consequently also for the national economy. There is no denying the fact that the proper management and protection of mineral springs is significantly facilitated by the possibility of utilizing available tools ensured by spatial planning. However, it should be remembered that: 1. Even if a specific provision is not included in the local land use plan, it does not mean that it is allowed. The Act on health resort treatment, health resorts and protected health resort areas as well as on health resort communes, which contains restrictions on health resort protection zones, has a higher rank than any local law. 2. Local land use plans are not always prepared for the whole area of the health resort. The “A” protection zone must always be covered by the plan. Usually, communes strive to develop a local plan for the “B” zone as well. The “C” zone is frequently covered only partially. 55
3.
The plans developed before the Act on health resort treatment, health resorts and protected health resort areas as well as on health resort communes entered into force (2005) should have been updated with its provisions. Therefore, when dealing with these planning documents, special attention should be paid to the updatedness of the version of the local plan which is being used.
Acknowledgments The paper was carried out under the Statutory Research at the Faculty of Drilling, Oil and Gas, AGH University of Science and Technology, financed from the funds of the Polish Ministry of Science and Higher Education. Agreement 11.11.190.555. References ACT of March 27, 2003 on spatial planning and land management, i.e. of May 11, 2017 (Journal of Laws of 2017, item 1073, as amended) [Ustawa z 27 marca 2003 roku o planowaniu i zagospodarowaniu przestrzenneym, tj. z 11 maja 2017 roku (Dz. U. z 2017 roku, poz. 1073, z pózn. zm.)]. ACT of July 28, 2005 on health resort treatment, health resorts and protected health resort areas as well as on health resort communes, i.e. of May 11, 2017 (Journal of Laws of 2017, item 1056, as amended) [Ustawa z 28 lipca 2005 roku o lecznictwie uzdrowiskowym, uzdrowiskach i obszarach ochrony uzdrowiskowej oraz o gminach uzdrowiskowych, tj. z dnia 11 maja 2017 r. (Dz.U. z 2017 r. poz. 1056, z pózn. zm.)]. ACT of June 9, 2011 – Geological and Mining Law, i.e. of October 16, 2017 (Journal of Laws of 2017, item 2126, as amended) [Ustawa z 9 czerwca 2011 r. - Prawo geologiczne i górnicze, tj. z 16 października 2017 r. (Dz.U. z 2017 r. poz. 2126, z pózn. zm.)]. BIEDA, A., BIEDA, A. 2017. Renewable energy in the system of spatial planning in Poland. Geographic Information Systems Conference and Exhibition “GIS Odyssey 2017”, Conference proceedings, 2842. BYDŁOSZ, J., HANUS, P. 2013. The impact of landslide areas on municipal spatial planning. Real Estate Management and Valuation, 21(4): 5-10. CIĘŻKOWSKI, W., CHOWANIEC, J., GÓRECKI, W., KRAWIEC, A., RAJCHEL, L., ZUBER, A. 2010. Mineral and thermal waters of Poland. Przegląd Geologiczny, 58(9/1): 762-773. DOWGIAŁŁO, J. 2004. Therapeutic waters in the Polish geological and mining law. Environmental Geology, 46(5): 643-645. GAŁAŚ, S. 2017. Assessment of implementation of protection of mineral deposits in spatial planning in Poland. Land Use Policy, 67: 584-596. KORELESKI, K. 2008. Studies of natural environmental conditions for the needs of local spatial management plans in Poland. Geomatics and Environmental Engineering, 2(1): 41-47. KORELESKI, K. 2009. The system of spatial planning and land management in Poland. Geomatics and Environmental Engineering, 3(2): 27-42. KRYZIA, K., KRYZIA, D. 2017. Revitalization possibilities of the post-mining area of natural aggregate mine in the Waryś village. Infrastruktura i Ekologia Terenów Wiejskich, III/1: 963-975. PTAK, M., PARASZCZUK, K. 2017. Ochrona złóż wód leczniczych w zagospodarowaniu przestrzennym terenów górniczych [Protection of medicinal waters in the spatial development of mining areas]. Bezpieczeństwo Pracy i Ochrona Środowiska w Górnictwie, 3: 25-30. RESOLUTION No. XV/174/03 of the Sejmik of Lesser Poland Province of 22 December 2003 on the adoption of the Land Use Plan of Lesser Poland Province, as amended [Uchwała Nr XV/174/03 Sejmiku Województwa Małopolskiego z dnia 22 grudnia 2003 roku w sprawie uchwalenia Planu Zagospodarowania Przestrzennego Województwa Małopolskiego, z pózn. zm.].
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MONITORING OF SELECTED GEOHAZARDS BY USING UNMANNED AERIAL SYSTEMS (UAS) Peter Blistan, assoc. prof., Ph.D., MBA Institute of Geodesy, Cartography and Geographical Information Systems Faculty of Mining, Ecology, Process Control and Geotechnology Technical University of Košice Košice, Slovakia e-mail:
[email protected] – contact person Department of Geotechnics, Geomatics and Waste Economy Faculty of Environmental, Geomatic and Energy Engineering Kielce University of Technology Kielce, Poland e-mail:
[email protected] – contact person
Ľudovit Kovanič, Ph.D.
Institute of Geodesy, Cartography and Geographical Information Systems Faculty of Mining, Ecology, Process Control and Geotechnology Technical University of Košice Košice, Slovakia e-mail:
[email protected]
Matej Patera, M.Sc.
Institute of Geodesy, Cartography and Geographical Information Systems Faculty of Mining, Ecology, Process Control and Geotechnology Technical University of Košice Košice, Slovakia e-mail:
[email protected]
Paweł Frąckiewicz, M.Sc.
Department of Geotechnics, Geomatics and Waste Economy Faculty of Environmental, Geomatic and Energy Engineering Kielce University of Technology Kielce, Poland e-mail:
[email protected]
Marcin Gil, M.Sc.
Department of Geotechnics, Geomatics and Waste Economy Faculty of Environmental, Geomatic and Energy Engineering Kielce University of Technology Kielce, Poland e-mail:
[email protected] Abstract Landslides belong to the category of serious geohazard that is commonly found in different parts of the Earth. They are caused by natural as well as anthropogenic factors. Their occurrence has a significant impact on urbanisation and land use. The primary influence on landslide formation is a loss of vegetation, changes in climatic conditions and harmful human activity. In Central Europe, namely in Slovakia, there are several sites where there are localities with smaller or more massive landslides that may affect the land relief, limit the urban use of the land and cause material damage. Therefore there is necessary the systematic monitoring of these landslides. In recent years a modern trend in the geo-hazard monitoring is the use of unmanned aerial systems (UAS). Aerial photogrammetry with UAS is a new technology for monitoring of the objects on the earth surface, including landslides. One of the results of the UAS aerial photogrammetry is the point cloud. Its detail and accuracy are comparable to another modern method terrestrial laser scanning TLS. Several scientific papers have demonstrated that a 3D model created from 57
the point cloud obtained by processing of the UAS photogrammetry images is suitable for assessing changes in the surface of the ground. The aim of our research is long-term stage monitoring and verification of the land changes using UAS photogrammetry in selected locations in Slovakia. One of these sites is also a landslide in the cadastral area of the municipality of Nižná Myšľa, which falls into the Košice self-governing region, district Košice - okolie (Slovakia). Key words: Unmanned aircraft systems, Photogrammetry, Mapping, Digital terrain model, Landslide Introduction Landslides are the most common and dangerous geodynamic phenomenon affecting urbanism on the Earth. They occur in places where there are combinations of several factors such as • morphology of the slope, • the inclination of the slope, • length of the slope, • the intensity of weathering, • geological structure of the territory etc. A significant influence on slope movements is also the tectonic activity and climatic conditions (GARIANO, GUZZETTI, 2016). In Europe, due to its geological and geomorphological structure, there are several sites where slope movements of smaller or larger dimensions occur. These landslides cause a change of the relief of the affected site where the use of the land is limited. Slovakia belongs to the countries with a relatively large number of landslides also. Based on the Atlas of the Slope Stability Map in Slovakia, there are 19104 registered landslides in Slovakia. These slope deformations threaten 98.8 km of motorways and roads of the first class, 571 km of roads II. and III. Class, 62 km of railways, 11 km of overhead lines, 3.5 km of oil pipelines, 101 km of gas pipelines, 291 km of waterworks and nearly 30000 buildings (WWW.1). Landslides are generally defined as gravitational movements of rock masses from a higher position to lower. The notion of slope movements associates all the gravitational movements of rock masses in the slopes, except those where the transport media - water, snow, wind (CRUDEN, VARNES, 1996; ČABALOVÁ, BALIAK, KOPECKÝ, 1999) are carried rock material away. Based on the geological research, it has been demonstrated that the majority of landslides in Slovakia that occurs in the inhabited areas during the last 30 years were either wholly or partly caused by man 's intervention in the sensitive stabilisation regime of old landslides. Particularly dangerous are anthropogenic influences that cause changes in groundwater regime. Landslides are mainly affecting on • agricultural land and forests, • urbanisation, • communication structures, • water management structures. (ZÁRUBA, MENCL, 1987; NEMČOK, 1982). Material and methods Surface object and phenomena mapping using UAS In recent years Unmanned aerial systems - UAS is a modern technology that has been used for mapping of the surface objects including landslide hazards (NIETHAMMER et al, 2012; STUMPF et al, 2013; ARDI et al, 2018; ROSSI et al, 2018). UAS include many types of flying units. In addition to airplanes and helicopters, there are also very popular advanced multi-rotor helicopters. UAV´s are carriers for a variety of the devices, most often equipped with cameras and Lidars. UASs are now commonly equipped with navigation technologies - the Global Navigation Satellite System (GNSS), inertial measurement systems or compass that serve the positional orientation. This paper will focus on documenting and mapping of the geohazards and photogrammetric data collection using UAS. Aerial photogrammetry is a surveying method designed to collect data using photographic devices (cameras) with results in orthophotographs, topographic maps or terrain 3D models from the data thus obtained (KRŠÁK et al, 2016). These outputs can be used as underlying digital data (REMONDINO et al, 2011; NEX, REMONDINO, 2013). The process of mapping the surface objects using UAS can be divided into two basic parts. In th e first part, we collect the data and in the second part obtained data are processed. System capabilities limit data collection. Such limitations include flight height or parameters of the digital camera used for capturing of the images. Various commercial and non-commercial software that works on the principle
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of automated or semi-automated output generation serves to produce requisite outputs (KYŠEĽA et al, 2013; ARCDATA, 2017; PAVELKA, 2009). Case study – testing of the UAS v Nižná Myšľa locality Area of interest The area of interest is about 7 km SE from Košice in the cadastral area of the municipality of Nižná Myšľa, which belongs to Košice self-governing region, district Košice - okolie (Fig. 1). The terrain of the territory is smoothly modeled with a slope of 5 to 12%. The slightly wavy surface indicates the occurrences of geodynamic phenomena - landslides. From a geological aspect, the area of interest is a part of the region of the neogenic tectonic columns and the area of the intramountain basins. There occur sediments with the character of fine-grained soils. Landslides in this area have the character of active frontal landslides along rotary and combined shear surfaces (TOMETZ et al, 2010). Landslides of different stages disrupt the territory. The morphological features of the older landslides are covered by anthropogenic activity and the processes of slope modelling of non-sliding character. Based on general knowledge of engineering geology this territory can be characterized as follows (TOMETZ et al, 2010): • Territory builds quaternary (deluvial-eluvial) and neogenic sediments (high-plastic clays, less medium-plastic clays). • In the locality, the atmospheric precipitation has an impact to the occurrence of slope movements. • The groundwater level is at different depths (1 - 22 m below the terrain) and has a surface tension character. At the time of increased precipitation, it can climb up to the surface in the observation boreholes. • Shear surfaces are located at depths of 3 to 17 m under the terrain. • Anthropogenic impacts related to the weakening the heal of the slope (excavations and cuttings), loading the top part of it (construction of new homes), as well as poorly drained rainwater from the roofs of residential buildings and reinforced surfaces, have affected by the stability of the territory.
Fig. 1. The geographical position of the area. Source: Own study.
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The landslide in Nižná Myšľa was one of the most significant geodynamic phenomena in the territory of the Košice Autonomous Region. It was widely documented during extensive floods in 2010. The landslide in Nižná Myšľa occurred on 4.6.2010, and its consequences on the anthroposphere and the environment of the village were disastrous. It should be to tell that this was an extraordinary situation with an acute danger status to the lives of inhabitants and their property - residential houses and other objects in the cadastral territory of the municipality. The landslide was mainly due to long-term and heavy rainfall between 10 May and 5 June 2010.
Fig. 2. View on the area of interest. Source: Own study.
The research aimed to verify the usability of UAV photogrammetry in the documentation of the landslide area and the identification of morphological changes with damage to the road infrastructure due to the activation of the landslide. The accuracy with which the low-cost UAV DJI Phantom 4 can capture these changes was tested. The road communication between the municipalities of Nižná Myšľa and Nižná Hutka and the adjacent landslide area located northeast of this communication was surveyed (Fig. 2). Traces of landslide are visible on both sides of the road in this area (Fig. 3).
Fig. 3. Observable landslides on area Nižná Myšľa. Source: Own study.
Photogrammetric data collection using UAS The data collection was performed using the DJI Phantom 4 quadcopter (Fig. 4). This UAS device belongs to the category of "cheap" UAVs. It contains as well a built-in GPS module, a gyrocompass and a 12Mpx DJI HD camera. The camera is mounted on a 3-axis gimbal. The whole flight was pre-programmed by the Android application Pix4D. Three flights in different heights were realized in total. Each took about 15 minutes. A total of 363 aerial images were created. Specifications of the UAS are stated in Table. 1 Image processing and modelling The aerial images were graphically modified before processing in specialised photogrammetric software. The adjustment consisted of the following features: white balance correction, Noise reduction, and Chromatic aberration correction. Subsequently, the images were processed in the Agisoft PhotoScan® software (Fig. 5). Agisoft PhotoScan® is photogrammetric software for efficient 3D image processing to 60
create detailed point cloud and high-quality, textured, 3D scene model. Work in this software environment is relatively simple and the outputs generated are highly accurate (Fig. 6). For these reasons, Agisoft PhotoScan® has become wide-spread software in a relatively short time. Table 1. DJI Phantom 4 – technical parameters. Aircraft Weight (Battery & Propellers included): Max Ascent / Descent Speed: Max. flight speed: Max. flight time: Camera Operating Environment Temperature: Sensor size: Effective Pixels: Resolution: Gimbal pitch Remote Control Communication Distance (open area):
1380g 6m/s / 4m/s 20m/s 28 min. 0°C-40°C 1/2.3" 12 Megapixels 4000×3000 -90° to +30° CE Compliant: 3,5km; FCC Compliant: 5km
Source: Own study.
Fig. 4. UAV - DJI Phantom 4. Source: Own study.
Fig. 5. Image processing in Agisoft PhotoScan® with positions of images. Source: Own study.
Two products of processing were used. Dense point cloud and the final product of the entire process is a textured 3D model that faithfully displays the terrain (Fig. 6). The generated model can be exported through export filters to different formats, depending on the needs of the next processing. In final 344 images were processed in our research. A total of 10 ground control points (GCP) (Fig. 5 and 6) were used to transform the frame into the S-JTSK coordinate system. The GNSS Leica 900CS gave 61
the coordinates of GCP. The results of the photogrammetric data processing show the following characteristics: • GSD resolution is 2.04 cm/pixel. • The error in the position of the measured point in the image is 0.259 pixels. • The quadratic average of the residue at the GCP is 0.017 m. • Longitudinal image overlay was 80% and 60% lateral.
Fig. 6. Textured 3D model with the position of the GCP. Source: Own study.
Results and discussion In the last period, the permanent impact on the population has in particular climatological and consequently geological threats. The first step is risk analysis, which is a prerequisite for understanding the threats and, of course, for effective risk management (BLIŠŤANOVÁ, 2017). In the area of risk management, the evaluation of the risks of the landslides - the risks that cause geodynamic phenomena – has an important role (MESÁROŠ et al, 2015; URBAN et al, 2017). Geodynamic phenomena, especially landslides, have caused considerable damage in Slovakia in recent years. For this reason, it is still an essential task of geodesy to monitor these phenomena by the methods which are as effective and as accurate as possible. Just in the field of monitoring of landslide areas, modern methods of data collection, for example, INSAR, LIDAR, and UAV photogrammetry, where their significant advantage is, in particular, the speed of data collection, density of surveyed points and their financial availability. To assess the suitability of low-cost UAV photogrammetry as an alternative method to classical terrestrial geodetic methods, we have researched the landslide area near village Nižná Myšľa. The surface was documented using a low-cost UAV to perform repeated measurements with a time span of about half a year and then evaluate the results. The first measurement was realized in autumn 2017, and its results are presented in this article. Further measurements will be made in the autumn of the 2018 year. From the aspect of the accuracy, the goal was to verify the error with which we can model the object by the photogrammetric measurement. The test results of pixel heights obtained by photogrammetric data processing indicate that low-cost UAV photogrammetry as a data acquisition method provides the precision of height determination near terrestrial laser scanning (PUKANSKÁ et al, 2014). However, the UAV use, it should be noted that their commercial deployment in practice is in the Slovak Republic regulated by relatively strict legislation. Performing commercial aviation operations related to aerial photography is subject to authorisation by several institutions and offices. This fact can be discouraged for many subjects who would like to take an active part in this progressive method of the collecting geodata. Although it is not natural for us to make forecast maps of geological hazards and risks, it is only a matter of time when it becomes a necessary. With progressive urbanisation and an increasing need for greater living comfort, structure designers are forced to cope with increasingly complex engineering and geological conditions in the assessment of land, underground, line, water, and other types of construction. The correct location of the building, with a thorough knowledge of the current state of the geological environment, but especially the assumption of geological processes in the future, with the emphasis on geobarriers, can be a means of saving the high financial costs of future remediation and, last but not least, increasing the safety of the population. The monitoring of flood risks using the UAV and the predictive map of geological hazards is, therefore, an ideal basis for urban planning of individual localities (LUCIEER et al, 2014). 62
Acknowledgement This work was supported by project SKHU/1601/4.1/187 and by the Scientific Grant Agency of the Slovak Republic (VEGA – MŠVVaŠ SR) through project. No. 1/0844/18. References ARCDATA PRAHA, Družicová data [on line]: http://download.arcdata.cz/doc/druzicova_data.pdf (access 15.08.2017). ARDI, N. D., IRYANTI, M., ASMORO, C. P., NURHAYATI, N., & AGUSTINE, E. 2018. Mapping landslide potential area using fault fracture density analysis on unmanned aerial vehicle (UAV) image. Paper presented at the IOP Conference Series: Earth and Environmental Science, 145(1). BLIŠŤANOVÁ, M. 2017. Hodnotenie bezpečnostných rizík prírodného charakteru na Slovensku. Košická bezpečnostná revue, 1: 1-17. MESÁROŠ, M., ĎURICA, T., LOŠINCZI, P., BLIŠŤANOVÁ, M. 2015. Possibilities for protection of critical infrastructure prior to geohazards. International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM. CRUDEN, D. M., VARNES, D. J. 1996. Landslide types and processes, In: K.A. Turner, R.L. Schuster (Eds.), Landslides: Investigation and Mitigation, Special Report 247, Transportation Research Board, Washington, p. 36-75. ČABALOVÁ, D., BALIAK, F., KOPECKÝ, M. 1999. Geológia. Bratislava: STU,. p. 142-143. GARIANO, S. L., GUZZETTI, F. 2016. Landslides in a changing climate. Earth-Science Reviews, 162: 227-252. KRŠÁK, B., BLIŠŤAN, P., PAULIKOVÁ, A., PUŠKÁROVÁ, P., KOVANIČ, Ľ., PALKOVÁ, J., ZELIZŇAKOVÁ, V. 2016. Use of lowcost UAV photogrammetry to analyze the accuracy of a digital elevation model in a case study . Measurement, 91: 276-287. KYŠEĽA, K., BLIŠŤAN, P., KOVANIČ, Ľ. 2013. Využitie vybraných geodetických metód pre zameranie povrchových banských prevádzok s cieľom tvorby ich 3D modelov. In: Fórum mladých geoinformatikov 2013: recenzovaný zborník príspevkov. 2- 3 May 2013, Zvolen. - Zvolen: Technická univerzita, p. 1-10. LUCIEER, A., JONG, S.M.D., TURNER, D. 2014. Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography. Prog. Phys. Geogr., 38(1): 97116. NEMČOK, A. 1982. Zosuvy v slovenských Karpatoch. Bratislava: VEDA SAV. NEX, F., REMONDINO, R. 2013. UAV for 3D mapping applications: A review. Applied Geomatics, 6(1): 1-15. NIETHAMMER, U., JAMES, M. R., ROTHMUND, S., TRAVELLETTI, J., JOSWIG, M., 2012. UAV-based remote sensing of the Super-Sauze landslide: Evaluation and results. Engineering Geology, 128: 2-11. PAVELKA, K. 2009. Fotogrammetrie 1, 1st ed.; Česká technika, Praha. PUKANSKÁ, K., BARTOŠ, K., SABOVÁ, J. 2014. Comparison of survey results of the surface quarry spišské tomášovce by the use of photogrammetry and terrestrial laser scanning. Inzynieria Mineralna, 15(1): 47-54. REMONDINO, F., BARAZZETTI, L., NEX, F., SCAIONI, M., SARAZZI, D. 2011. UAV photogrammetry for mapping and 3D modeling–current status and future perspectives. In: H. Eisenbeiss, M. Kunz, H. Ingensand (Eds.). Proceedings of the International Conference on Unmanned Aerial Vehicle in Geomatics (UAV-g) Zurich, Switzerland. ROSSI, G., TANTERI, L., TOFANI, V., VANNOCCI, P., MORETTI, S., & CASAGLI, N. 2018. Multitemporal UAV surveys for landslide mapping and characterization. Landslides, 15(5): 1045-1052. STUMPF, A., MALET, J. P., KERLE, N., NIETHAMMER, U., ROTHMUND, S. 2013. Image-based mapping of surface fissures for the investigation of landslide dynamics. Geomorphology, 186: 12-27. TOMETZ, L., BLIŠŤAN, P., HARABINOVÁ, S., LEŠŠO, J., NYÁRHIDY, J., TUROVSKÝ, F. 2010. Nižná Myšľa – havarijný zosuv, inžinierskogeologický prieskum. Manuskript GEOTON s.r.o., Košice, p. 59. URBAN, R., ŠTRONER, M., BALEK, J. 2017. Realization of geodetic network for monitoring of landslide area near Třebenice. In: 17th International Multidisciplinary Scientific Geoconference SGEM 2017 Geodesy and Mine Surveying. Sofia: STEF92 Technology Ltd., p. 531-538. WWW.1: Zosuvy a iné svahové deformácie [on line]: http://www.minzp.sk/sekcie/temyoblasti/geologia/zosuvy-ine-svahove-deformacie.html (access 15.06.2018). ZÁRUBA, Q., MENCL, V. 1987. Sesuvy a zabezpečování svahú. Praha: Academia.
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RESEARCH OF THE MORPHOLOGY OF RIVER DNIESTER USING REMOTE SENSING AND CARTOGRAPHIC DATA Prof. Khrystyna Burshtynska, Ph.D.
Department of Photogrammetry and Geoinformatics Lviv National Polytechnic University Lviv, Ukraine e-mail:
[email protected]
Volodymyr Shevchuk, Ph.D.
Department of Photogrammetry and Geoinformatics Lviv National Polytechnic University Lviv, Ukraine e-mail:
[email protected]
Andriy Babushka, Ph.D.
Department of Photogrammetry and Geoinformatics Lviv National Polytechnic University Lviv, Ukraine e-mail:
[email protected] – contact person
Sofija Tretyak, M.Sc.
Department of Photogrammetry and Geoinformatics Lviv National Polytechnic University Lviv, Ukraine e-mail:
[email protected]
Maksym Halochkin, M.Sc.
Department of Photogrammetry and Geoinformatics Lviv National Polytechnic University Lviv, Ukraine e-mail:
[email protected] Abstract The aim of the work is to research the method of studying horizontal displacements in the channel of the Dniester (the second largest river in Ukraine) from river source to canyon using data of different periods – topographic maps, space images and special maps. The main factors of displacements and meandering of the Dniester riverbed were considered. The boundaries of the Precarpathian bend and VolhynianPodolian upland are shown as their structures influence the formation of the character of the Dniester riverbed. The monitoring was carried out on the site with a total length of about 400 km for over a 100years period. Data for conducting research includes topographic maps (1890, 1928, 1986) and space images obtained from satellites Landsat 5 (1979), Landsat 7 (2000) and Sentinel (2017), as well as special ground maps and maps of Quaternary deposits. The general workflow of data processing is presented. Depending on the type and the displacement of the riverbed, the research site is divided into 5 sections. Visualization and studies of changes in the Dniester riverbed were carried out with ArcGIS 10.1 software. The sinuosity coefficients of the Dniester river channel were determined, and measurements of the maximum displacements of the river on its five selected fragments of the channel were performed. The maximum displacement during the 100-year period is 950 meters. For the analysis of the influence of relief, the digitized river channel was imposed on DEM. It was established that the main effective method for forecasting channel changes is a hydrological and morphological analysis based on different topographical data, and information obtained on the basis of remote sensing data, which involves the combination and analysis of modern and past configurations of the riverbed. Key words: monitoring, channel processes, riverbed displacement, meandering, alluvial and deluvial sediments
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Introduction It is commonly known that with time riverbeds change their plane position and elevation. Depending on the type of river, it can move by a measure, which significantly exceeds the width of the riverbed, new straits and distributaries can appear, or a riverbed can change its configuration in 50-100 years. Therefore, results of monitoring of riverbed deformation processes need to be taken into account while solving a series of tasks related to riverbed processes, and specifically: • developing and building hydraulic engineering facilities; • designing power transmission grid across rivers; • laying natural gas transmission pipeline; • determining flood hazard zones and the scale of destruction after flash floods or seasonal floods; • establishing boundaries of land conservation areas; • managing recreation activities; • studying the condition of frontier lands and establishing the border along the midstream of rivers. Expenses for examining the riverbed and geological environment make a few percent of expenses for construction of a facility, but these engineering and geological examinations often determine successful use of the planned facility. Ignoring foreseeable displacements of riverbeds often results in unpredictable consequences. Thus, for example, a shift in the riverbed of the river can cause emergencies at submerged crossings of pipelines. Bank caving causes breakage of pipeline, which in its turn causes a massive explosion and fire, breakage of the pipeline causes oil spill and environmental disruptions. Significant losses to the economy of the country can be caused by bridge scouring, power transmission supports scouring, etc. Protection of frontier land and prevention of interstate contradictions can be mentioned as one of special tasks related to riverbed processes. Among major works on topics, related to riverbed processes, the following works can be mentioned (GRENFELL et al., 2014; HOOKE, 1984, 2006; BURSHTYNSKA et al., 2015; ZOLEZZI et al., 2012). Broad-scale researches of different nature on riverbed evolution are being conducted abroad. Hence, the impact of topography, geology, climate, vegetation and land use onto the space and time of riverbed shifting processes in the North West Pacific is pointed out in (BUFFINGTON, 2014). The authors study the impact of types of riverbeds on physical models that can be used for forecasting changes in the riverbed morphology. The connection between the topography of ground surface and hydraulic characteristics of the riverbed, and specifically the impact of pre-channel and subsurface water flows, as well as the study of morphology and riverbed structure of the Amazon river is laid out in the following works (BEIGHLEY et al., 2009; PIRMEZ et al., 1995). A survey on the impact of bank erosion and methods of its assessment is given in (WATSON, BASHER, 2005-2006). Scientists from Great Britain (FRIEND, SINHA, 1993) studied the interweaving and sinuosity of single-distributary and multi-distributary rivers with determining interweaving and sinuosity coefficients. It has been found that multi-distributary rivers are more sinuous than single-distributary ones. The study of issues of riverbed processes in the rivers of Western Australia is given in report (JANICKE, 2000). It has revealed the impact of anthropogenic factors onto the transportation of deposits and silting. Attention has been drawn to the solution of the issue of river degradation and riverbed processes, which is the responsibility of a special Water and Rivers Commission. Research (GUNERALP et al., 2011) analyses migration of the Brazos River stream in Texas in 19102010. It uses topographic maps and satellite images from different years. It analyses not only the riverbed migration, but also meanders, tilting and form of the riverbed of this river. It has determined migration zones of the riverbed in the future, which is an analytical instrument for determining areas, which can be at risk of catastrophes and floods. In Article (LEGG, OLSON, 2014) rivers of the Western Washington serve as an object of research, or more specifically – migration of their riverbeds. It is pointed out that riverbeds migrate along floodplains due to processes of riverbed broadening, alteration of bends and their frequency. In order to assess the interrelation between the change of climate, processes of relief formation, percentage of forest lands and the modern dynamics of riverbeds, stratigraphic, geo-morphological and paleo-environmental data from high-altitude watersheds in the Great Basin of Central Nevada have been collected (MILLER et al., 2001). They indicate that the transition to drier, warmer climate conditions 13002500 years ago caused a complex set of geo-morphological reactions. The initial reaction was a massive upland erosion with simultaneous gravitation of side valley alluvial deposits. It was followed by stabilization of deposits because fine-grain deposits were formed out of rocks, and specifically – alteration
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of deposit processes and the flow took place. It was pointed out that modern dynamics of riverbeds and the associated riverbank ecosystems have a significant impact on the shape of forestland. From literature sources (BURSHTYNSKA et al., 2016, MORISAWA, 1985, RUD’KO, PETRYSHYN, 2014) it is known that every river has its own properties depending on natural and anthropogenic factors. Factors affecting deformation processes of riverbeds are divided into two groups: natural and anthropogenic, which in turn are divided into direct and indirect factors. Classification of the main factors influence on riverbed displacements are given in Table 1. Table1. Classification of main factors influence on riverbed displacements. Riverbed processes Natural
Anthropogenic
Direct
Indirect
Direct
Indirect
Landslides and bank erosion
Rainfall regime
Hydro-technical construction
Watershed destruction
Soil drifting
Erosion intensity at the watershed
Overregulation of the water flow
Deforestation in the basin
Surge of the river
Water-blocking capacity of the soil
Streambed and floodplain quarries
Mining for mineral resources at the watershed
Freeze-up and frozen soil
Vegetation at the watershed
Communications across rivers
Hydro-technical and amelioration measures at the watershed and floodplains
Vegetation in the river and on the floodplain
Landscape structure of the watershed
Amelioration works in the riverbed
Gravel and stone extraction
Water flow
Settlements along riverbanks
Sediment run-off Geological and morphological structure
Source: Own study based on the information from OBODOVSKY (2001).
Materials and methods The object of research is the second biggest river in Ukraine – the Dniester river from the headwaters to the canyon part (the city of Zalishchyky) (Fig.1). It is no coincidence that this river was picked up for research, because its flowing along the borderline of two geological structures – the Precarpathian bend and the Volhynian-Podolian upland, the structures of which affect the formation of the character of the riverbed. The length of the section under research makes 440 km. The stream gradient is 4,5 m/km at the upper reaches and up to 0,3 m/km at the lower reaches. The width of the riverbed is up to 10 - 15 meters at the upper reaches and up to 300 meters at the lower reaches. The average depth is from 0,5 to 1,0 m, maximum depth of the riverbed is 2,5-2,8 meters (Transkordonne…). The river is rain– fed and snow-fed. The freeze-up period is from the end of November to the middle of March. Spring floods and spring-fall flash floods are common for the river. The Dniester river has a very sinuous riverbed in certain sections of it with the most interesting meanders around the village of Kruzhyky.
Fig. 1. General view of the field of research. Source: Own work and map from bing.com.
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The Precarpathian bend is a young alpine area of Earth’s crust subsidence, which is located between the Carpathian Structure and the Volhynian-Podolian upland (KRAVCHUK, 1999). Figure 2 shows the boundaries of the Precarpathian bend and the Volhynian-Podolian upland, the structures of which affect the formation of the Dniester’s riverbed, as well as of its right-bank tributaries.
Legend: 1 - the edge of the Carpathians; 2 - the edge of Volhynian-Podolian upland; 3 – the Kovalivka-Smykovtsi line and its Carpathian continuation; 4 – accumulative terraces;
5 – low terrace level; 6 – high terracing level (Loyeva level); 7 – the highest level; 8 – some ancient directions of Precarpathian rivers.
Fig. 2. Precarpathian bend. Source: (KRAVCHUK, 1999).
Methodology of the research is based on the principles of hydrological and morphological analysis, which has been conducted using topographical maps and satellite images from various times. For monitoring displacements and meandering of the Dniester’s riverbed in the stretch between the headwaters area and the city of Zalishchyky with the length of 440 km the following has been used: • topographic maps in scale 1:100000 (Austrian period – 1890y., Polish period –1928y., the Soviet period – 1986y.); • satellite images Landsat 5 (1986y.), Landsat 7 (2000y.) and Sentinel 2 (2017y.); • soil map in scale 1:200000. The materials used in the studies are presented in Figure 3. The technological scheme of investigations is presented on Fig.4. Visualization and analysis of planar Dniester’s riverbed variations has been done using ArcGIS software. Horizontal displacements of the riverbed have been determined according to satellite images received from satellites Landsat5 (1986) Landsat7 (2000) та Sentinel2 (2017) and topographic maps. Spatial interval of images from the Landsat system makes 15 meters after the pansharpening; and 10 meters from the Sentinel2 systems channels. Georeferencing of topographic raster maps was done with use of 10 points coordinates of which determined from the kilometer grid. Austrian period map with absent kilometer grid was georeferenced using coordinates transformation of easily identifying points (bridges, road intersections, geodetic control points) on existing georeferenced maps. Polynomial of second order was chosen to achieve better accuracy which not exceeds 15 meters on the intrinsic convergence. Afterwards all georeferenced raster maps were transformed to WGS-84 coordinate system in which satellite images was given.
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Fig. 3. Materials of research. Source: Own study. Data retrieval Satellite images Topographic maps
Composite image creation
зззображень
Pansharpening procedure
Georeferencing Vectorization of river channels Analysis of the soil map Analysis of the displacement of the riverbed Fig. 4. Technological scheme of investigations. Source: Own study.
Results and discussion As it has been defined in reference books and geographical descriptions of the river (Transkordonne…), the properties of the riverbed give reasons to mark out three major sections: mountain, valley and river mouth ones. The conducted research showed an approximate approach to this division, and specifically to the valley section, the description of which does not take into account geological structures and the types of soil having the determining influence on the character of the riverbed. The task presumed the study of horizontal displacements of the Dniester River, determining sections of maximum displacements, analysis of various approaches to the assessment of the riverbed rigidity and calculation of rigidity coefficient considering displacements of the riverbed. One of the principal characteristics of the rivers is sinuosity coefficient Kl, which is determined from the correlation (Table 2): Kl=L’/L,
(1)
where: L’ is the length of the riverbed in the area; L is the length of the riverbed of between the extreme points measured in a straight line.
Table 2. Sinuosity coefficient of the research river and type of soil. Sections of research І
ІІ
ІІІ
IV
V
Sinuosity coefficient
1,29
1,33
1,5
1,31
2,39
Type of soil and rock
Outputs of country rock, small boulders, pebbles
Small pebbles, large gravel
Gravel, sand
Gravel, sand
Fine gravel
Source: Own study and information from OBODOVSKY (2001).
68
According to the character of horizontal displacements and morphological features, the stretch of the Dniester River under study has been divided into 5 sections: 1) mountain; 2) hill and valley; 3) wetland and valley; 4) valley; 5) canyon. The mountain section is predominantly straight with some sinuosity of 1,35 (Fig. 5a), and a Vshaped narrow valley; the steam gradient is – 4,45 m/km; displacements are minor, reaching 130 meters. In places where the tributaries flow into the river, the valley is broader, and displacements can reach 400 meters. The increase of meandering and the Kl coefficient to 1,33 is common for the transition from the mountain section to the valley one. An especially complex character of meandering is observed near the village of Kruzhyky, where opposite banks of the river differ in their height and the steepness (Fig. 5b). The analysis of the topographic map of this section testifies to major soil erosion, which is reflected in the formation of gullies, which with time and after consolidation of soil become covered with plants. The most unexpected stretch at the transition from the mountain and hill section of the riverbed to the valley one is the stretch, located in a broad wetland valley (Fig. 5c). The riverbed sinuosity, shown in the topographic map of 1886 is significant and the sinuosity coefficient reaches 1,97. In this map we can see a lot of dead arms of the river, which testifies to major meandering of the riverbed as compared to previous epochs, the riverbed displacements reach 950 meters. Taking into consideration the valley type of the locality, the angles of slopes gradient are 0,5°. A great number of submerged and partially submerged lands is typical for this territory. Thus, since the 30s of the past century, riverbed straightening and bank protection works have been conducted here. In the 60s-70s amelioration works were conducted along the Dniester river. Some channels got silted up. River bank protection got broken in some places. It is worthy a note that certain stretches of the riverbed tend to shift to the riverbed of 1886. In the fourth section the riverbed clearly depends on geomorphological properties of the locality: in places with a broad valley the meandering is significant and reaches 870 meters (Fig. 5d). The fifth section is the transition from the valley to the canyon section, which is not dependent on the sinuosity or stream gradient, but first of all on the types of rocks, forming the canyon (Fig. 5e). The space of the floodplain is not big and makes up to 370 meters. Riverbed displacements are also insignificant – 200-350 meters. As to the measure, which characterizes the riverbed stability, two approaches are described in special literature. According to the first approach, the riverbed stability index is determined at specific stretches of insignificant length, where the river has similar characteristics (ROSGEN, 2001, SIMON, KLIMETZ, 2008). It presumes taking into account major parameters, often detailed ones, determined through ground measurement (for instance - the depth of the river near two banks, or erosion, caused by bank caving, etc.) according to empirical criteria, which are then added to determine the riverbed rigidity (MAKKAVEEV, CHALOV, 1986). The second approach determines indices of stability according to the data of morphometric characteristics using mathematical relations. The table 3 gives main morphometric characteristics of the above five sections of the riverbed, and table 4 shows calculated riverbed stability indices. The study demonstrates significant discrepancy between the stability indices, which refers to sections I and V in particular. The sinuosity coefficient can be one of the stability indices only for sections with a significant width of the floodplain. For example, for the canyon section the sinuosity coefficient Кl=2,4, however the riverbed is stable because the stability factor are rocks forming the banks of the river. It is proposed to show the riverbed stability index as a correlation of the width of the floodplain to the width of the riverbed: K = В´/B,
(2)
where В´ is the width of the floodplain, determined based on the maps of quaternary deposits. Measurement of the characteristics of the channel for each of the sections was carried out at selected points in 3-4 km (in total at 120 points). Stability criteria: stable – 1–3, moderately stable – 4–10; non-stable – > 10. The proposed criterion is congruent with horizontal displacements of the riverbed determined for the period of 100 years.
69
b)
a)
c)
e)
d)
Fig. 5. Fragments of the riverbed in sections under the study: a- mountain, b – hill and valley; c-wetland and valley; d – valley; e - canyon. Source: Own study. Table 3. Main morphometric characteristics of the above five sections of the riverbed. Sections of research Main morphometric characteristics
І
ІІ
ІІІ
IV
V
Length l, km
38,2
36,1
71,1
157,5
137,4
Difference in altitude of river section ΔΗ, m/km
170
78
19
54
50
Stream gradient І, m/km
4,45
2,16
0,27
0,34
0,36
Average width of the river, В, m
23
28
25
100
180
Average depth of the river h, m
0,5
0,8
1,0
1,2
1,7
Average sediment diameter d, mm
50
10
1
1
2
Average width of the floodplain В´, m
210
500
1180
2010
380
Source: Own study and data from OBODOVSKY (2001).
70
Table 4. Calculated riverbed stability indices. Main reletions for determining riverbed stability index
Stability criteria of the riverbed, from not stable to stable
Sections of research І
ІІ
ІІІ
IV
V
1
L = d/І
2 –
(1)
where: E – a finite set of elements of the {𝑒𝑗 ; 𝑗 ∈ 𝐽} system, R – a finite set of {𝑅𝑖 ; 𝑖 ∈ 𝐼} correlations defined in set E, whereas: 𝐽 = {1,2,3, … J} – the set of indices of set E, whereas 𝐼 = {1,2,3, … I} – the set of indices of set R, DZ – the purpose of system operations. The E set describing the system composition meets the 𝐸 = {𝑒𝑗 ∶ 𝜉(𝑗, 𝑞), 𝑗 ∈ 𝐽, 𝑞 ∈ 𝑄𝑗 } requirements. The 𝜉(𝑗, 𝑞) value shall be construed as the following sentence formula: "The element number 𝑗 ∈ 𝐽 is characterized by feature number 𝑞 ∈ 𝑄𝑗 , where 𝑄𝑗 is the set of indices of the 𝐶 𝑗 set of elements number "j". The set of E elements of the automated control and monitoring system of the current level of information security may decomposed in the following manner: 𝐸 = 𝐸 𝑃𝑆 ∪ 𝐸 𝑃𝑃 ∪ 𝐸 𝐴𝑅 ∪ 𝐸 𝑂𝑇
(2)
where: 𝐸 𝑃𝑆 – the set of elements of the subsystem for controlling the security configuration properties, 𝐸 𝑃𝑃 – the set of elements of the subsystem for information processing, 𝐸 𝐴𝑅 – the set of elements of the subsystem for risk analysis, 𝐸 𝑂𝑇 – the set of elements that constitute both external and internal environment - i.e. environment of the information processing subsystem. Among the elements of the subsystem for controlling the security configuration properties, in the 𝐸 𝐴𝑅 risk analysis subsystem and 𝐸 𝑃𝑃 elements of information processing, it is possible to distinguish the following functional components: 𝑃𝑆 𝑃𝑆 𝑃𝑆 𝐸 𝑃𝑆 = 𝐸𝑃𝐷 ∪ 𝐸𝑃𝑅 ∪ 𝐸𝑂𝑇 𝐴𝑅 𝐴𝑅 𝐴𝑅 𝐴𝑅 𝐸 = 𝐸𝑃𝐷 ∪ 𝐸𝑃𝑅 ∪ 𝐸𝑂𝑇
214
𝑃𝑃 𝑃𝑃 𝑃𝑃 𝐸 𝑃𝑃 = 𝐸𝑃𝐷 ∪ 𝐸𝑃𝑅 ∪ 𝐸𝑂𝑇
where: 𝑃𝑆 𝐸𝑃𝐷 – the set of elements of the controlling subsystem, which constitute the decision-making subject, 𝑃𝑆 𝐸𝑃𝑅 – the set of elements of the controlling subsystem, which constitute its subject, 𝑃𝑆 𝐸𝑂𝑇 – the set of elements of the controlling subsystem, which constitute the environment of its subject and object, 𝐴𝑅 𝐸𝑃𝐷 – the set of elements of the risk analysis subsystem, which constitute its subject of operations, 𝐴𝑅 𝐸𝑃𝑅 – the set of elements of the risk analysis subsystem, which constitute its object, 𝐴𝑅 𝐸𝑂𝑇 – the set of elements of the risk analysis subsystem, which constitute the environment of its subject and object, 𝑃𝑃 𝐸𝑃𝐷 – the set of elements of the information processing subsystem, which constitute its subject of processing, 𝑃𝑃 𝐸𝑃𝑅 – the set of elements of the information processing subsystem, which constitute its subject, 𝑃𝑃 𝐸𝑂𝑇 – the set of elements of the information processing subsystem, which constitute the environment of its subject and object. Set R of correlations defined in set E may be decomposed in the following manner: 𝑅 = 𝑅𝑃𝑆 ∪ 𝑅𝑃𝑃 ∪ 𝑅 𝐴𝑅 ∪ 𝑅 𝑆𝑃
(3)
where: 𝑅𝑃𝑆 ⊂ 𝐸 𝑃𝑆 × 𝐸 𝑃𝑆 – the set of correlations between elements of the security configuration control subsystem, ensuring specific operation of such subsystem, 𝑅𝑃𝑃 ⊂ 𝐸 𝑃𝑃 × 𝐸 𝑃𝑃 – the set of correlations between elements of the information processing subsystem, ensuring specific operations of such subsystem, 𝑅 𝐴𝑅 ⊂ 𝐸 𝐴𝑅 × 𝐸 𝐴𝑅 – the set of correlations between elements of the risk analysis subsystem, ensuring specific operations of such subsystem, 𝑅 𝑆𝑃 ⊂ 𝐸 𝑃𝑆 × 𝐸 𝑃𝑃 – the set of correlations between elements of the control system and information processing subsystem, 𝑅 𝑆𝑅 ⊂ 𝐸 𝑃𝑆 × 𝐸 𝐴𝑅 – the set of correlations between elements of the control system and risk analysis subsystem. 1.
The system operations may be defined in the following way for the analyzed category of the system: with respect to the control of the utility properties of the security configuration, as an ordered pair: 𝐷𝑍 𝐾𝐵 =,
(4)
where: ∝𝐾𝐵 – the purpose of the control subsystem, 𝑍 𝐾𝐵 – the set of tasks (controls) allowing to achieve the ∝𝐾𝐵 goal, 2.
with respect to the information (information resources) processing subsystem, as an ordered pair: 𝐷𝑍 𝑝𝑝 =,
(5)
where: ∝𝑃𝑃 – the purpose of operations of the information processing subsystem, 𝑍 𝑃𝑃 – the set of information processing operations allowing to achieve the ∝𝑃𝑃 goal, 3.
with respect to the risk analysis subsystem, as an ordered pair: 𝐷𝑍 𝐴𝑅 =, where: ∝𝐴𝑅 – the purpose of operations of the risk analysis subsystem, 𝑍 𝐴𝑅 – the set of tasks allowing to achieve the ∝𝐴𝑅 goal.
215
(6)
It is assumed that the purpose of operations of the subsystem for controlling the security configuration is to maintain the required level of the information (information resources) security through appropriate adaptation of the means of information protection to the scale of risk of losing the information security attributes. Such goal may be achieved by controlling the utility properties of the information resources in the information processing subsystem. The aforementioned resources refer to technical, organizational or human resources. It is assumed that the purpose of operations of the risk analysis subsystem is to decrease negative impact of risk on the functioning of the information processing subsystem and undertake appropriate actions aimed at combating and mitigating the risk. It is also assumed that risk identification as well as qualitative and quantitative risk assessment and monitoring constitute part of the 𝑍 𝐴𝑅 set. The risk analysis comes down to identification of the most vulnerable assets in the organization (places where the probability that any of such risks materializes is relatively high), which allows to determine which assets should be dealt with in the first place and for which assets some security measures (technical, organizational or HR) should be implemented. It is assumed that the purpose of operations of the information processing subsystem is to manage the processing of the information resources (sets of data) so as to ensure continuity of the security attributes assigned thereto, such as: confidentiality, integrity, availability, non-repudiation or accountability. Such goal may be achieved by mitigating the risk of infringement of rights and freedoms as well as business goals or consent given to process the data. The specificity of the information processing subsystem is the fact that all physical actions are in the form of operations on the information or data, whose source is the environment of such subsystem. It is assumed that the following shall be included in the 𝑍 𝑃𝑃 set: 1. collecting, gathering, storing, using, making available, passing and removing according to the needs of the entity. The tasks are implemented in a traditional, automated or automatic manner using IT equipment, 2. information processing tasks in compliance with the adopted technological principles. Furthermore, it is assumed that: 1. part of the information processing operations may be executed using a computer system, whereas the other part requires approval of the processing entity, 2. part of the information processing operations may be executed automatically by the entity of the information processing subsystem. Subject, object and purpose of the system operations In terms of controlling the current level of the information security, the operator shall be an element of the automated system for making steering decisions, e.g. automated security control system or data administrator, hereinafter referred to as the decision-making entity. In such case, the subject shall be the set of such 𝑒𝑗 ∈ 𝐸 elements, whose desired status may be determined by the decision-making entity. Therefore, the following symbols shall be introduced: SF – the set of ordered pairs: 𝑠𝑓𝑝 =< 𝑂𝑝 , 𝐼𝑇𝑝 > ∈ × 2𝐼𝑇 , hereinafter referred to as positions; where: – a group of officers appointed at the stage of designing the system, who shall participate in the information processing process, hereinafter referred to as the processing entity, IT – the set of IT devices, which constitute the workplace equipment of the processing entity, ̂ – the set of permissible steering values, thanks to which the decision-making entity may determine 𝑈 current utility values of the positions of the processing entity, 𝑉𝑢 – the set of < 𝑝, 𝑞 >∈ 𝑃̂ × 𝑄̂ pairs corresponding to such steering values, where: 𝑃̂ – the set of numbers of the selected positions of the processing entity, 𝑄̂ – the set of numbers of characteristic features of the positions; 𝑆̂ – the vector of the status of special conditions of the position, whose coordinates define the status of particular position. The 𝑠𝑝 status, where p ∈ 𝑃̂ , for the pth position shall be deemed to mean the vector of characteristics describing in detail the current utility properties: 𝑞
𝑞
𝑠𝑝 = < 𝑎𝑝 ∈ 𝐴𝑝 ∶ 𝑝 ∈ 𝑃̂, 𝑞 ∈ 𝑄̂ > where:
216
(7)
𝑞
𝑎𝑝 – coordinates of the vector of status of the pth position, expressing individual features, 𝑞 𝐴𝑝 – the set of permissible implementation of the qth feature of the pth position. The impact of such control on the position and hence their characteristics may be noted in the following manner: 𝑞
𝑞
⋀∈𝑃̂×𝑄̂ 𝑎𝑝 = 𝑎𝑝 [𝑢(𝑡)], 𝑢 ∈ 𝑈,
(8)
As a result, the set of controlled positions may be defined as follows: ̂ = {𝑠𝑓𝑝 ∈ SF ∶ ⋁𝑞∈𝑄̂[ < 𝑝, 𝑞 >∈ 𝑉𝑢 ], 𝑝 ∈ 𝑃̂ }. 𝑆𝐹 The ∝ 𝑆𝑃 goal of the operations of the information processing subsystem is determined in the set of the controlled positions. In terms of the information processing process, the processing entity in the automated control and ̂ set of positions, whereas the monitoring system of the current level of information security shall be the 𝑆𝐹 𝑂 subject of operations shall be the set of such 𝑒𝑗 ∈ 𝐸 elements, where the purpose of operations of the information processing subsystem is determined. Some bites of information (information resources) collected or processed by the information processing subsystem may be elements of the 𝐸 𝑂 set. Such bites of information define actual information objects in the organization (e.g. data of natural persons, descriptions of basic assets in the organizations, descriptions of supporting assets, etc.). They are formed by the information processing subsystem according to certain rules and are subject to further processing. Each bite of information, hereinafter referred to as the information object (information resource) is marked with p ∈ 𝑃𝑂 number and described by the set of 𝐶𝑝𝑂 feature names. If all different sets of 𝐶𝑝𝑂 features used to describe individual information resources are numbered with 𝑏 = ̅̅̅̅̅ 1, 𝐵 variable (to be called the type of the information resource or object), then, two objects shall be of the same type (e.g. "b") when described by identical sets of features. The sets of 𝑄𝑝𝑂 numbers of features describing the 𝑝 ∈ 𝑃𝑂 object and the sets of 𝐶𝑝𝑂 feature names corresponding thereto may not be empty for each 𝑝 ∈ 𝑃𝑂 , where 𝑃𝑂 is the set of numbers of the selected information resources. It is assumed that for each 𝑞 ∈ 𝑄𝑂 feature, the 𝐴𝑂𝑞 set of possible implementation of the 𝑎𝑞 feature shall be defined. Therefore, the following symbols shall be introduced: D – the set of steering decisions, hereinafter referred to as orders, used by the Processing Entity (officers) from its positions to initiate the data processing operations and hence influence the current properties of the information resources (also including the properties of the security attributes assigned thereto); 𝑉𝐷 – the set of < 𝑝, 𝑞 >∈ 𝑃 𝑍 × 𝑄 𝑍 pairs corresponding to such steering values, where: 𝑃 𝑍 – the set of numbers of the selected information resources, 𝑄 𝑍 – the set of numbers of the selected features of the information resources, 𝑎(𝑡) – the vector of status of the selected information resources, whose coordinates determine the processing statuses of particular objects at moment t, also including in terms of security (e.g. loss or continuity of confidentiality, integrity, non-repudiation, availability and accountability). The 𝑎𝑝 (𝑡) status, 𝑝 ∈ 𝑃𝑂 of the pth object shall be deemed to mean the vector of features describing in detail its current quality - properties related to utility, security, reliability, etc.: 𝑝
𝑞
𝑎𝑝 (𝑡) =< 𝑎𝑞 (𝑡) ∈ 𝐴̈𝑝 : 𝑝 ∈ 𝑃 𝑍 , 𝑞 ∈ 𝑄 𝑍 >
(9)
where: 𝑝 𝑎𝑞 (𝑡) – coordinates of the vector of status of the pth object, expressing individual features, 𝑞 𝐴̈𝑝 – the set of permissible implementation of the qth feature of the pth object, 𝑄 𝑍 – the set of numbers of the selected features of the object. The impact of decisions made by the processing entity on the current security status, at moment t, may be noted in the following manner: 𝑞
𝑞
⋀∈𝑃𝑍×𝑄𝑍 𝑎𝑝 (𝑡) = 𝑎𝑝 [𝑑(𝑡)], 𝑑 ∈ 𝐷.
217
(10)
As a result, the set of resources, whose current status (and hence current level of security) may be determined by officers, may be defined as follows: 𝑂𝐵 = 𝑍𝐼 = {𝑧𝑖𝑝 ∈ 𝐸 𝑂 : ⋁𝑞∈𝑄𝑍[< 𝑝, 𝑞 >∈ 𝑉𝐷 ], 𝑝 ∈ 𝑃 𝑍 }.
(11)
In terms of possibilities of controlling current properties of the automated control and monitoring system of the current level of information security and processing information therein, each position may be described in the following extended manner: ̂𝑝 =< 𝑛𝑧𝑝 , 𝑅𝑂𝑃𝑝 , 𝑅𝑍𝐼𝑝 , Ś𝐵𝑝 , 𝑍𝐿𝑝 > 𝑠𝑓
(12)
where: 𝑛𝑧𝑝 – the name of an activated human resource of the pth position (e.g. code of the information processing entity), 𝑅𝑂𝑃𝑝 – the set (register) of the information processing operations assigned to the p th position (a list of processing operations that may be performed at the p th position), 𝑅𝑍𝐼𝑝 – the set (register) of the data sets assigned to the pth position (a list of information resources owned by the person from the pth position), Ś𝐵𝑝 – the set of security measures of technical and organizational nature, which may be activates in the information processing system from the pth position, 𝑍𝐿𝑝 – the set of steering decisions (orders) assigned to the p th position, used by the processing entity to initiate processing from the 𝑅𝑂𝑃𝑝 set. The goal of operations of the automated control and monitoring system in terms of its purpose is considered equivalent of the goal of the information processing subsystem. It may be defined by specifying the desired security statuses of the established group of information resources. Therefore, the following symbols shall be introduced: 𝑃̇ (𝑡) – the set of numbers of the information resources collected in the information processing subsystem by moment t, which require further safe processing, 𝑝 [𝑡0 , ̇ 𝑇̇ 𝑝 ] – the permissible time framework, during which the object number 𝑝 ∈ 𝑃̇ (𝑡) should retain the assigned security attributes - i.e. the required level of security, 𝑝 𝑊̇𝑝̇ – the desired security status of the p th information object obtained within the [𝑡0 , ̇ 𝑇̇ 𝑝 ] time framework, where: 𝑝 𝑡0 , – the time of collecting (registering) the pth object in the information processing subsystem, 𝑇̇ 𝑝 – the time of deregistering (removing) the pth object in the information processing subsystem, 𝑃𝑃𝐼 𝑄 (𝑤) – the set of numbers of the information object features, where the 𝑤 ∈ 𝑊̇𝑝̇ property is defined. To determine whether the information resource number 𝑝 ∈ 𝑃̇ (𝑡) has the "w" property, it is neces𝑞 𝑞 sary to define the ∝𝑝 (𝑤) ⊂ 𝐴̇𝑝 subsets of implemented features, for each 𝑞 ∈ 𝑄𝑃𝑃𝐼 (𝑤) feature. If the imple𝑝 𝑝 𝑞 mentation of the 𝑎𝑞 (𝑡) features of the pth object at the time 𝑡 ∈ [𝑡0̇ , 𝑇̇ 𝑝 ] belongs to such ∝𝑝 (𝑤) subsets, it is possible to state that the object number 𝑝 ∈ 𝑃̇ (𝑡) has the "w" property. 𝑞 𝑞 When assuming obviousness of the sets of the 𝑄̇𝑃 features, on whose values the ∝𝑝 (𝑤) ≡ ∝̇𝑝 , 𝑞 ∈ 𝑄̇𝑃 subsets are determined, for each 𝑝 ∈ 𝑃𝑃𝑃𝐼 object, the purpose of the automated control and monitoring system may be defined in the following manner: 𝑞 ∝ 𝑍𝑆𝐾𝑖𝑆𝐵𝑃𝐵𝐼 ≡ ∝𝑃𝑃𝐼 { ∝̇𝑝 ∶ < 𝑝, 𝑞 >∈ 𝑉𝐷 , 𝑝 ∈ 𝑃̇ (𝑡), 𝑞 ∈ 𝑄𝑃𝑃𝐼 }.
(13)
In terms of a possibility of achieving the goal of the automated control and monitoring system, every 𝑧𝑝 ∈ 𝑃̇ (𝑡) information resource, processed under the information processing subsystem, may be described in the following manner: ̇ 𝑏 ), 𝑅𝑏 > 𝑧𝑝 = < 𝑏𝑝 , 𝑂𝑝𝑏 , 𝑤𝑝𝑏 , 𝑄 (𝑤𝑝𝑏 ), ∝̇ (𝑤 𝑝 𝑝 where: 𝑏𝑝 – the type of the pth information resource, 𝑂𝑝𝑏 – the officer being the owner of the pth information resource of b type,
218
(14)
𝑤𝑝𝑏 , – the property (security level) of the pth information resource of b type, 𝑞 𝑄 (𝑤̇ 𝑏 ) – the set of numbers of properties, where the ∝ (𝑤 𝑏 ) subsets are defined, 𝑝
𝑝
𝑝
∝̇ (𝑤𝑝𝑏 ) – the set of the desired security statuses of the pth object of b type, 𝑅𝑝𝑏 – the set of correlations between 𝑏𝑝 and ∝̇ (𝑤𝑝𝑏 ). System model for controlling the current level of information security An ordered five was adopted as the system model for controlling the current level of information security: < 𝑆𝐹, 𝑈, 𝐾𝐵, 𝐹𝑅, 𝑄 >,
(15)
where: 𝑆𝐹 – the set of positions of persons processing the data, 𝑈 – the set of numbers of the types of emergency situations (the set of numbers of the lost security levels under the ISO), selected on the basis of the analysis of effects that such emergency situations may cause, 𝐾𝐵 – the family of permissible security configurations, 𝐹𝑅 – the general reconfiguration function, 𝑄 – the general reconfiguration function. Any failure shall be deemed to mean an event that occurred at time 𝑡𝑖 due to the difference between the desired property of the security configuration and its current security configuration. It is in line with the following condition: 𝐾𝐵𝑊𝑌 (𝑡𝑖 ) ⊃ 𝐾𝐵𝑀𝑂 (𝑡𝑖 ),
(16)
where: 𝐾𝐵𝑊𝑌 (𝑡𝑖 ) = ⋃𝑖: 𝑧𝑖∈ 𝑂𝐵𝑊𝑌 (𝑡𝑖) 𝐾𝐵𝑔 – the desired security configuration, which needs to be initiated to ensure the required level of security of the n information resources, which belong to the 𝑧𝑖 ∈ 𝑂𝐵𝑊𝑌 (𝑡𝑖 ) set; it may be analyzed as a multitude of security configurations for the 𝑧𝑖 ∈ 𝑂𝐵 𝑊𝑌 (𝑡𝑖 ) information resources, whereas: 𝐾𝐵𝑔 = 〈𝑧𝑔 , 𝑂𝑔 , 𝑀𝐵𝑔 〉, where: 𝑧𝑔 – the information resource protected by the gth security configuration, 𝑂𝑔 – the subset of human resources, which may be used to ensure the maintenance of the security attributes assigned to the 𝑧𝑔 information resources, 𝑀𝐵𝑔 – the set of security mechanisms creating the gth security configuration, KB MO (t i ) = ⋃i: zi∈ OBMO (ti ) KBg . – the security configuration, which may be constructed at time t i , based on technical or organizational security mechanism in currently proper condition; 𝑂𝐵𝑊𝑌 (𝑡𝑖 ) – the set of information resources, with respect to which, as of time 𝑡𝑖 , the required security level may not be maintained, 𝑂𝐵𝑀𝑂 (𝑡𝑖 ) ∈ ΘΒ(𝑡) – the set of information resources, with respect to which, as of time 𝑡𝑖 , it is possible to maintain the required level of security, based on the currently initiated security configurations; i.e. if at time 𝑡𝑖 it is necessary to protect the information resource newly introduced to the ISO, the current required level of security is lost, ΘΒ(𝑡) – the set of sets which may be created on the OB(t) set. The following notation of any security configuration shall be introduced: 𝐾𝐵𝑘𝑙 = 〈𝑂𝐵𝑘𝑙 , 𝑂𝑘 , 𝑀𝐵𝑙 〉
(17)
where: 𝑂𝐵𝑘𝑙 – the set of information resources of the information system in the organization subject to protection by the klth security configuration, 𝑘 𝑂 – the set of officers responsible for ensuring security of the information resources, which belong to the 𝑂𝐵𝑘𝑙 set, 𝑙 𝑀𝐵 – the set of security mechanisms of technical or organizational nature, which created the kl th security configuration.
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The knowledge of the 𝐾𝐵𝑘𝑙 security configurations makes it possible to assign to each 𝑂𝐵𝑘𝑙 , set, with the predefined 𝑀𝐵𝑙 , the 𝑂𝑘 set of security mechanism (organizational and technical security measures) corresponding thereto. The 𝐾𝐵𝑘𝑙 security configuration may be implemented only when it is possible to assign such 𝑧𝑏𝑖ó𝑟 𝑂𝑘 , to the 𝑂𝐵𝑘𝑙 set, with the predefined elements of the 𝑀𝐵𝑙 set, ensuring the maintenance of the required level of security of the set of 𝑂𝐵𝑘𝑙 information resources. Therefore, it may be stated that as a consequence of the above, the 𝑂𝐵 𝑘𝑙 set, with the predefined 𝑙 𝑀𝐵 set, remains in correlations with the 𝑂𝐵𝑘𝑙 set, i.e. 𝑂𝐵𝑘𝑙 𝐾𝐵𝑘𝑙 𝑂𝑘 . Therefore, it is possible to analyze the security configuration (17) as an analogous to the terminal system, based on which the information resources from the set 𝑂𝐵𝑘𝑙 constitutes the input data, whereas the elements of the set 𝑂𝑘 - the output data. Space for potential emergency situations creates creates the Cartesian product 𝐴 = 2𝑂𝐵 × 2𝑂 × 𝑀𝐵 2 . The 𝑎𝑛𝑚𝑠 =< 𝑂𝐵𝑛 , 𝑂𝑚 , 𝑀𝐵𝑠 >∈ 𝐴 element determines the type of an emergency situation. Let us assume that for each type of the emergency situation, there is function value 𝜒(𝑛𝑚𝑠) = 𝑢 defining the number of the emergency situation. It is assumed that the decision-making entity is equipped with visualization subsystem, security control subsystem and control and diagnostic complex, which may identify all type of emergency situations (loss of security). The 𝑎 ∈ 𝐴 type emergency situation, number u ∈ 𝑈 shall be deemed to mean 𝑂𝐵𝑛 , 𝑂𝑚 , 𝑀𝐵𝑠 sets that remain after the emergency situation number u ∈ 𝑈 occurs. The set of the permissible security configurations, upon the loss of security, shall be defined on the basis of the knowledge of: 𝑂𝐵𝑝 – a set of information resources, with respect to which the required security level shall be maintained, 𝑂𝑝 – a group of human resources (officers) available after the occurrence of the emergency situation, number u ∈ 𝑈, 𝑀𝐵𝑝 ∈ ΜΡ – a set of implementable security configurations on the basis of sets of efficient technical or organizational security measures, which remain after the loss of security event, number u ∈ 𝑈, according to the following formula:
𝑢 𝐾𝐵𝑑𝑜𝑝
{𝐾𝐵𝑘𝑙 = 〈𝑂𝐵𝑘𝑙 , 𝑂𝑘 , 𝑀𝐵𝑙 〉 ∈ 𝛩𝛣𝑝 × Θ𝑝 × 𝛭𝛲𝑝 ∶ ={ 𝑂𝐵 𝑘𝑙 ⊃ 𝑂𝐵𝑝 }, 𝑗𝑒ż𝑒𝑙𝑖 ⋁〈𝑘,𝑙〉 ∈ 𝐾𝑢×𝐿𝑢 (𝑂𝐵𝑘𝑙 ⊇ 𝑂𝐵𝑝 ) . 𝑤 𝑝𝑟𝑧𝑒𝑐𝑖𝑤𝑛𝑦𝑐ℎ 𝑝𝑟𝑧𝑦𝑝𝑎𝑑𝑘𝑎𝑐ℎ − 𝑧𝑏𝑖ó𝑟 𝑝𝑢𝑠𝑡𝑦.
(18)
𝑢 The above means that the 𝐾𝐵𝑑𝑜𝑝 set of permissible security configurations, shall include - upon loss of the required level of security of the information resources under the ISO - all security configurations, constructed for different variants of human resources as well as the set of technical or organizational security measures, which remain after the occurrence of the emergency situation, ensuring the required level of security with respect to the current set of the 𝑂𝐵 (𝑡) ∈ ΘΒ(𝑡) information resource. Each security con𝑢 figuration from the set 𝐾𝐵𝑑𝑜𝑝 guarantees maintenance of the acceptable security level of the information 𝑘𝑙 resources from the set 𝑂𝐵 . The representation of radio waves is determined at the stage of designing the control system for the current level of security or at the stage of determining the security system to ensure accomplishment of the desired purpose of activities of the processing entity and the information processing subsystem during their exploration, despite the occurrence of the emergency situation. After the occurrence of the emergency situation – loss of the required level of security, it is essential to generate permissible or optimum security configuration to be able to efficiently continue the process of safe information processing under the ISO (KIEDROWICZ, 2017; KIEDROWICZ, STANIK, 2017). The optimum security configuration is generated among the set of the permissible solutions on the basis of the detailed Q reconfiguration function, which - from the point of view of its essence - constitutes a criterial function.
Model of subsystem for controlling the level of security of the information resources – example Formal description The automated control and monitoring system of the current level of information security in a hypothetical organization is the subject of the considerations herein. The officer performing the duties of IOD2
IOD – Inspector for the Protection of Personal Data, i.e. former ABI. ABI – Information Security Administrator, i.e. ABI, a natural person appointed by the personal data administrator (ADO), responsible for ensuring compliance with the regulations on personal data protection. 2
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or ASI3 shall be also responsible for controlling the level of security. The position of such officer shall be equipped with the following technical or organizational resources: • data visualization means describing the current level of security of the informations resources processed under the ISO, e.g. the system of automated security control ISO, • IT means used by the IOD to assign work (steering decisions, instructions, etc.) to determine the current levels of security of the information resources by initiating appropriate security configurations from the set of permissible configurations determined at the stage of design. The set of permissible steering decision (orders) has the following form: ̅̅̅̅}. 𝑍𝐿 = {𝑧𝑙𝑖 ; 𝑖 = 1,7 Particular elements of the ZL set shall be interpreted in the following manner: 𝑧𝑙1 – initiate the set of security measures with the security configuration defined in the register of structures of the security system on the i th position (e.g. defined in the 5th row of such register), 𝑧𝑙2 – activate the indicated technical or organizational security measure in the security system (with current security configuration), 𝑧𝑙3 – switch on/off the indicated technical or organizational security measure (with current security configuration) in the security system, 𝑧𝑙4 – establish the indicated job (with current security structure) in the security service, 𝑧𝑙5 – cancel the indicated job (with current security structure) from the security service, 𝑧𝑙6 – assign the indicated protection process to the specific position, 𝑧𝑙7 – remove the indicated protection process from the specific position. From the point of view of management of the security of information resources, the subject of activities shall be the PO set of protection processes managed by officers from the O set, assigned to the SF set of controllable positions, established under the current security structure of the organization. The set of 𝑃̃ numbers of the managed protection processes and 𝑄̃ numbers of the distinguished features of such process have the following format: 𝑃̃ = {1,2,3,4,5,6,7,8,9}, 𝑄̃ = {1,2,3,4,5}. Particular elements of the 𝑄̃ set shall be interpreted in the following manner: 1 - security measure initiated as part of the current security configuration, 2 - security measure not initiated as part of the current security configuration, 3 - security configuration having all protection methods and techniques (implemented) of technical or organizational nature, established at the stage of design, 4 - security configuration having a sufficient number of security measures ensuring proper functioning of the set, 5 - security configuration not having a sufficient number of security measures ensuring proper functioning of the set. The subjects of activities are bites of information gathered or processed under the ISO. The set of information bites - information resources is determined on the basis of the 𝑂𝐵 = 𝑍𝐼 = {𝑧𝑖𝑝 ∈ 𝐸 𝑆𝐼𝑂 : ⋁𝑞∈𝑄𝑆𝐼𝑂 [< 𝑝, 𝑞 >∈ 𝑉𝐷 ], 𝑝 ∈ 𝑃 𝑆𝐼𝑂 } correlation. According to this definition, the sets of 𝑃 𝑆𝐼𝑂 numbers of the distinguished objects and 𝑄 𝑆𝐼𝑂 numbers of the distinguished features of such information resources have the following format: 𝑃 𝑆𝐼𝑂 = {1,2, … . 20}, 𝑄 𝑆𝐼𝑂 = {1,2, … . 8} Particular elements from the 𝑄 𝑆𝐼𝑂 set shall be interpreted in the following manner: 1- identification number of the object, 2 - name, 3 - set of assigned security attributes, 4 - value of the required level of security in terms of the assigned security attributes, 5 - valuation of the resource in terms of potential damages that the organization may incur due to the loss of the assigned security attributes or required level of security, 6 - set of current vulnerability factors, 7 - current vulnerability value in the context of the set of current vulnerability, 8 - set of currently assigned technical security measures, 9 - set of currently assigned organizational security measures, 10 - value of residual risk, 11 - confidentiality clause.
3
Information system administrator (ASI). A person responsible for the safety of data processing in the information systems. The ASI function is more determined by the practical experience than by the provisions of law.
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Each object number 𝑝 ∈ 𝑃 𝑆𝐼𝑂 shall be defined by the following correlation in accordance with deliberations herein. ̇ 𝑏 ), 𝑅𝑏 > 𝑂𝐵 = 𝑍 =< 𝑏𝑝 , 𝑂𝑝𝑏 𝑤𝑝𝑏 , 𝑄 (𝑤𝑝𝑏 ), ∝̇ (𝑤 𝑝 𝑝 A. B. C.
D.
E.
According to the definition, the 𝐵, 𝑊, 𝑄̇ 𝑏 , ∝̇𝑏 , 𝑅𝑏 , 𝑏 ∈ 𝐵 sets have the following form: The set of the type 𝐵 = {1,2,3} objects, where the elements are interpreted in the following manner: 1- personal data, 2 - confidential data, 3 - sensitive data. The set of W= {1,2} security properties, where the elements are interpreted in the following manner: 1 - resource maintained security attributes, 2 - resource lost basic security attributes. ̅̅̅̅ sets, 𝑄̇𝑏 ; 𝑏 = 1,3 a. 𝑄̇1 = {1,2,4,8.9.10} b. 𝑄̇2 = {1,2,3,4,5,6,7,8,9,10,11} , c. 𝑄̇3 = {1,2,3,4,5,8,9,10} , ∝̇𝑏 ; 𝑏 = ̅̅̅̅ 1,3 sets, a. ∝̇1 = { 1,2,3, 4} b. ∝̇2 = {3,4,5} , c. ∝̇3 = {4, 5} , Elements of the ∝̇𝑏 sets shall be interpreted in the following manner: 1 - basic level of security, 2 medium level of security, 3 - high level of security, 4 - acceptable risk, 5 - tolerable risk. ̅̅̅̅ sets, 𝑅𝑏 ; 𝑏 = 1,3 𝑅1 = 𝑍1 × ∝̇1 = {< 𝑧11 , 1 >, < 𝑧21 , 2 > , < 𝑧31 , 3 > < 𝑧41 , 4 >} 𝑅2 = 𝑍 2 × ∝̇2 = {< 𝑧12 , 3 >, < 𝑧22 , 4 > , < 𝑧32 , 5 >} 𝑅3 = 𝑍 3 × ∝̇3 = {< 𝑧13 , 4 >, < 𝑧23 , 5 >}
̅̅̅̅ sets are activities (tasks) performed in stages, which the subject The elements of the 𝑍 𝑏 ; 𝑏 = 1,3 of activities (𝑜𝑝 ∈ 𝑂𝑝𝑏 officer) should perform to allow the object (information resource) type 𝑏 ∈ 𝐵 form the ∝̇𝑏 set achieve the desired state. ̅̅̅̅} set performed in stages are described in the following manner: Individual tasks from { 𝑍 𝑏 ; 𝑏 = 1,3 𝑧1 ≡ 𝑧11 =< 𝐷𝑀𝐵1 , {𝑃𝑅1 , 𝑃𝑅2 } >, 𝑧2 ≡ 𝑧21 =< 𝐷𝑀𝐵2 , {𝑃𝑅1 , 𝑃𝑅3 , 𝑃𝑅5 , 𝑃𝑅8 } >, 𝑧3 ≡ 𝑧31 =< 𝐷𝑀𝐵3 , {𝑃𝑅1 , 𝑃𝑅2 , 𝑃𝑅6 , 𝑃𝑅7 } >, …………… 𝑧8 ≡ 𝑧13 =< 𝐷𝑀𝐵8 , {𝑃𝑅1 , 𝑃𝑅2 , 𝑃𝑅4 , 𝑃𝑅5 , 𝑃𝑅6 , 𝑃𝑅7 , 𝑃𝑅10 , 𝑃𝑅11 } >, 𝑧9 ≡ 𝑧23 =< 𝐷𝑀𝐵9 , {𝑃𝑅1 , 𝑃𝑅2 , 𝑃𝑅3 , 𝑃𝑅4 , 𝑃𝑅6 , 𝑃𝑅9 } >. The purpose of activities of the processing entity is the form of 𝑞
̅̅̅̅}. ∝ 𝑆𝐵 = {∝̇𝑝 ⊂ ∝̇𝑏 , 𝑏 = 1,3 Particular elements from the ∝̇𝑏 set shall be interpreted in the following manner: ∝̇1 = {1,2,3,4}; ∝̇2 = {3,4,5}, ∝̇3 = {4,5}. Let us assume that the acceptable time frame, during which the 𝑝 ∈ 𝑃 𝑆𝐼𝑂 (𝑡) object (information resources) should reach the desired state may not exceed 3 days. Control of the current level of security Let us assume that the system described in chapter 1 operates for a longer period of time [𝑡0 , 𝑡], where 𝑡0 – moment of starting the information processing process under the ISO, t - current time. While using the ISO, both desired (required) and current utility and security properties are subject to change in terms of the subject of processing and ISO. Let us assume that at 𝑡𝑖 = 𝑡 moment, the system of automated security control or processing entity detected an emergency situation. It is in line with the following condition: 𝐾𝐵 𝑊𝑌 (𝑡𝑖 ) ⊃ 𝐾𝐵𝑀𝑂 . To provide the required level of security of the information resources from the 𝑂𝐵𝑊𝑌 (𝑡𝑖 ) set, the Inspector for the Protection of Personal Data shall initiate the 𝑧𝑙1 order, which generates and implements the new security configuration, ensuring maintenance of the required level of security. The order initiating the new security configuration in the security system may be as follows: RTO n, where:
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•
RTO of security measures - code of the order initiating implementation of an appropriate set of technical and organizational security measures, • n - number of the row in the register of permissible security configurations, corresponding to the number of the emergency situation. The number of the emergency situation is defined by an officer or automatically by the automated security control system based on the knowledge of: • the set of information resources with respect to which it is required to ensure appropriate levels of security, • the set of currently efficient or useful security mechanisms of technical, organizational and personnel nature, • the set of officers at the disposal of the security services of the organization. Let us assume that emergency situation number n=5 occurred. In case of this situation (number 5), the 𝑂𝐵5 , 𝑆𝐹 5 , 𝑀𝐵5 sets are the following: 𝑂𝐵5 = {𝑧𝑖2 , 𝑧𝑖5 , 𝑧𝑖6 , 𝑧𝑖7 , 𝑧𝑖8 , 𝑧𝑖11 } , 𝑆𝐹 5 = {𝑠𝑓1 , 𝑠𝑓2 , 𝑠𝑓3 }, 𝑀𝐵5 = {𝑚𝑏1 , 𝑚𝑏2 , 𝑚𝑏3 , 𝑚𝑏5 , 𝑚𝑏7 , 𝑚𝑏8 , 𝑚𝑏10 , 𝑚𝑏12 , 𝑚𝑏13 }. Summary Fast-paced technological progress and globalization brought new challenges in the fields of information security and personal data protection. The scope of collection and exchange of the information resources significantly increased. Thanks to the technology, both private companies and public bodies may use in its activities the information resources, in particular personal data, on an unprecedented scale. Risk mitigation and provision of efficient protection means for the resources are the possibilities delivered by the automated control and monitoring system of the current information security level. The automated control and monitoring systems of the current information security level, which apart from: • irregularities caused by failure of hardware, • irregularities or new vulnerability of protection means, • new risks, • lost secure processing of some information resources, changes in the work conditions due to the real-time changes in demand for the scope of services offered by the system. In such systems, a number of mechanisms preventing the effects of emergency situation, for example developed systems of automated control of the level of security, systems of automated control of suitability, hardware and software mechanisms for failure tolerance, risk analysis systems, mechanisms for security system reconfiguration, systems for controlling current utility properties, etc. were introduced. The resources of the above-mentioned systems are used, to a varying degree, to implement particular tasks of the information processing, whereas any changes in their use are determined by different emergency situations. For many years now, the works on standardization and optimization of the automated control and monitoring systems of the current information security level have been carried out. According to the conditions of the information society, it is necessary for each security system to have the following properties: 1. continuous readiness, i.e. maintenance of the required level of current functionality, reliability and efficiency in terms of the maintenance of the desired security level, regardless of the emergency situations that may occur, 2. high operability in terms of controlling the performance properties, understood as timely and definite reaction to all emergency situations, and making steering decisions to restore efficiency of the system with respect to the maintenance of the required security level within the required time limit. The article does not offer the recipe for the design and construction of the efficient automated control and monitoring systems of the current information security level. It is merely a proposal of the authors for partial solution of the problem related to the determination and construction of the system, which would allow present control of the security level of the information system in the organization. The proposed approach to the issue of security, aimed at the reconfiguration process, results, among other things, from the observations and long-term experience of the authors gained: • during observations of the construction and implementation of such systems in the organizations and corporations, • during research and implementation projects, • during scientific and research projects as well as seminar discussions relating to the issue of information security.
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References HOFFMANN, R., KIEDROWICZ, M., STANIK, J. 2016. Risk management system as the basic paradigm of the information security management system in an organization. 20th International Conference on Circuits, Systems, Communications and Computers (CSCC 2016), MATEC Web of Conferences, vol. 76. KIEDROWICZ, M. 2018. Metodyka zarządzania ryzykiem w bezpieczeństwie zasobów informacyjnych. (Methodology of risk management in the security of information resources). In: Collegium of Economic Analysis Annals, Publisher: Warsaw School of Economics (SGH) Collegium of Economic Analysis, vol 49, p. 287-305. KIEDROWICZ, M., STANIK, J., NAPIÓRKOWSKI, J. 2018. Standardy bezpieczeństwa w cyklu życia systemu zabezpieczeń systemu informacyjnego organizacji. (Safety standards in the life cycle of the organization's information system security system). Collegium of Economic Analysis Annals, Publisher: Warsaw School of Economics (SGH) Collegium of Economic Analysis, vol 49, p. 347-369. KIEDROWICZ, M. 2017. Multi-faceted methodology of the risk analysis and management referring to the IT system supporting the processing of documents at different levels of sensitivity. 21st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017), MATEC Web of Conferences, vol. 125. KIEDROWICZ, M., STANIK, J. 2017. Models and method for the risk assessment of an intellectual resource. WSEAS Transactions on Information Science and Applications, 14: 174-183. STANIK, J., NAPIÓRKOWSKI, J., HOFFMANN, R. 2016. Zarządzanie ryzykiem w systemie zarządzania bezpieczeństwem organizacji (The risk analysis and the risk management as basic components of the safety management system of the organization). Scientific Papers of the University of Szczecin, Economic Problems of Services, 123: 321-336. ROZPORZĄDZENIE Parlamentu Europejskiego i Rady (UE) 2016/679 z dnia 27 kwietnia 2016 r. w sprawie ochrony osób fizycznych w związku z przetwarzaniem danych osobowych i w sprawie swobodnego przepływu takich danych oraz uchylenia dyrektywy 95/46/WE - ogólne rozporządzenie o ochronie danych (Regulation (EU) No 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC - General Data Protection Regulation). ISO / IEC 27002: 2015 Technika informatyczna - Techniki bezpieczeństwa - Kodeks postępowania w zakresie kontroli bezpieczeństwa informacji (Information technology - Security techniques - Code of conduct in the field of information security control). ISO / IEC 27004: 2013 Technika informatyczna - Techniki zabezpieczeń - Zarządzanie bezpieczeństwem informacji – pomiary (Information technology - Security techniques - Information security management - measurements). http://www.zut.edu.pl/fileadmin/pliki/abi/9/RYZYKO_ODO-1.pdf (access 21.03.2018). http://www.zut.edu.pl/fileadmin/pliki/abi/9/RYZYKO_ODO-2.pdf (access 21.03.2018).
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ASSESSMENT OF THE USEFULNESS OF THE SECURITY CONFIGURATION Maciej Kiedrowicz, Ph.D. Cybernetics Faculty Military University of Technology Warsaw, Poland e-mail:
[email protected]
Jerzy Stanik, Ph.D.
Cybernetics Faculty Military University of Technology Warsaw, Poland e-mail:
[email protected] Abstract The article outlines a method of assessment of the usefulness of the security configuration 1 (SC) from a set of available security configurations, after occurrence of an emergency situation. It is believed that the best security configuration is the one that not only ensures maintenance of the required security level of the information resources, but also provides the best values describing its utility properties. The values describing the utility properties of the security configuration and partial criteria for measuring their utility were proposed. The utility measures of the security configuration include performance, reliability and security indicators. Key words: utility, security system, security configuration, loss of security Introduction To ensure the required level of security of an organization or high level of security of a given information system of such organization, which would protect it against risks, it is necessary to develop the protection strategy (plan, project) in accordance with a reliable methodology (STANIK, KIEDROWICZ, 2017; KIEDROWICZ, 2017), and then implement such project by experts, using appropriate technology and maintaining appropriate security configurations. The designed security configurations of technical or organizational nature should be to a large extent based on the results of the risk analysis, specifications of security requirements as well as general theory of security measures (i.a. it is required to assess utility of the current security configuration, verify resistance of the applied security measures to different types of attacks and re-configure the security system following the occurrence of various types of emergency situations and loss of the required level of security). After the occurrence of an emergency situation – loss of the required level of security, it is essential to generate permissible or optimum security configuration to efficiently continue the process of safe information processing in the information system of the organization (ISO). The optimum security configuration generated from among a set of permissible solutions (EHRGOTT, 2005) is possible on the basis of the detailed reconfiguration function Q, which - from the point of view of its essence - is a criterial function. Schematic representation of the organization from the perspective of the reconfiguration process – control of current properties of the security configuration is in figure 1. The purpose of this article is to develop the security system model to formulate the issue of multicriteria optimization of the security configuration. To achieve the assumed goal, it was necessary to execute the following tasks, which at the same time constitute the scope of this article: • definition of the subject, object and purpose of the operations of the security system, • distinction of material values describing utility properties of the security system and security configuration, • definition of the method for measuring utility properties of the security configuration, • proposal of a set of partial criteria (criteria functions and quality indicators) for measuring utility of the security configuration, • definition of the means for measuring utility of the security configuration to assess and chose the best configuration. Security configuration – a set of technical, organizational and human resources (security measures) as well as correlations between them, which reflect the quality, e.g. utility, security, performance and reliability features. 1
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The configuration property control subsystem (safety, functionality, reliability) Information security status in the organization at time t (k)
Functional Positions Security Service
Information subsystem
Register of records Safety Configuration
Automatic Safety Control System
Threat level at time t (k)
Security measures
Subsystem to maintain the security configuration
Automatic system Reliability Control
threat
threat Protection measure susceptibility
accountability
Risk susceptibility
confidentiality
List of identified risks
Requirements for the application of control and
susceptibility
Processes Business
Register actions processing
Resources information
integrality
Register value assets
Register of current security measures and control mechanisms
susceptibility
Final value
Risk
Risk
Register entities processing
Criteria for risk acceptance
Register owners assets
susceptibility
Technological environment
security measures
Legal, social, political environment, external entities
threat
Protection measure
Risk
threat
Protection measure
Documentation
Configuration control
Working Group Security officer
The level of threat at time t (k + 1)
Set of control decisions (operator's orders)
A subsystem for the design and operation of security configurations
Zasoby
Initial value
Information security status in the organization at time t (k + 1)
Deciding entity
Criteria and evaluation scales
susceptibility
availability
Risk Protection measure
Protection measure threat
threat
Current Configuration Safety
The reconfiguration process
Desired security configuration
Fig. 1. Representation of the organization from the perspective of the reconfiguration process – control of current properties of the security configuration. Source: Own study.
According to the authors, all intended elements were described in this article. Furthermore, to facilitate the understanding of the above-mentioned issues, we assume that the purpose of the security system is to assign appropriate 𝛼𝑝̇ statuses to the ISO objects (e.g. business processes, information processing processes, established bits of information - information resources), within the Δ𝑇𝑝̇ time framework, not only in terms of their functionality or utility, but also security. When determining the current security level of information, three main issues, typical for the structure of the article, must be taken into consideration: • at each particular moment of time, it must be possible to safely process the required set of information resources, • key business processes and sensitive information resources are required 2, with respect to which protection processes need to be implemented to ensure maintenance of appropriate security attributes 3 at the acceptable risk level 4, • To maintain the required security attributes, the security authorities shall establish, implement and maintain strictly predefined security configurations with respect to a selected set of ISO resources, ensuring their appropriate level of security or tolerable risk value.
Sensitive information resource – each asset of the organization, whose loss may cause significant damages to the organization. Information security attribute – here: confidentiality, non-repudiation, availability, integrity, accountability, reliability. 4 Acceptable risk – the level of risk which the organization may accept without any additional remedial actions or changes in its operations. 2 3
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The security system and its subject, object and purpose of operations Security system When compared with other definitions of the information security theory, the following definition seems to be the most accurate in terms of the requirements (STANIK et al., 2016; HOFFMANN et al., 2016; KIEDROWICZ, 2018) hereof: "The security system constitutes a part of the whole system for information security management with predefined actions concerning the design, monitoring and maintenance of the desired set of technical and organizational security measures, based on which it is possible to generate the required security configuration". The security system includes an organizational structure, planned actions, scopes of responsibilities and work tools allowing to control the current level of security of the entire organization as its elements. The security system constitutes one of the key links in the Information Security Management Systems. Following the above definition, we shall adopt the ordered four as the model for the information security system: 𝑆𝐵 =< 𝑃𝑂𝐹, 𝑃𝐷𝑍, ℂ, 𝐾𝐵 >,
(1)
where: 𝑃𝑂𝐹 - the subject of activities of the security system refers to a group of officers, who perform different roles in the data processing process, entitled to make decisions in that respect, 𝑃𝐷𝑍- the object of activities, i.e. the ISO objects, with respect to which the data must be processed and the security maintained at the required level, ℂ - the purpose of operations as defined in the object of activities, 𝐾𝐵 - the set of permissible security configurations, which constitutes a basic element of the object of activities in terms of maintaining the required level of security. The set of permissible security configurations shall be considered a comprehensive, consistent and non-contradictory security system aimed at reducing the probability of risk of assets or information system of the organization. Their appropriate selection and efficient use allow to significantly reduce the cost of security of the organization, additionally ensuring appropriate level of security - tolerable level of protection. The above-mentioned elements constitute the subject of deliberations in the subsequent subchapters of the article. Object of activities In terms of controlling the current level of information security, the object of activities may be the following: 1. an element of the automatic process for making steering decisions, e.g. the system of automatic security control system, 2. a group of officers, appointed within the framework of a team responsible for the design and handling of security configurations or Information Security Management System (ISMS) in a given organization, hereinafter referred to as the object of the decision making process. Let us introduce the following symbols: SF – a set of the ordered fours: 𝑠𝑓𝑝 =< 𝑂𝑝 , 𝑃𝑝 , 𝑃𝑂𝑝 , 𝑀𝐵𝑝 > ∈ × 2𝑃 × 2𝑃𝑂 × 2𝑀𝐵 ,
(2)
hereinafter referred to as positions; while considering the set of {𝑅𝑖 ; 𝑖 ∈ 𝐼} correlations defined in the SF set, it is possible to distinguish different functional structures of the security system team, where: - a group of officers appointed within the framework of the security system; the group of such persons is determined at the stage of designing the ISMS, 𝑃 - a set of ISO objects, with respect to which the officers of the security system should maintain the required level of security, 𝑃𝑂 - a set of control mechanisms or protection processes, thanks to which it is possible to support the processing of the information in the ISO in terms of security and continuity of business processes in the organization, 𝑀𝐵 - a set of security measures available to officers of the security system.
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Subject of activities In terms of controlling the current level of information security, the subject of activities shall be a set of such 𝑒𝑗 ∈ 𝐸 𝑆𝐼𝑂 elements, information system of the organization (ISO), whose required status may determine the object of the decision making process. The following may be the elements of the 𝐸 𝑆𝐼𝑂 set: • key business processes, • information processing processes, • bits of information (information resources) collected or processed under ISO, hereinafter referred to as an object or information resource. Every 𝑧 ∈ 𝑍 information resource shall be marked with 𝑝 ∈ 𝑃 𝑆𝐼𝑂 number and described using the 𝑆𝐼𝑂 𝐶𝑝 set of property names. If all different sets of 𝐶𝑝𝑆𝐼𝑂 features used to describe particular information resources are numbered with 𝑏 = ̅̅̅̅̅ 1, 𝐵 variable (which shall be called a type of the information resource object), the two objects shall be of the same type (e.g. "b"), when described by the identical sets of features. The sets of 𝑄𝑝𝑆𝐼𝑂 numbers of features describing the 𝑝 ∈ 𝑃 𝑆𝐼𝑂 object and sets of 𝐶𝑝𝑆𝐼𝑂 feature names corresponding thereto may not be empty for each 𝑝 ∈ 𝑃 𝑆𝐼𝑂 , where 𝑃 𝑆𝐼𝑂 constitutes the set of numbers of the distinguished information resources. We assume that the 𝐴𝑞𝑆𝐼𝑂 set of potential implementation of the 𝑎𝑞 feature shall be determined for each 𝑞 ∈ 𝑄 𝑆𝐼𝑂 feature. Purpose of operations of the security system The operations of the security system may be defined as the following ordered pair: 𝐷𝑍 𝑆𝑍 =,
(3)
where: ∝𝑆𝑍 – the purpose of operations of the security system in terms of safety of the information processing, 𝑍 𝑆𝑍 – the set of tasks related to safe processing of information allowing to achieve the goal ∝𝑆𝑍 . Let us introduce the following symbols: 𝑃̇ (𝑡) – the set of numbers of the information resources collected in the ISO by the time t, and with respect to which it is required to continue safe processing, 𝑝 [𝑡0 , ̇ 𝑇̇ 𝑝 ] – permissible time framework, during which the object number 𝑝 ∈ 𝑃̇ (𝑡) should retain the security attributes - i.e. should have the required level of security, 𝑝 ̇ 𝑊̇𝑝 – the desired security feature of the pth information object obtained during the [𝑡0 , ̇ 𝑇̇ 𝑝 ] time framework, where: 𝑝 𝑡0 , – time of registering the pth object in the ISO 𝑇̇ 𝑝 – time of de-registering (removing) the pth object in the ISO 𝑄 𝑆𝐼𝑂 (𝑤) – the set of features of the information object, based on which the "w" property is determined. To determine whether the information resource number 𝑝 ∈ 𝑃̇(𝑡) has the "w" property, it is neces𝑞 𝑞 sary to define for such object the ∝𝑝 (𝑤) ⊂ 𝐴̇𝑝 subsets of the feature implementation, for each 𝑞 ∈ 𝑄 𝑆𝐼𝐾 (𝑤) 𝑝 𝑝 𝑞 feature. If the 𝑎𝑞 (𝑡) features of the pth object implemented at the 𝑡 ∈ [𝑡̇0 , 𝑇̇ 𝑝 ] time belong to the ∝𝑝 (𝑤) subsets, it is possible to state that the object number 𝑝 ∈ 𝑃̇ (𝑡) has the "w" property. When assuming that 𝑞 𝑞 the sets of 𝑄̇𝑃 features, whose values are used to define the ∝𝑝 (𝑤) ≡ ∝̇𝑝 , 𝑞 ∈ 𝑄̇𝑃 subsets, are known for each 𝑝 ∈ 𝑃 𝑆𝐼𝑂 object, the purpose of the security system may be determined in the following manner: 𝑞 ∝ 𝑆𝑍 ≡ ∝ 𝑆𝑍 { ∝̇𝑝 ∶ < 𝑝, 𝑞 >∈ 𝑉𝐷 , 𝑝 ∈ 𝑃̇ (𝑡), 𝑞 ∈ 𝑄 𝑆𝐼𝑂 }.
(4)
In terms of a possibility of achieving the goal of the security system operations, each 𝑧𝑝 ∈ 𝑍 information resource processed under the ISO may be described in the following manner: ̇ 𝑏 , 𝐺 𝑏 , 𝑆𝑏 , 𝑅𝑏 > 𝑧𝑝 = < 𝑏𝑝 , 𝑂𝑝𝑏 , 𝑤𝑝𝑏 , 𝑄 (𝑤𝑝𝑏 ), ∝̇ (𝑤𝑝𝑏 ), 𝑅 𝑝 𝑝 𝑝 𝐺𝑆 where: 𝑏𝑝 – the type of the pth information resource,
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(5)
𝑂𝑝𝑏 – the officer responsible for maintaining the required level of security with respect to the p th information resource of the "b" type, 𝑤𝑝𝑏 , – security feature of the pth information resource of the "b" type, 𝑞 𝑄 (𝑤̇ 𝑏 ) – the set of feature numbers, based on which the ∝ (𝑤 𝑏 ) subsets are defined, 𝑝
𝑝
𝑝
∝̇ (𝑤𝑝𝑏 ) – the set of desired statuses of the pth "b" type object, 𝑅𝑝𝑏 – the set of correlations linking 𝑏𝑝 with ∝̇ (𝑤𝑝𝑏 ), 𝐺𝑝𝑏 – the set of potential risks of the pth information resource of "b" type, 𝑆𝑝𝑏 – the set of vulnerability of the pth information resource of "b" type, 𝑏 𝑅𝐺𝑆 – the correlation linking 𝐺𝑝𝑏 with 𝑆𝑝𝑏 . Security configuration The following notation of any security configuration shall be introduced 𝐾𝐵𝑘𝑙 = 〈𝑂𝐵𝑘𝑙 , 𝑃𝑂𝑘 , 𝑀𝐵𝑙 〉
(6)
where: 𝑂𝐵𝑘𝑙 – the set of information resources of the information system in the organization subject to protection by the klth security configuration, 𝑘 𝑃𝑂 – the set of protection processes implemented to ensure security of the information resources belonging to the 𝑂𝐵𝑘𝑙 set, 𝑙 𝑀𝐵 – the set of technical, organizational and human security measures, which constitute the kl th security configuration. The knowledge of the 𝐾𝐵𝑘𝑙 security configuration makes it possible to assign the 𝑀𝐵𝑙 set corresponding to each 𝑂𝐵𝑘𝑙 , set, with the predefined 𝑃𝑂𝑘 set of security mechanisms (organizational and technical security measures). The 𝐾𝐵𝑘𝑙 security configuration is implemented only when it is possible to assign such 𝑧𝑏𝑖ó𝑟 𝑃𝑂𝑘 , to the 𝑂𝐵𝑘𝑙 set, with predefined elements of the 𝑀𝐵𝑙 set, which shall guarantee the maintenance of the required level of security for the 𝑂𝐵𝑘𝑙 set of information resources. It may be assumed that as a result of the above, the 𝑂𝐵𝑘𝑙 set, with the predefined 𝑀𝐵𝑙 set, remains in correlation with the 𝑃𝑂𝑘 set, i.e. 𝑂𝐵 𝑘𝑙 𝐾𝐵𝑘𝑙 𝑃𝑂𝑘 . Therefore, it is possible to analyze the security configuration (9) as analogous to the terminal system, in which the information resources from the 𝑂𝐵𝑘𝑙 set constitute input data, whereas the elements of the 𝑃𝑂𝑘 set - output data. If a given 𝑧𝑔 ∈ 𝑂𝐵 information resource may be protected by way of the 𝑝𝑜 ∈ P𝑂 protection process, then, by providing the 𝑅𝑥 feasibility correlation, ( 𝑅𝑥 ⊂ 𝑂𝐵 × P𝑂), in case of which the following formula: 〈𝑧𝑔 , 𝑝𝑜𝑗 〉 ∈ 𝑅𝑥 is correct, it is possible to determine the set of protection processes used to protect a single 𝑧𝑔 information resource. Depending on the types of information resources, which need to be protected through the protection processes and security measures, with the predefined security configuration, it is possible to activate, at a given moment, several or even a dozen or so 𝐾𝐵𝑔 resource security configurations. In such case, any 𝐾𝐵𝑘𝑙 security configuration may be analyzed as a multitude of the security configurations for the 𝑧𝑔 ∈ 𝑂𝐵𝑘𝑙 resources, i.e.: 𝐾𝐵𝑘𝑙 = ⋃𝑔: 𝑂𝐵𝑔 ∈ 𝑂𝐵𝑘𝑙 𝐾𝐵𝑔 .
(7)
It should be stressed that the information resources subject to protection require specific technical or organizational security measures to ensure the acceptable security level. Values describing utility properties of the security system In case of loss of the required level of security, it should be possible to activate (using efficient security mechanisms - technical and organizational security measures) several other protection processes or permissible security configurations. In such cases, it is necessary to choose one of them. It is obvious that the chosen security configuration must be the best in every aspect. Therefore, it is necessary to comprehensively assess - in terms of criteria functions - all variants of the permissible security configuration, including many values (characteristics) describing its utility and security properties. The assessment shall be com-
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posed of many partial assessments. Such task may be executed only upon establishment of the set of representative characteristics reflecting the purpose of operations of the security system, manner of its operation and rules of use, determining the system's utility 5 or efficiency6. In such a manner, the subjectivity of the assessment is decreased, thus, it is possible to: 1. reduce the number of criteria functions and quality indicators, which constitute grounds for such assessment and choice of the optimal or suboptimal security configuration, 2. ensure proportionality of the significance (weight) of particular values and criteria functions, 3. reasonably assess the utility of the security system with a specific security configuration. With the above in mind, it is possible to state the following with respect to the utility of the security configuration in the security system, distinguishing the following values (characteristics): 1. Sensitivity7 of the security system to the loss of the required level of security, 2. Time of generation of the security configuration, 3. Efficiency of the operations of the information processing subsystem, 4. Redundancy with respect to the technical security measures, 5. Redundancy with respect to the protection processes. The above-mentioned values describing the properties of the security system with a specific security configuration do not constitute any closed set. It is possible to introduce other (not mentioned herein) values, which concern, for example, bandwidth or capacity of the security configuration. Let us introduce the following symbols: Ω – the set of values describing utility properties of the security configuration, 𝑢 𝐾𝐵𝑑𝑜𝑝 – the set of permissible security configurations in case of the emergency situation (loss of security), number "u", Q – the set of distinguished criteria functions, 𝑊 – the set of vectors of implementation of particular values from the Ω set, 𝑓1−5 – the vector-valued function assigning a vector of implementation of particular values to each permissible security configuration. While considering the above values (describing the utility properties of the security configuration), the Ω set may be presented in the following manner: ̅̅̅̅}. 𝛺 = {𝛺 𝑖 , 𝑖 = 1,5
(8)
Let us assume that for each 𝛺 𝑖 value, the 𝑊 𝑖 set of possible implementation is determined. In such case, the ordered set of implementation of the < 𝑓1 (𝐾𝐵), 𝑓2 (𝐾𝐵), 𝑓3 (𝐾𝐵), 𝑓4 (𝐾𝐵), 𝑓5 (𝐾𝐵) > value shall corre𝑢 spond to the permissible 𝐾𝐵 ∈ 𝐾𝐵𝑑𝑜𝑝 security configuration, recorded shortly 𝑓( 𝐾𝐵) or 𝑤 =< 𝑤1 , 𝑤2 , 𝑤3 , 𝑤4 , 𝑤5 >.
(9)
𝑢 The functions assigning to each permissible 𝐾𝐵 ∈ 𝐾𝐵𝑑𝑜𝑝 configuration the implementation of its ith value, may be presented in the following manner:
𝑢 ̅ 𝐾𝐵𝑑𝑜𝑝 𝑓:
𝑢 𝑓𝑖 ∶ 𝐾𝐵𝑑𝑜𝑝 ⟶ 𝑊𝑖 , 𝑓𝑖 (𝐾𝐵) = 𝑤𝑖 , 𝑖 = 1,5. ⟶ 𝑊1 × 𝑊2 × 𝑊3 × 𝑊4 × 𝑊5 ; 𝑓(̅ 𝐾𝐵) = 𝑤 vector function.
(10) (11)
According to further considerations on 𝑤 vectors of implementation of the values describing the utility properties of the security configurations, it may be assumed that the security configurations with the same type of implementation of such values are indistinguishable and have the same use value for the assessor (in terms of utility). Such assumption is true only when the distinguished values reflect basic material utility properties of the security configuration. 𝑢 𝑢 The 𝑊 = 𝑓(𝐾𝐵𝑑𝑜𝑝 ) set of permissible 𝐾𝐵 ∈ 𝐾𝐵𝑑𝑜𝑝 security configurations does not have to include all possible combinations of implementation of the values (𝑊1 × 𝑊2 × 𝑊3 × 𝑊4 × 𝑊)) and usually does not include. Some types of implementation of the Cartesian product (𝑊1 × 𝑊2 × 𝑊3 × 𝑊4 × 𝑊)) correspond, in practice, to impermissible or unfeasible variants.
Easy operation and meeting the actual needs of the user. Verification whether the undertaken activities produced the expected results. 7 Ability of the security system to react to the change of type and amount of the information subject to further processing under the ISO, 5 6
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The vectors of implementation of values reflecting the utility properties of the security configuration are not value determinants in general. The criteria functions, depending on the vectors of implementation of such values, are used to show the utility of the security configuration. Therefore, the criteria func̅ (KB) vectors defined in the following manner: tions are the functions of 𝑤 or 𝑓: 𝑢 𝑄𝑚 : 𝑊 ⟶ 𝑌𝑚 , 𝑚 = 1, 𝑀 or 𝑄𝑚 : 𝑓(𝐾𝐵𝑑𝑜𝑝 ) ⟶ 𝑌𝑚 , 𝑚 = 1, 𝑀
(12)
where: 𝑢 W, 𝑓(𝐾𝐵𝑑𝑜𝑝 ) – the sets of vectors of implementation of values, M – the number of distinguished criteria functions. The permissible security configurations may be assessed using the following vectors: 𝑄(𝐾𝐵) = (𝑄1 (𝑓(𝐾𝐵)) , 𝑄2 (𝑓(𝐾𝐵)) , 𝑄3 (𝑓(𝐾𝐵)) , 𝑄4 (𝑓(𝐾𝐵)) , … , 𝑄𝑀 (𝑓(𝐾𝐵)) ) or 𝑄(𝐾𝐵) = (𝑄1 (𝐾𝐵), 𝑄2 (𝐾𝐵), 𝑄3 (𝐾𝐵), … , 𝑄𝑀 (𝐾𝐵) ).
(13)
̂ criteria functions, their extremization are not provided for, but preferences In case of 𝑄𝑚 , 𝑚 ∈ 𝑀 are to be established. The preferences mean that the level of each distinguished criterion must be achieved equally or exceeded unequally, i.e.: ̂ 𝑄𝑚 (𝐾𝐵) ≥ 𝑦̂𝑚 , 𝑚 ∈ 𝑀
(14)
where: 𝑦̂𝑚 – the level of preference (aspiration) for the mth criteria function, ̂ – the set of numbers of criteria functions, with respect to which no extremization is provided for. 𝑀 The aspiration level values are determined by experts from the security system team, depending on what is demanded from such system. To find optimal or suboptimal security configuration, the following stages must be executed: 1. Definition and measurement of values describing utility properties of the security configuration, 2. Definition of the set of criteria functions, 3. Formulation of the issue of multicriteria optimization, 4. Solution of the task of multicriteria optimization. Assessment and measurement of values describing utility properties of the security configuration The characteristics of the values mentioned in point 1 describing the utility properties of the security configuration may be determined (measured) by choosing one of the following options: 1. Measurements based on actual security systems, with predefined security configuration in simulated conditions of incoming risks and vulnerability of information resources and security measures of technical and organizational nature, or while using the security system in various test or actual conditions; 2. The measurements conducted in the simulated security system, with the predefined security configurations. The first method applies to already existing and used Information Security Management Systems, whereas the second one - to the designed Information Security Management Systems. Sensitivity assessment of the system with the predefined security configuration Sensitivity characteristics of the security system with the predefined security configuration are assessed with respect to the type and number of information resources, subject to further protection (with respect to which it is necessary to maintain the required level of security) after the occurrence of an emergency situation. The method for assessing sensitivity of the security system with the predefined security configuration to quantitative changes of the types of bits of informations is as follows: 1. When using the 𝐹 = (𝐹 𝑂𝐵 , 𝐹 𝑃𝑂 , 𝐹 𝑀𝐵 ) vector function for identifying the emergency situation – loss of the required level of security, for example number "u", the following must be determined: a) The set of 2𝑂𝐵 information resources under the ISO, with respect to which the security needs to be maintained at a required level, as of the time of the loss of the required level of security, 231
b) 2.
The 2𝑃𝑂 set of protection processes, which may be initiated after the occurrence of an emergency situation, c) The 2𝑀𝐵 set of efficient technical and organizational mechanisms. Having determined the 𝑂𝐵𝑢 , 𝑃𝑂𝑢 , 𝑀𝐵𝑢 sets, it is essential to establish the set of permissible security configurations, ensuring the maintenance of the required level of security of the information resources in the 𝑂𝐵𝑢 set. The set of permissible security configurations my be presented in the following manner: 𝑢
𝑢
𝑢
̂ 𝑢 𝐾𝐵𝑑𝑜𝑝 = {𝐾𝐵𝑥𝑢 ∈ 2𝑂𝐵 × 2𝑃𝑂 × 2𝑀𝐵 : 𝑂𝐵𝑥𝑀𝐴𝑋 ⊇ 𝑂𝐵 𝑢 , 𝑥 ∈ 𝑋 𝑢 },
(15)
where: ̂ 𝑢 – the set of information resources, with respect to which it is possible to achieve the re𝑂𝐵 quired level of security, with the predefined 𝑂𝑢 and 𝑀𝐵𝑢 sets. 𝑀𝐴𝑋 𝑂𝐵𝑥 – the set of information resources, including a maximum number of information resources, with respect to which it is possible to maintain the level of security as part of the 𝐾𝐵𝑥 th security configuration, 𝑢 𝑋 𝑢 – the set of indices of the 𝐾𝐵𝑑𝑜𝑝 set. 3.
Assuming that the security system with the 𝐾𝐵𝑥 th security configuration is: a) insensitive to emergency situations if 𝑂𝐵𝑥𝑀𝐴𝑋 ≡ 𝑂𝐵 b) sensitive to emergency situation if 𝑂𝐵𝑢 ⊂ 𝑂𝐵𝑥𝑀𝐴𝑋 , c) critically sensitive if 𝑂𝐵𝑥𝑀𝐴𝑋 ≡ 𝑂𝐵𝑢 .
Method for measuring the generation time of the system with the predefined security configuration The generation time of the security system with the predefined security configuration shall be understood as the sum total of the duration time of the initiated protection processes by the decision-making entity, counted from the occurrence of the emergency situation - loss of the required level of security as of the generation time of the security system with an appropriate security configuration. The duration of such actions shall be deemed to mean average time set for the multiple development of the aforesaid configuration for the same emergency situation. Therefore, the setting of the generation values of the security system with the predefined security configuration requires statistical surveys. Efficiency assessment of the operations of the information processing subsystem with the predefined security configuration The efficiency of the operations of the information processing subsystem is assessed with respect to the types of protection processes and the number of such types that may be initiated to maintain the required level of security of the information resources. The method of efficiency assessment of the operations of the information processing subsystem with the predefined security configuration may be as follows: 1. The 𝑅𝑥 set of types of the protection processes initiated as part of the 𝐾𝐵𝑥 th security configuration is determined for the established 𝑃𝑂𝑥 set, 2. The8 efficiency measure is set for each 𝑟 ∈ 𝑅𝑥 type. 𝐻𝑟𝑥 . 3. on the basis of the knowledge of the following: a) vector efficiency measure of the information processing subsystem 𝐻 𝑥 = (𝐻1𝑥 , 𝐻2𝑥 , … , 𝐻𝑟𝑥 , … , 𝐻𝑅𝑥𝑥 )
(16)
where: 𝐻𝑟𝑥 – vector coordinates showing expected values of the relative effects of operations of particular protection processes, 𝑅𝑥 – number of the distinguished protection processes initiated in the 𝐾𝐵𝑥 th security configuration, b)
8
vector of statuses of all protection processes initiated in the 𝐾𝐵𝑥 th security configuration
The measure is set at the stage of designing the security level by the risk analysis team 232
𝐾 𝑥 = (𝐾1𝑥 , 𝐾2𝑥 , … , 𝐾𝑟𝑥 , … , 𝐾𝑅𝑥𝑥 )
(17)
where: 𝐾𝑟𝑥 – vector coordinates showing the count of the protection processes initiated in the 𝐾𝐵𝑥 th security configuration, 𝑅𝑥 – number of types of the distinguished protection processes initiated in the 𝐾𝐵𝑥 th security configuration, c)
vector of statuses of critical protection processes initiated in the 𝐾𝐵𝑥 th security configuration 𝑥 𝑥 𝑥 𝑥 𝑥 𝐾𝐾𝑅 = (𝐾𝐾𝑅,1 , 𝐾𝐾𝑅,2 , … , 𝐾𝐾𝑅,𝑟 , … , 𝐾𝐾𝑅,𝑅 ) 𝑥
(18)
where: 𝑥 𝐾𝐾𝑅,𝑟 – vector coordinates showing the count of the protection processes of particular types included in the 𝐾𝐵𝑥 th security configuration, 𝑅𝑥 – number of the distinguished types of the protection processes included in the 𝐾𝐵𝑥 th security configuration.
4.
𝑥 𝑥 The correlations between the 𝐾𝑟𝑥 and 𝐾𝐾𝑅,𝑟 values are determined, where (𝐾𝐾𝑅,𝑟 = 𝐾𝑟𝑥 ∙ 𝐻𝑟𝑥 ) means an average number of the protection processes initiated to protect the information resources under the ISO. Assuming that the subsystem for the processing of the information resources, in which the 𝐾𝐵𝑥 th security configuration was activated, is: 𝑥 a) efficient if ⋁𝑟∈𝑅𝑥 𝐾𝑟𝑥 ≥ 𝐾𝐾𝑅,𝑟 , 𝑥 𝑥 b) inefficient if ⋁𝑟∈𝑅𝑥 𝐾𝑟 < 𝐾𝐾𝑅,𝑟 ,
Assessment of the existence of security redundancy in the information processing subsystem with the predefined security configuration The existence of security redundancy in the information processing subsystem shall be assessed with respect to the types and number of such types of security measures that may be initiated in the 𝐾𝐵𝑥 th security configuration for the purpose of maintaining the required level of security of the information resources. The method for assessing the existence of security redundancy in the information processing subsystem may be as follows due to quantitative changes in the security measures: 1. In case of the already established 𝑂𝐵𝑥 , 𝑃𝑂𝑥 , 𝑀𝐵𝑥 sets, it is essential to determine the 𝑅𝑥 set of security mechanisms initiated as part the 𝐾𝐵𝑥 th security configuration, ensuring safe processing of the information resources from the 𝑂𝐵𝑥 set. 2. While using the 𝛾: 2𝑃𝑂 ⟶ 2𝑀𝐵 transformation, it is required to determine the 𝑀𝐵𝑢 set of technical and organizational resources, necessary to provide the information resources from the set 𝑂𝐵 𝑢 3. Assuming that in the ISO of the 𝐾𝐵𝑥 th security configuration: a) security redundancy exists if 𝑀𝐵𝑥 ⊃ 𝑀𝐵𝑢 , b) security redundancy does not exist if 𝑀𝐵𝑥 ≡ 𝑀𝐵𝑢 . Assessment of even load of the security configuration with the technical security measures Even load of the 𝐾𝐵𝑥 th security configuration with the technical security measures shall be assessed with respect to the types and number of such types of security measures that may be initiated in the 𝐾𝐵𝑥 th security configuration for the purpose of maintaining the required level of security of the information resources. The method of assessment of even load of the 𝐾𝐵𝑥 th security configuration with technical security measures may be as follows: 1. For the already established 𝑍𝑇𝑥 set, the following is determined: a) the Ix set of numbers of efficient security measures implemented as part of the KBx th security configuration and ensuring safe processing of the information resources from the OBx set, b) the Jx set of numbers of the protection processes implemented as part of the KBx th security configuration and ensuring safe processing of the information resources from the OBx set, c) the Bx set of types of the technical security measures included in the KBx th security configuration,
233
d) 2.
the Nx = [nij ] matrix, size I × J, whose elements show the number of technical security measures from the jth type to the ith protection process, initiated under the KBx th security configuration. Assuming that the protection processes included in the 𝐾𝐵𝑥 th security configuration are: a) evenly loaded if ⋀∈𝐼𝑥×𝐼𝑥(⋀𝑗∈𝐵𝑥 𝑛𝑖𝑗 = 𝑛𝑘𝑗 ) , 𝑖 ≠ 𝑘 b)
unevenly loaded if ⋁∈𝐼𝑥×𝐼𝑥(⋁𝑗∈𝐵𝑥 𝑛𝑖𝑗 = 𝑛𝑘𝑗 ), 𝑖 ≠ 𝑘 .
Forms of the distinguished criteria functions In case of the security system, the utility of the security configuration may be assessed and compared in a reliable manner using the following qualitative indicators 1. 𝑄1 (𝐾𝐵𝑥 ) - sensitivity of the security system to the loss of the required level of security, 2. 𝑄2 (𝐾𝐵𝑥 ) - time of generation of the security configuration, 3. 𝑄3 (𝐾𝐵𝑥 ) - efficiency of the operations of the information processing subsystem, 4. 𝑄4 (𝐾𝐵𝑥 ) - redundancy with respect to the technical security measures, 5. 𝑄5 (𝐾𝐵𝑥 ) - assessment of even load of the security configuration with the technical security measures. The above-mentioned indicators are defined in the following manner: 𝑄1 (𝐾𝐵𝑥 ) = 𝑦1 =
̿̿̿̿ 𝑂𝐵𝑥𝑀𝐴𝑋 − ̿̿̿̿ 𝑂𝐵𝑢 ,𝑥 ̿̿̿̿ 𝑂𝐵
∈ 𝑋;
(19)
where : ̿̿̿̿ 𝑂𝐵𝑥𝑀𝐴𝑋 , ̿̿̿̿ 𝑂𝐵 𝑢 , ̿̿̿̿ 𝑂𝐵 – cardinality 𝑂𝐵𝑥𝑀𝐴𝑋 ,𝑂𝐵𝑢 , 𝑂𝐵; whereas: 𝑂𝐵𝑥𝑀𝐴𝑋 – the set of information resources, including a maximum number of information resources, with respect to which it is possible to maintain the level of security as part of the 𝐾𝐵𝑥 th security configuration, 𝑂𝐵𝑢 – the set of information resources, with respect to which it is necessary to maintain the required level of security as of the time of occurrence of the emergency situation number "u", with the predefined 𝑂𝑢 and 𝑀𝐵𝑢 sets. 𝑂𝐵 – the set of of the information resources in the ISO determined at the stage of design. 𝑄2 (𝐾𝐵𝑥 ) = 𝑦2 =
1 𝑁𝑥
𝑥 𝑥 ∑𝑁 𝑖=1 𝑡𝑖 , 𝑥 ∈ 𝑋;
(20)
where: 𝑁𝑥 – the number of experiments conducted in the security system in the KBx th security configuration, t xi – the time of generation of the KBx th security configuration in the ith experiment. 1. 2.
The strive towards shortening the generation time allows to: reduce a possibility of interrupting the continuity of business processes in the organization, in particular the information processing process, reduce a possibility of interrupting the information receipt process in the ISO environment due to temporary break in operation of the system. 𝑥 𝑥 ̅𝑟𝑥 − 𝐾𝐾𝑅,𝑟 ̅𝑟𝑥 ≥ 𝐾𝐾𝑅,𝑟 ∑𝑟∈𝑅𝑥(𝐾 ) , 𝑗𝑒ż𝑒𝑙𝑖 ⋀𝑟∈𝑅𝑥 𝐾 𝑄3 (𝐾𝐵𝑥 ) = 𝑦3 = { , 𝑥 ∈ 𝑋; 𝑥 ̅𝑟𝑥 < 𝐾𝐾𝑅,𝑟 −1, 𝑗𝑒𝑠𝑒𝑙𝑖 ⋁𝑟∈𝑅𝑥 𝐾
(21)
where: ̅𝑟𝑥 – the average number of the rth type protection processes initiated as part of the KBx th security 𝐾 configuration, 𝑥 𝐾𝐾𝑅,𝑟 – the number of the rth type protection processes necessary to construct the security configuration critical in emergency situations, 𝑅𝑥 – the set of types of the protection processes initiated in the KBx th security configuration.
234
𝑄4 (𝐾𝐵𝑥 ) = 𝑦1 =
̿̿̿̿ ̿̿̿̿ 𝑢 𝑂𝐵𝑥𝑀𝐴𝑋 − 𝑂𝐵 ,𝑥 ̿̿̿̿ 𝑂𝐵
∈ 𝑋;
(23)
where: ̿̿̿̿̿ 𝑀𝐵𝑥𝑀𝐴𝑋 , ̿̿̿̿̿ 𝑀𝐵 𝑢 , ̿̿̿̿̿ 𝑀𝐵 – cardinality 𝑀𝐵𝑥𝑀𝐴𝑋 ,𝑀𝐵𝑢 , 𝑀𝐵 sets; whereas: 𝑀𝐵𝑥𝑀𝐴𝑋 – the set of the security mechanisms, including a maximum number of the security mechanisms implemented as part of the 𝐾𝐵𝑥 th security configuration 𝑀𝐵𝑢 – the set of security mechanisms, with respect to which it is necessary to maintain the required level of security as of the time of occurrence of the emergency situation number "u", with the predefined 𝑂𝑢 and 𝑃𝑂𝑢 sets. 𝑀𝐵 – the set of security mechanisms established at the stage of designing the security system. It is obvious that the value of such indicator should significantly exceed the critical value. 𝑚𝑖𝑛{∑
𝑗∈𝐵𝑖𝑥
𝑛𝑗𝑖 ,…,∑
𝑛 } 𝑗∈𝐵𝑖𝑥 𝑗𝐼𝑥
𝑄5 (𝐾𝐵𝑥 ) = 𝑦5 = {𝑚𝑎𝑥{∑𝑗∈𝐵𝑖 𝑛𝑗𝑖 ,…,∑𝑗∈𝐵𝑖 𝑥
𝑥
𝑛𝑗𝐼𝑥 }
, 𝑗𝑒ż𝑒𝑙𝑖 ⋁∈𝐼𝑥×𝐼𝑥(⋀𝑗∈𝐵𝑥 𝑛𝑖𝑗 ≠ 𝑛𝑘𝑗 );
(24)
1, 𝑗𝑒ż𝑒𝑙𝑖 ⋀∈𝐼𝑥×𝐼𝑥(⋀𝑗∈𝐵𝑥 𝑛𝑖𝑗 = 𝑛𝑘𝑗 ) where: 𝐼x – the set of numbers of technical security measures included in the KBx th of the security configuration. Bx – the set of numbers of the types of technical security measures used under the i th protection process, included in the KBx th security configuration, 𝑛𝑖𝑗 – the number of technical security measures of the jth type initiated under the ith protection process. The subject of the next article shall be the formulation of the multicriterial task for optimization of the security configuration and method of its execution. Summary The works on optimization of the security systems have been carried out worldwide for many years. The approach based on the information resource risk and current control of the utility properties of the security configuration is nothing new (STANIK et al., 2016; KIEDROWICZ, STANIK, 2017). The adoption of such rules in the security systems is aimed at protecting the processed information resources in a reasonable manner (the higher risk of losing security attributes, the more advanced protection measures). The conditions of the information society make it necessary for each security system to have the following properties: 1. continuous readiness, i.e. maintenance of the required level of current functionality, reliability and efficiency in terms of the maintenance of the desired security level, regardless of the emergency situations that may occur, 2. high operability in terms of controlling the performance properties, understood as timely and definite reaction to all emergency situations, and making steering decisions to restore efficiency of the security system with respect to the maintenance of the required security level within the required time limit, 3. high quality and security of the information processing processes - information processes through: a) reasonable adoption of steering decisions related to the initiation of appropriate security configurations, b) application of scientific methods and good practices while assessing the utility of the security system and choosing the best security configuration. The article does not provide the "recipe" for design and implementation of efficient security configurations, which are the basic link of the security systems. It is merely a proposal of the authors for partial solution of the problem related to the determination and construction of the security system, which would allow current maintenance of the security level of the information system in any organization. The proposed method for assessing utility of the security configuration is aimed at the reconfiguration and optimization of the security configuration, with an identified emergency situation – loss of the required level of security. The approach to the issue of security, aimed at the reconfiguration process, results, among other things, from the observations and long-term experience of the authors gained:
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•
during observations of the construction and implementation of such security systems in the organizations and corporations, • during research and implementation projects, • during scientific and research projects as well as seminar discussions relating to the issue of corporate security. • while studying the literature on security audits (POLACZEK, 2014; ISO, 2013; ISO 2015). The proposed concept of assessing the utility of the security configuration may be also used at the stage of designing the ISMS as the "privacy by design" principle recommended under the General Data Protection Regulation (GDPR)9. References EHRGOTT, M. 2005. Multicriterial optimization, 2nd edition, Springer, Berlin. HOFFMANN, R., KIEDROWICZ, M., STANIK, J. 2016. Evaluation of information safety as an element of improving the organization's safety management. 20th International Conference on Circuits, Systems, Communications and Computers (CSCC 2016), MATEC Web of Conferences, vol. 76. ISO / IEC 27002: 2015. Technika informatyczna - Techniki bezpieczeństwa - Kodeks postępowania w zakresie kontroli bezpieczeństwa informacji (Information technology - Security techniques - Code of conduct in the field of information security control). ISO / IEC 27004: 2013. Technika informatyczna - Techniki zabezpieczeń - Zarządzanie bezpieczeństwem informacji – pomiary (Information technology - Security techniques - Information security management - measurements). KIEDROWICZ, M. 2018. Metodyka zarządzania ryzykiem w bezpieczeństwie zasobów informacyjnych (Methodology of risk management in the security of information resources). Collegium of Economic Analysis Annals, 49: 287-305. KIEDROWICZ, M. 2017. Multi-faceted methodology of the risk analysis and management referring to the IT system supporting the processing of documents at different levels of sensitivity. 21st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017), MATEC Web of Conferences, vol. 125. KIEDROWICZ, M., STANIK, J. 2017. Models and method for the risk assessment of an intellectual resource. WSEAS Transactions on Information Science and Applications, vol. 14, p. 174-183. POLACZEK, T. 2014. Audyt bezpieczeństwa informacji w praktyce (Information security audit in practice), Helion, Warsaw. STANIK, J., NAPIÓRKOWSKI, J., HOFFMANN, R. 2016. Zarządzanie ryzykiem w systemie zarządzania bezpieczeństwem organizacji (The risk analysis and the risk management as basic components of the safety management system of the organization). Scientific Papers of the University of Szczecin, Economic Problems of Services. vol. 123, pp. 321-336. STANIK, J., KIEDROWICZ, M. 2017. Wieloaspektowa metodyka analizy i zarządzania ryzykiem procesów biznesowych (Multifaceted methodology of risk analysis and management of business processes). Scientific Papers of the University of Szczecin, Economic Problems of Services, 126:p. 339-3354.
The Regulation of the European Parliament and Council (EU) 2016/679 of April 27, 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data and the repeal of Directive 95/46/EC (General Data Protection Regulation). http://www.giodo.gov.pl/pl/1520284/9745. 9
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MULTICRITERIA OPTIMIZATION USED FOR THE INFORMATION SECURITY – IDEAL AND ANTI-IDEAL Maciej Kiedrowicz, Ph.D.
Cybernetics Faculty Military University of Technology Warsaw, Poland e-mail:
[email protected]
Jerzy Stanik, Ph.D.
Cybernetics Faculty Military University of Technology Warsaw, Poland e-mail:
[email protected] Abstract The article outlines the concept of assessing the utility of the security configuration, using two reference points (ideal and anti-ideal). The concept is in line with the natural intention of getting closer to the ideal point. In case of several such solutions, it is possible to obtain the solution that would move the least desirable situations as far as possible. In methodological context, the article consists of two layers. The first layer includes the security configuration model, including values describing the utility properties and partial criteria for measuring utility. The second layer refers to the issue of multicriteria optimization of the security configuration and proposed method of its resolution. Key words: security configuration, utility of configuration, polioptimization task, multicriteria optimization methods Introduction The efficiency of the information processing process in an organization to a large extent depends on the present qualitative properties, e.g. functionality, reliability, utility, security of the security system (SS). Therefore, it is crucial to appropriately control the current properties of the SS by generating the most desired security configurations1 from among the set of permissible solutions after the occurrence of an emergency situation2. The most desired security configuration is the one, which not only ensures maintenance of the required level of security, but also has the best utility properties. The issue was analyzed as the task of multicriteria optimization of the security configuration. The issue constitutes the main theme of the article and determines its framework. The subject of the article is composed of the following elements: 1. Development of models of the Security System and Security Configuration allowing to consider the interdependence between the current level of security and random changes of risk factors having material impact on the safety of the information processing processes. 2. Proposal of the values describing the utility properties of the security configuration and partial criteria for measuring their utility. 3. Formulation of the issue of multicriteria optimization of the security configuration and proposed method of its resolution. The re-configuration process is executed on the basis of the detailed Q reconfiguration function, which - from the point of view of its essence - constitutes a criterial function. Schematic representation of the configuration from the perspective of the reconfiguration process is in figure 1. The figure shows two important groups of elements: 1. basic components of the security configuration and some of the selected interdependencies between them,
Security configuration – a set of technical, organizational and human security measures as well as correlations between them, which reflect the quality, e.g. utility, security, performance and reliability features. 2 Emergency situation – an event that occurred due to the difference between the desired property of the SS and its current utility feature. 1
237
2.
basic components of the reconfiguration process and interdependencies between them, reflecting the manner of transformation from the current, ineffective security configuration into the desired security configuration. The RECONFIGURATION process
Deciding entity Directory (register of descriptions) Safety Configuration
ENVIRONMENT Outer and Inner
Requirements for the application of control and security measures
Vulnerabilities Register of current security measures and control mechanisms
protection
A set of current information processing operations Automatic data processing operations
Automated data processing operations
Traditional data processing operations
Vulnerabilitiesi
Information resources or personal data
Information processing subject
Administrator data
Desired security configuration
List of identified risks
Analysis and evaluation of risk
Register of owners
Legal, social, political environment, external entities
Random stream of threats
Risk
Hazard analysis and assessment subsystem
Random stream of threats
Current Safety Configuration
Resources - basic assets of the organization
Processes or activities Business
Technological environment
A set of acceptable security configurations
Risk Analysis Subsystem
Information processing subsystem
threat
areas factors risks
Automatic system Security Control
Required security level
Third party Data Subject
threat
Processing
threats
Configuration resources
Security Configuration Design and Service
Available mechanisms Safety
Fig. 1. Illustration of the configuration from the perspective of the reconfiguration process. Source: Own study.
After the occurrence of an emergency situation – loss of the required level of security, it is essential to generate permissible or optimum security configuration to efficiently continue the process of safe information processing in the information system of the organization (ISO). The optimum security configuration is generated among the set of the permissible solutions on the basis of the detailed Q reconfiguration function, which - from the point of view of its essence - constitutes a criterial function. Security configuration as a fundamental pillar of the information security system Information security system When compared with other definitions of the information security theory, the following definition seems to be the most accurate in terms of the requirements (STANIK et al., 2016; HOFFMANN et al., 2016) hereof: "The security system constitutes a part of the whole system for information security management with predefined actions concerning the design, monitoring and maintenance of the desired set of technical and organizational security measures, based on which it is possible to generate the required security configuration". The security system includes an organizational structure, planned actions, scopes of responsibilities and work tools allowing to control the current level of security of the entire organization as its elements. The security system constitutes one of the key links in the Information Security Management Systems (KIEDROWICZ, 2018; KIEDROWICZ, 2017; KIEDROWICZ, STANIK, 2017). Following the above definition, we shall adopt the ordered four as the model for the security system: 𝑆𝑍 =< 𝑃𝑂𝐹, 𝑃𝐷𝑍, ℂ, 𝐾𝐵 >,
238
(1)
where: 𝑃𝑆𝐹 - the subject of activities of the security system refers to a group of officers, who perform different roles in the data processing process, entitled to make decisions in that respect, 𝑃𝐷𝑍- the object of activities, i.e. the ISO objects, with respect to which the data must be processed and the security maintained at the required level, ℂ - the purpose of operations as defined in the object of activities, 𝐾𝐵 - the set of permissible security configurations, which constitutes a basic element of the object of activities in terms of maintaining the required level of security. The set of permissible security configurations shall be considered a comprehensive, consistent and non-contradictory subsystem of the security system aimed at reducing the probability of risk of assets or information system of the organization. Appropriate selection of such security configurations (set of permissible security configuration) and their efficient use allow to significantly reduce the cost of security of the organization, additionally ensuring appropriate level of security - tolerable level of protection. The above-mentioned elements are the subject of considerations in the subsequent subchapters of this article. Security configuration The grounds for the security configuration model shall be a correlation between the set of the information processing processes (recorded actions) and the set of activated technical, organizational, process and human security measures, after the occurrence of serious circumstances 3, hereinafter referred to as the emergency situation. In case of some types of the emergency situations, it may turn out that it is possible to safely process the data or maintain the required level of information security by various sets of activated security measures or protection processes. In such cases, it is necessary to choose one of them – the best from the point of view of a specific criterion. The following notation of any security configuration shall be introduced 𝐾𝐵𝑘𝑙 = 〈𝑂𝐵𝑘𝑙 , 𝑃𝑂𝑘 , 𝑀𝐵𝑙 〉
(2)
where: 𝑂𝐵𝑘𝑙 – the set of the data processing processes or operations (information resources and personal details) in the information system of the organization protected by the kl th security configuration, 𝑃𝑂𝑘 – the set of control mechanisms or protection processes aimed at meeting business, legal and other requirements for the processing of data, including personal details, which belong to the 𝑂𝐵𝑘𝑙 set, 𝑙 𝑀𝐵 – the set of security mechanisms creating the klth security configuration. The knowledge of the 𝐾𝐵𝑘𝑙 security configuration makes it possible to assign the 𝑀𝐵𝑙 set corresponding to each 𝑂𝐵𝑘𝑙 , set, with the predefined 𝑃𝑂𝑘 set of security mechanisms (organizational and technical security measures). The 𝐾𝐵𝑘𝑙 security configuration is implemented only when it is possible to assign such 𝑧𝑏𝑖ó𝑟 𝑃𝑂𝑘 , to the 𝑂𝐵𝑘𝑙 set, with predefined elements of the 𝑀𝐵𝑙 set, which shall guarantee the maintenance of the required level of security for the 𝑂𝐵𝑘𝑙 set of information resources. It may be assumed that as a result of the above, the 𝑂𝐵𝑘𝑙 set, with the predefined 𝑀𝐵𝑙 set, remains in correlation with the 𝑃𝑂𝑘 set, i.e. 𝑂𝐵 𝑘𝑙 𝐾𝐵𝑘𝑙 𝑃𝑂𝑘 . Therefore, it is possible to analyze the security configuration (2) as analogous to the terminal system, in which the elements from the 𝑂𝐵𝑘𝑙 set constitute input data, whereas the elements of the 𝑃𝑂𝑘 or 𝑀𝐵𝑙 set - output data. If a given 𝑧𝑔 ∈ 𝑂𝐵 data processing process may keep the required level of security through the 𝑝𝑜 ∈ P𝑂 protection process and subset of security measures from the 𝑀𝐵𝑙 set, then, by providing the 𝑅𝑥 feasibility correlation, ( 𝑅𝑥 ⊂ 𝑂𝐵 × P𝑂 × 2𝑀𝐵 ), in case of which the following formula 〈𝑧𝑔 , 𝑝𝑜𝑗 , 𝑀𝐵𝑛 〉 ∈ 𝑅𝑥 is correct, it is possible to determine the sets of protection processes and security measures used to protect a single 𝑧𝑔 data processing process. In the subsequent part of the article, only such situations are analyzed, which meet the following condition: (⋀𝑧𝑔⊂𝑂𝐵 𝑘𝑙 ⋁𝐾𝐵 ∈𝐾𝐵𝑘𝑙 ×2𝑃𝑂𝑔 ×2𝑀𝐵𝑔 𝐾𝐵𝑔 ⊂ 𝐾𝐵𝑘𝑙 ) ⟺ (𝑧𝑔 𝐾𝐵𝑔 𝑃𝑂𝑔 𝐾𝐵𝑔 𝑀𝐵𝑔 ). 𝑔
(3)
Serious circumstances – the occurrence of one of the following events: inefficiency or uselessness of the security measures, inability to perform the data processing due to significant disruption of the processing environment, e.g. the occurrence of a large number of risks or vulnerability factors, etc. 3
239
In the above-mentioned relation, 𝐾𝐵𝑔 means the security configuration of the g th information resource. While considering the (2) configuration, 𝐾𝐵𝑔 may be defined in the following manner: 𝐾𝐵𝑔 = 〈𝑧𝑔 , 𝑃𝑂𝑔 , 𝑀𝐵𝑔 〉,
(4)
where: 𝑧𝑔 – the data processing process protected by the gth security configuration, 𝑂𝑃𝑔 – the set of protection processes used to maintain the required level of security of the 𝑧𝑔 th data processing process, 𝑀𝐵𝑔 – the set of security measures creating the gth security configuration. The knowledge of the security configuration for the data processing process creates a possibility of assigning the 𝑀𝐵𝑔 set to the 𝑧𝑔 ∈ 𝑂𝐵 process, with the predefined 𝑃𝑂𝑔 set. On the basis of the above considerations, it is evident that the following condition is true for the analyzed class of the security systems: 𝐾𝐵𝑘𝑙 = ⋃𝑔: 𝑂𝐵𝑔∈ 𝑂𝐵𝑘𝑙 𝐾𝐵𝑔 .
(5)
In such case, any 𝐾𝐵𝑘𝑙 security configuration may be analyzed as a multitude of the security configurations for the particular 𝑧𝑔 ∈ 𝑂𝐵𝑘𝑙 data processing processes. Depending on the types of the data processing processes, which need to be protected through the protection processes and security measures, with the predefined security configuration, it is possible to activate, at a given moment, several or even a dozen or so 𝐾𝐵𝑔 action security configurations. It should be stressed that the data processing process subject to protection requires specific protection processes and technical or organizational security measures to ensure the acceptable security level. Values describing utility properties of the security system In case of an emergency situation related to the loss of the required level of security, it should be possible to activate (using protection processes and efficient security mechanisms - security measures) several different permissible security configurations. In such cases, it is necessary to choose one of them. It is obvious that the chosen security configuration must be the best in every aspect. Therefore, it is necessary to comprehensively assess - in terms of criteria functions - all variants of the permissible security configuration, including many values (characteristics) describing its utility and security properties. The rating shall be composed of many partial ratings. Such task may be executed only upon establishment of the set of representative characteristics reflecting the purpose of operations of the security system, manner of its operation and rules of use, determining the system's utility 4 or efficiency5. In such a manner, the subjectivity of the rating is decreased, thus, it is possible to: 1. reduce the number of criteria functions and quality indicators, which constitute grounds for such rating and choice of the optimal or suboptimal security configuration, 2. ensure proportionality of the significance (weight) of particular values and criteria functions, 3. reasonably assess the utility of the security system with a specific security configuration. 4. With the above in mind, it is possible to state the following with respect to the utility of the security configuration in the security system, distinguishing the following values (characteristics): 5. sensitivity6 of the security system to the loss of the required level of security, 6. time of generation of the security configuration, 7. efficiency of the operations of the information processing subsystem, 8. redundancy with respect to the technical security measures, 9. redundancy with respect to the protection processes. The above-mentioned values describing the properties of the security system with a specific security configuration do not constitute any closed set. It is possible to introduce other (not mentioned herein) values, which concern, for example, bandwidth or capacity of the security configuration. Let us introduce the following symbols: Ω – the set of values describing utility properties of the security configuration, Easy operation and meeting the actual needs of the user. Verification whether the undertaken activities produced the expected results. 6 ability of the security system to react to the change of type and amount of the information subject to further processing under the ISO, 4 5
240
𝑢 𝐾𝐵𝑑𝑜𝑝 – the set of permissible security configurations in case of the emergency situation (loss of security), number "u", Q – the set of distinguished criteria functions, 𝑊 – the set of vectors of implementation of particular values from the Ω set, 𝑓1−5 – the vector-valued function assigning a vector of implementation of particular values to each permissible security configuration. While considering the above values (describing the utility properties of the security configuration), the Ω set may be presented in the following manner:
𝛺 = {𝛺 𝑖 , 𝑖 = ̅̅̅̅ 1,5}.
(6)
Let us assume that for each 𝛺 𝑖 value, the 𝑊 𝑖 set of possible implementation is determined. In such case, the ordered set of implementation of the < 𝑓1 (𝐾𝐵), 𝑓2 (𝐾𝐵), 𝑓3 (𝐾𝐵), 𝑓4 (𝐾𝐵), 𝑓5 (𝐾𝐵) > value shall cor𝑢 respond to the permissible 𝐾𝐵 ∈ 𝐾𝐵𝑑𝑜𝑝 security configuration, recorded shortly 𝑓( 𝐾𝐵) or (7)
𝑤 =< 𝑤1 , 𝑤2 , 𝑤3 , 𝑤4 , 𝑤5 >. 𝑢 The functions assigning to each permissible 𝐾𝐵 ∈ 𝐾𝐵𝑑𝑜𝑝 configuration the implementation of its ith value, may be presented in the following manner:
𝑢 ̅ 𝐾𝐵𝑑𝑜𝑝 𝑓:
𝑢 𝑓𝑖 ∶ 𝐾𝐵𝑑𝑜𝑝 ⟶ 𝑊𝑖 , 𝑓𝑖 (𝐾𝐵) = 𝑤𝑖 , 𝑖 = 1,5. ⟶ 𝑊1 × 𝑊2 × 𝑊3 × 𝑊4 × 𝑊5 ; 𝑓(̅ 𝐾𝐵) = 𝑤 vector function.
(8) (9)
According to further considerations on 𝑤 vectors of implementation of the values describing the utility properties of the security configurations, it may be assumed that the security configurations with the same type of implementation of such values are indistinguishable and have the same use value for the assessor (in terms of utility). Such assumption is true only when the distinguished values reflect basic material utility properties of the security configuration. 𝑢 𝑢 The 𝑊 = 𝑓(𝐾𝐵𝑑𝑜𝑝 ) set of permissible 𝐾𝐵 ∈ 𝐾𝐵𝑑𝑜𝑝 security configurations does not have to include all possible combinations of implementation of the values (𝑊1 × 𝑊2 × 𝑊3 × 𝑊4 × 𝑊)) and usually does not include. Some types of implementation of the Cartesian product (𝑊1 × 𝑊2 × 𝑊3 × 𝑊4 × 𝑊)) correspond, in practice, to impermissible or unfeasible variants. The vectors of implementation of values reflecting the utility properties of the security configuration are not value determinants in general. The criteria functions, depending on the vectors of implementation of such values, are used to show the utility of the ̅ (KB) vectors defined in security configuration. Therefore, the criteria functions are the functions of 𝑤 or 𝑓: the following manner: 𝑢 𝑄𝑚 : 𝑊 ⟶ 𝑌𝑚 , 𝑚 = 1, 𝑀 or 𝑄𝑚 : 𝑓(𝐾𝐵𝑑𝑜𝑝 ) ⟶ 𝑌𝑚 , 𝑚 = 1, 𝑀
(10)
where: 𝑢 W, 𝑓(𝐾𝐵𝑑𝑜𝑝 ) – the sets of vectors of implementation of values, M – the number of distinguished criteria functions. The permissible security configurations may be rated using the following vectors: 𝑄(𝐾𝐵) = (𝑄1 (𝑓(𝐾𝐵)) , 𝑄2 (𝑓(𝐾𝐵)) , 𝑄3 (𝑓(𝐾𝐵)) , 𝑄4 (𝑓(𝐾𝐵)) , … , 𝑄𝑀 (𝑓(𝐾𝐵)) ) or
(11) 𝑄(𝐾𝐵) = (𝑄1 (𝐾𝐵), 𝑄2 (𝐾𝐵), 𝑄3 (𝐾𝐵), … , 𝑄𝑀 (𝐾𝐵) ).
̂ criteria functions, their extremization are not provided for, but preferences In case of 𝑄𝑚 , 𝑚 ∈ 𝑀 are to be established. The preferences mean that the level of each distinguished criterion must be achieved equally or exceeded unequally, i.e.: ̂ 𝑄𝑚 (𝐾𝐵) ≥ 𝑦̂𝑚 , 𝑚 ∈ 𝑀 241
(12)
where: 𝑦̂𝑚 – the level of preference (aspiration) for the mth criteria function, ̂ – the set of numbers of criteria functions, with respect to which no extremization is provided for. 𝑀 The aspiration level values are determined by experts from the security system team, depending on what is demanded from such system. To find optimal or suboptimal security configuration, the following stages must be executed: 1. Definition and measurement of values describing utility properties of the security configuration, 2. Definition of the set of criteria functions, 3. Formulation of the issue of multicriteria optimization, 4. Solution of the task of multicriteria optimization, The issues 1 and 2 constitute the subject of the article (STANIK, KIEDROWICZ, 2018), whereas the issues 3 and 4 constitute the subject of this article. Formulation of the issue of multicriteria optimization of the security configuration The formulation of the issue of a multicriteria optimization of the security configuration is justified only in such cases when in case of an emergency situation, it is possible to generate (with efficient technical, organizational and human resources) several permissible security configurations. In case of many different (with materially different values of the distinguished quantities) permissible security configurations, the problem is usually to choose the best configuration, which shall meet the requirements determined at the stage of designing the SS to the greatest extent possible. Such choice may be made only in the event when the assessor determines (for assessed security system class) the vector criteria function and domination dependency in the criterial space. Forms of the distinguished criteria functions In case of the security system, the utility of the security configuration may be rated and compared in a reliable manner using the following qualitative indicators 1. 𝑄1 (𝐾𝐵𝑥 ) - sensitivity of the security system to the loss of the required level of security, 2. 𝑄2 (𝐾𝐵𝑥 ) - time of generation of the security configuration, 3. 𝑄3 (𝐾𝐵𝑥 ) - efficiency of the operations of the information processing subsystem, 4. 𝑄4 (𝐾𝐵𝑥 ) - redundancy with respect to the technical security measures, 5. 𝑄5 (𝐾𝐵𝑥 ) - assessment of even load of the security configuration with the technical security measures The above-mentioned indicators are defined in the following manner: 𝑄1 (𝐾𝐵𝑥 ) = 𝑦1 =
̿̿̿̿ 𝑂𝐵𝑥𝑀𝐴𝑋 − ̿̿̿̿ 𝑂𝐵𝑢 ,𝑥 ̿̿̿̿ 𝑂𝐵
∈ 𝑋;
(13)
where: ̿̿̿̿𝑥𝑀𝐴𝑋 , 𝑂𝐵 ̿̿̿̿ 𝑢 , 𝑂𝐵 ̿̿̿̿ – cardinality 𝑂𝐵𝑥𝑀𝐴𝑋 ,𝑂𝐵𝑢 , 𝑂𝐵 sets; 𝑂𝐵 whereas: 𝑂𝐵𝑥𝑀𝐴𝑋 – the set of information resources, including a maximum number of information resources, with respect to which it is possible to maintain the level of security as part of the 𝐾𝐵𝑥 th security configuration, 𝑢 𝑂𝐵 – the set of information resources, with respect to which it is necessary to maintain the required level of security as of the time of occurrence of the emergency situation number "u", with the predefined 𝑂𝑢 and 𝑀𝐵𝑢 sets. 𝑂𝐵 – the set of of the information resources in the ISO determined at the stage of design. 𝑄2 (𝐾𝐵𝑥 ) = 𝑦2 =
1 𝑁𝑥
𝑥 𝑥 ∑𝑁 𝑖=1 𝑡𝑖 , 𝑥 ∈ 𝑋;
(14)
where: 𝑁𝑥 – the number of experiments conducted in the security system in the KBx th security configuration. t xi – the time of generation of the KBx th security configuration in the ith experiment. The strive towards shortening the generation time allows to: 242
1. 2.
reduce a possibility of interrupting the continuity of business processes in the organization, in particular the information processing process, reduce a possibility of interrupting the information receipt process in the ISO environment due to temporary break in operation of the system. 𝑥 𝑥 ̅𝑟𝑥 − 𝐾𝐾𝑅,𝑟 ̅𝑟𝑥 ≥ 𝐾𝐾𝑅,𝑟 ∑𝑟∈𝑅𝑥(𝐾 ) , 𝑗𝑒ż𝑒𝑙𝑖 ⋀𝑟∈𝑅𝑥 𝐾 𝑄3 (𝐾𝐵𝑥 ) = 𝑦3 = { , 𝑥 ∈ 𝑋; 𝑥 𝑥 ̅𝑟 < 𝐾𝐾𝑅,𝑟 −1, 𝑗𝑒𝑠𝑒𝑙𝑖 ⋁𝑟∈𝑅𝑥 𝐾
(15)
where: ̅𝑟𝑥 – the average number of the rth type protection processes initiated as part of the KBx th security 𝐾 configuration, 𝑥 𝐾𝐾𝑅,𝑟 – the number of the rth type protection processes necessary to construct the security configuration critical in emergency situations, 𝑅𝑥 – the set of types of the protection processes initiated in the KBx th security configuration. 𝑄4 (𝐾𝐵𝑥 ) = 𝑦1 =
̿̿̿̿ ̿̿̿̿ 𝑢 𝑂𝐵𝑥𝑀𝐴𝑋 − 𝑂𝐵 ,𝑥 ̿̿̿̿ 𝑂𝐵
∈ 𝑋;
(16)
where: ̿̿̿̿̿ 𝑀𝐵𝑥𝑀𝐴𝑋 , ̿̿̿̿̿ 𝑀𝐵 𝑢 , ̿̿̿̿̿ 𝑀𝐵 – cardinality 𝑀𝐵𝑥𝑀𝐴𝑋 ,𝑀𝐵𝑢 , 𝑀𝐵 sets; whereas: 𝑀𝐵𝑥𝑀𝐴𝑋 – the set of the security mechanisms, including a maximum number of the security mechanisms implemented as part of the 𝐾𝐵𝑥 th security configuration 𝑢 𝑀𝐵 – the set of security mechanisms, with respect to which it is necessary to maintain the required level of security as of the time of occurrence of the emergency situation number "u", with the predefined 𝑂𝑢 and 𝑃𝑂𝑢 sets. 𝑀𝐵 – the set of security mechanisms established at the stage of designing the security system. It is obvious that the value of such indicator should significantly exceed the critical value. 𝑚𝑖𝑛{∑
𝑗∈𝐵𝑖𝑥
𝑛𝑗𝑖 ,…,∑
𝑛 } 𝑗∈𝐵𝑖𝑥 𝑗𝐼𝑥
𝑄5 (𝐾𝐵𝑥 ) = 𝑦5 = {𝑚𝑎𝑥{∑𝑗∈𝐵𝑖 𝑛𝑗𝑖 ,…,∑𝑗∈𝐵𝑖 𝑥
𝑥
𝑛𝑗𝐼𝑥 }
, 𝑗𝑒ż𝑒𝑙𝑖 ⋁∈𝐼𝑥×𝐼𝑥(⋀𝑗∈𝐵𝑥 𝑛𝑖𝑗 ≠ 𝑛𝑘𝑗 );
(17)
1, 𝑗𝑒ż𝑒𝑙𝑖 ⋀∈𝐼𝑥×𝐼𝑥(⋀𝑗∈𝐵𝑥 𝑛𝑖𝑗 = 𝑛𝑘𝑗 ) where: 𝐼x – the set of numbers of technical security measures included in the KBx th of the security configuration, Bx – the set of numbers of the types of technical security measures used under the i th protection process, included in the KBx th security configuration, 𝑛𝑖𝑗 – the number of technical security measures of the jth type initiated under the ith protection process. Formulation of the issue of multicriteria optimization of the security configuration Having established: 𝑢 ̂ 𝑑𝑜𝑝 𝐾𝐵 – the set of permissible security configurations in case of an emergency situation (loss of security), number "u", with respect to which tighten requirements for the values describing their utility properties are met Q – vector criteria function, ≥ – domination dependency in the criteria space. The task of multicriteria optimization of the security configuration may be noted in the following manner (CICHOSZ, BOREK, 2007; PŁONKA, 2013): 𝑢 ̂ 𝑑𝑜𝑝 (𝐾𝐵 , 𝑄, ≥),
whereas: 1. The set of permissible security configurations may have the following form: 243
(18)
𝑢 𝑢 ̂ 𝑑𝑜𝑝 𝐾𝐵 = {𝐾𝐵𝑥 ∈ 𝐾𝐵𝑑𝑜𝑝 ∶ 𝑄2 (𝐾𝐵𝑥 ) ≤ 𝑇𝑑𝑜𝑝 ∧ 𝑄3 (𝐾𝐵𝑥 ) ≥ 0, 𝑥 ∈ 𝑋}
(19)
where: 𝑢 ̂ 𝑑𝑜𝑝 𝐾𝐵 – the set of permissible security configurations in case of the emergency situation (loss of security), number "u", defined in the following manner: 𝑄2 (𝐾𝐵𝑥 ) – the time of generation of the 𝐾𝐵𝑥 th security configuration, 𝑇𝑑𝑜𝑝 – permissible time of generation of the 𝐾𝐵𝑥 th security configuration, 𝑄3 (𝐾𝐵𝑥 ) − efficiency indicator of the operations of the information processing subsystem, 𝑢 ̂ 𝑑𝑜𝑝 𝑋 – the set of indices of the elements in the 𝐾𝐵 set, 2.
Vector criteria function is defined in the following manner: 𝑢 ̂ 𝑄: 𝐾𝐵𝑑𝑜𝑝 ⟶ 𝑌, 𝑄( 𝐾𝐵𝑥 ) = 𝑦
(20)
where: 𝑦 – the vector of partial rating of security configurations, 𝑌 – the criteria space defined in the following manner: 𝑢 ̂ 𝑑𝑜𝑝 𝑌 = {𝑦 = 𝑄(𝐾𝐵𝑥 ) ∈ ℛ 5 : 𝐾𝐵𝑥 ∈ 𝐾𝐵 },
(21)
whereas: 𝑄(𝐾𝐵𝑥 )– the rating vector of the 𝐾𝐵𝑥 th security configuration in the following form: 𝑄(𝐾𝐵𝑥 ) = (𝑄1 (𝐾𝐵𝑥 ), 𝑄2 (𝐾𝐵𝑥 ), 𝑄3 (𝐾𝐵𝑥 ), 𝑄4 (𝐾𝐵𝑥 ), 𝑄5 (𝐾𝐵𝑥 ));
(22)
where particular components of the 𝑄(𝐾𝐵𝑥 ) rating vector for the 𝐾𝐵𝑥 security configuration shall be construed in the following manner: 𝑄1 (𝐾𝐵𝑥 ) = 𝑦1 – indicator of sensitivity of the security system to the loss of the required level of security, 𝑄2 (𝐾𝐵𝑥 ) = 𝑦2 – time of generation of the security configuration, 𝑄3 (𝐾𝐵𝑥 ) = 𝑦3 – efficiency indicator of the operations of the information processing subsystem, with the predefined security configuration, 𝑄4 (𝐾𝐵𝑥 ) = 𝑦4 – redundancy indicator with respect to the technical security measures, 𝑄5 (𝐾𝐵𝑥 ) = 𝑦5 – indicator of even load of the security configuration with the technical security measures. Selection criteria of optimal security configuration: 𝑄1 (𝐾𝐵𝑥 ) = 𝑦1 =
̿̿̿̿𝑥𝑀𝐴𝑋 − ̿̿̿̿ 𝑂𝐵 𝑂𝐵 𝑢 ⟶ 𝑚𝑎𝑥 ̿̿̿̿ 𝑂𝐵 𝑁𝑥
1 𝑄2 (𝐾𝐵𝑥 ) = 𝑦2 = − ∑ 𝑡𝑖𝑥 ⟶ 𝑚𝑎𝑥 𝑁𝑥 𝑖=1
𝑥 ̅𝑟𝑥 − 𝐾𝐾𝑅,𝑟 𝑄3 (𝐾𝐵𝑥 ) = 𝑦3 = ∑ (𝐾 ) ⟶ 𝑚𝑎𝑥 𝑟∈𝑅𝑥
̿̿̿̿ 𝑂𝐵𝑥𝑀𝐴𝑋 − ̿̿̿̿ 𝑂𝐵 𝑢 ⟶ 𝑚𝑎𝑥 ̿̿̿̿ 𝑂𝐵 𝑚𝑖𝑛 {∑𝑗∈𝐵𝑖 𝑛𝑗𝑖 , … , ∑𝑗∈𝐵𝑖 𝑛𝑗𝐼𝑥 } 𝑥 𝑥 𝑄5 (𝐾𝐵𝑥 ) = 𝑦5 = ⟶ 𝑚𝑎𝑥 ∑ 𝑚𝑎𝑥 {∑𝑗∈𝐵𝑖 𝑛𝑗𝑖 , … , 𝑗∈𝐵𝑖 𝑛𝑗𝐼𝑥 } 𝑄4 (𝐾𝐵𝑥 ) = 𝑦1 =
𝑥
244
𝑥
Methods of resolving the issue of multicriteria optimization of the security configuration 𝑢 ̂ 𝑑𝑜𝑝 Resolution of the (𝐾𝐵 , 𝑄, ≥) polyoptimization task comes down to the establishment of the set of dominating solutions. The set has the following form:
𝑢 ̇ ∈ 𝐾𝐵 ̂ 𝑑𝑜𝑝 ̇ )= 𝐾𝐵𝐷≥ = {𝐾𝐵 ∶ 𝑄𝑚 (𝐾𝐵
̅̅̅̅}. 𝑚𝑎𝑥 𝑄𝑚 (𝐾𝐵), 𝑚 = 1,5
̂𝑢 𝐾𝐵∈𝐾𝐵 𝑑𝑜𝑝
(23)
Once nonempty 𝐾𝐵𝐷≥ set is obtained, the procedure is finished. Every 𝐾𝐵 ∈ 𝐾𝐵𝐷≥ security configuration is characterized by the values describing its utility proper𝑢 ̂ 𝑑𝑜𝑝 ties. Better than the security configuration belonging to the 𝐾𝐵 \𝐾𝐵𝐷≥ set. Any security configuration from ≥ the 𝐾𝐵𝐷 set of dominating solutions may be considered the optimal security configuration in terms of the adopted criterion. In practice, it is often the case that the set of dominating solutions is an empty set. In such situation, it is essential to choose the solution from the set of permissible solutions. The set of permissible solutions is usually quite "extensive". Therefore, a practical dilemma arises: which solution should be applied? A comparison of the permissible security configurations using the rating vector is difficult and labor-intensive. Therefore, it is recommended to use such solution, which would be a natural generalization of the optimization concept, including one global criteria function aggregating all partial criteria functions. The methods of reliable measurement of the values describing the utility properties of the security configurations and methods for determining the values of particular criteria functions are known. However, no general methods for aggregating partial ratings are available. The aggregation process requires great caution. It is especially misleading to aim at achieving general rating in the form of one number. According to fig. 2, when adopting, for the purpose of general rating of the security configuration utility, the "distance" of the analyzed security configuration from the model configuration (e.g. determined at the stage of designing the SS), many materially different permissible security configurations (with materially different values of the distinguished quantities) produce such results.
Master configuration ( Ideal ) Safety configurations about the same distance from ideal
Fig. 2. Comparison of various security configurations with the model rating7. Source: Own study.
Figure 2 shows potential problems that may be encountered in case of aggregating partial rates of the utility of the security configuration. By distinguishing many partial quality indicators, it is possible to assess the utility of the permissible security configurations in the form of a vector (10). Therefore, a ranking of the rated security configurations from "the best" to "the worst" and selection of the only one best security configuration (without ordering other configurations) may be a difficult task. It is an exceptional situation when one of the rated security configurations is better than other configurations in terms of all criteria (i.e. the value of each criteria function for such security configuration is higher or lower than the value of the same criteria function for other permissible security configurations (Fig.3)). Such situation means that there is an nonempty set of dominating solutions.
This and other figures show the limitation to the two-dimensional space (resulting from the fact that it is easier to illustrate) despite the fact that five partial criteria functions are being analyzed. The distance in the figure is the Euclidean distance (parameter p=2 was adopted). 7
245
Ideał
The best security configuration
Fig. 3. Domination of one security configuration over others. Source: Own study.
A serious problem occurs when none of the permissible security configurations significantly "dominates" over other security configurations (see: fig. 4).
Ideal
Fig. 4. Absence of domination of one permissible security configuration over others. Source: Own study.
In the events when it is impossible to explicitly indicate "the best" security configuration in the set of permissible solutions, it is necessary to find a way of ordering the security configurations (or at least a 𝑢 ̂ 𝑑𝑜𝑝 method for finding the best one). It is possible to reject such security configurations from the 𝐾𝐵 set of permissible security configurations, whose properties are worse (i.e. the value of each criteria function is less satisfactory to the assessor) than those of others (see: fig. 5).
KB worse than
KB worse than
KB worse than
Fig. 5. Domination of 𝐾𝐵1 , 𝐾𝐵2 𝑖 𝐾𝐵3 over other permissible security configurations. Source: Own study.
246
The set of security configurations, which may not be eliminated in the above-mentioned manner, shall be called the set of undominated security configurations. Such set (BLASZCZYNSKI et al., 2007) constitutes an inverse image of the set of undominated results. (24)
𝐾𝐵𝑁≥ = 𝑄−1 (𝑌𝑁≥ ). The set of undominated results has the following form:
(25)
𝑌𝑁≥ = {𝑦 ∈ 𝑌 ∶ 𝑛𝑖𝑒 𝑖𝑠𝑡𝑛𝑖𝑒𝑗𝑒 𝑧 ∈ 𝑌, 𝑧 ≠ 𝑦, ż𝑒 ( 𝑧, 𝑦) ∈ ≥ }.
The manner of choosing the suboptimal security configuration from the set of undominated solutions may be as follows: 1. First, such solutions that do not achieve the required level of values of the determined criteria functions shall be eliminated from the set. The representation of narrowing the set of permissible solutions is in fig. 6.
IDEAL A narrow set of non-dominated solutions
Set of solutions eliminated
Fig.6. Narrowed set of undominated solutions. Source: Own study. 𝑦̂
The narrowed 𝐾𝐵 ≡ 𝐾𝐵𝑁 set may be defined recursively 𝑦̂
𝑦̂
𝑦̂
𝐾𝐵𝑚 = {𝐾𝐵 ∈ 𝐾𝐵𝑚−1 ∶ 𝑄𝑚 (𝐾𝐵) ≥ 𝑦̂𝑚 }, 𝑚 ∈ {1,2,3,4,5}, 𝐾𝐵𝐷 = 𝑌𝑁≥
(26)
where: 𝑦̂𝑚 – the level of aspiration (preference) for the mth criteria function. The process of narrowing the set may be continued until a single solution is obtained through the change of the value of 𝜂𝑚 , 𝑚 = 1,5 coefficients. When high values of 𝜂𝑚 coefficients are adopted, the idea of such behavior may be distorted by eliminating (at some stage of the recursive procedure) all undominated 𝑦̂ solutions. Therefore, the values of 𝜂𝑚 coefficients should be selected from the following ranges: ̇𝑚 ≤ 𝜂𝑚 ≤ 𝑄𝑚 1, 𝑚 ∈ {1,2,3,4,5}, where 𝑄̇𝑚 = 𝑚𝑎𝑥 𝑄𝑚 (𝐾𝐵), not to allow acceptance of the situation. If the aforesaid sit≥ ̂𝑁 𝐾𝐵∈𝐾𝐵
uation occurs, i.e. ⋁𝑚∈{1,2,3,4,5} 𝐾𝐵𝑚 = 𝜙 , the 𝜂𝑚 (𝑚 ∈ {1,2,3,4,5} coefficient should be decreased so that the 𝜂 ⋀𝑚∈{1,2,3,4,5} 𝐾𝐵𝑚 ≠ 𝜙 conditions are met. Once a one-element 𝐾𝐵 set is obtained, the procedure is finished. 2.
A method of compromise solutions may be suggested for the set of the security configurations, which remained after the elimination process (described in point 1), as the continuation of the procedure. 247
The method is considered one of the ways of solving the polyoptimization tasks, using the so-called scalarization of partial criteria. ̅̅̅̅ set. Let us assume that X security configurations numbered 𝑥 ∈ 𝑋̅ = {1,2, … , 𝑋} are left in the 𝐾𝐵 The configurations shall be rated using five (M = 5) different quality indicators. 𝑦𝑚𝑥 ∈ ℛ1 shall mean the value of the mth criteria function of the xth security configuration, wheres 𝑦𝑚 - the rating scale relating to the mth criteria function. 𝑀𝐼𝑁
𝑀𝐴𝑋
𝑦𝑚 ∈ [𝑦𝑚 , 𝑦𝑚
(27)
] ∈ ℛ1
where: 𝑀𝐼𝑁 𝑀𝐴𝑋 𝑦𝑚 , 𝑦𝑚 – the minimum and maximum value of the criteria function, number "m". Furthermore, let us assume that the security configuration is highly rated if the value achieved by every criteria function is higher. At the beginning, it is crucial to normalize the value of criteria functions, e.g. in the following manner: 𝑦𝑚𝑥 𝑀𝐴𝑋 𝑦𝑚 − 𝑦𝑚
𝑦𝑚𝑥 =
or
𝑦𝑚𝑥 =
𝑦𝑚𝑥
𝑀𝐴𝑋
𝑦𝑚
.
(28)
The 𝑦𝑥 = (𝑦1𝑥 , 𝑦2𝑥 , 𝑦3𝑥 , 𝑦4𝑥 , 𝑦5𝑥 , ) ∈ ℛ 5 vector shall be considered representative of the security configuration number "x". The set 𝑁
(29)
𝑌 = {𝑦𝑚 ∈ ℛ 5 ∶ 𝑥 ∈ 𝑋}. shall be called the normalized space for the security configuration ratings. The vector 𝑁,𝑀𝐴𝑋
𝑦𝑚
𝑀𝐴𝑋
= (𝑦1
𝑀𝐴𝑋
, 𝑦2
𝑀𝐴𝑋
, 𝑦3
𝑀𝐴𝑋
, 𝑦4
𝑀𝐴𝑋
, 𝑦5
(30)
)
shall be called the normalized ideal point, representing the model (ideal) security configuration. To determine the "total" scalar rating of the security configuration, the following function shall be used: 𝑦
𝑀𝐴𝑋
𝑅𝑝
(𝑦𝑥 ) = ‖𝑦
𝑝
𝑁,𝑀𝐴𝑋
𝑁 𝑀𝐴𝑋 − 𝑦𝑥 ‖ = √∑𝑀 − 𝑦𝑚𝑥 )𝑝 , 𝑦𝑚𝑥 ∈ 𝑌. 𝑚=1( 𝑦𝑚 𝑝
(31)
̅̅̅̅ set (the closest to the ideal in terms of The set of "the best" security configurations from the 𝐾𝐵 the adopted distance measure) shall be determined in the following manner: 𝐾𝐵 𝑅
𝑦
𝑁,𝑀𝐴𝑋
𝑁,𝑀𝐴𝑋
= 𝑄 −1 (𝑌
𝑅𝑦
(32)
).
𝑁,𝑀𝐴𝑋
𝑅𝑦
In the above formulation, 𝑌 is the set of "the best" ratings of the security configuration from the ideal to the closest to the ideal in terms of the adopted distance measure. The set has the following form: 𝑌
𝑅𝑦
𝑁,𝑀𝐴𝑋
𝑁,𝑂
= {𝑦𝑥
𝑦
𝑀𝐴𝑋
∈ 𝑌: 𝑅𝑝
𝑁,𝑂
𝑦
(𝑦𝑥 ) = 𝑚𝑖𝑛𝑁 𝑅𝑝 𝑁
𝑦𝑥 ∈𝑌
𝑀𝐴𝑋
(𝑦𝑥 ), 𝑥 ∈ 𝑋̂ }
(33)
where: 𝑁
𝑌 – the normalized criteria space (all values of criteria functions fall within the range < 0,1 >). 𝑅𝑦
𝑁,𝑀𝐴𝑋
𝑁
𝑁
(𝑦𝑥 ) − norm in the 𝑌 criteria space (distance of the 𝑦𝑥 xth rating of the security configura𝑀𝐴𝑋
tion from the ( 𝑦𝑚 The norm in the 𝑅 𝑦
ideal point)).
𝑁,𝑀𝐴𝑋
𝑁
𝑁
(𝑦𝑥 ) − of the 𝑌 criteria space is defined in the following manner: 248
𝑅𝑦
𝑁,𝑀𝐴𝑋
𝑁
(𝑦𝑥 ) = ‖𝑦
𝑁,𝑀𝐴𝑋
2
𝑁 𝑀𝐴𝑋 − 𝑦𝑥 ‖= √∑5𝑚=1( 𝑦𝑚 − 𝑦𝑚𝑥 )2 .
(34)
Fig. 7 shows graphic interpretation of the assessed distance of the security configuration for the two indicators: 𝑄1 and 𝑄3 .
IDEAŁ ,
,
„best configurations”
Fig. 7. Assessed distance of the security configurations. Source: Own study.
In practice, there may be several rated security configurations from the ̅̅̅̅ 𝐾𝐵 set, with the same assessed distance from the ideal point (fig. 7). It means that the set 𝑌
𝑅𝑦
𝑀𝐴𝑋
𝑁,𝑂
= {𝑦𝑥
𝑦
∈ 𝑌: 𝑅𝑝
𝑀𝐴𝑋
𝑁,𝑂
𝑦
𝑀𝐴𝑋
(𝑦𝑥 ) = 𝑚𝑖𝑛𝑁 𝑅𝑝 𝑁
𝑦𝑥 ∈𝑌
(𝑦𝑥 ), 𝑥 ∈ 𝑋̂ } ≠ 𝜙.
(35)
In such cases, it is essential to choose the solution from the set of undominated solutions. 𝑁,𝑀𝐴𝑋
𝑦 𝐾𝐵𝑁𝑅
−1
= 𝑄 (𝑌
𝑅𝑦
𝑁,𝑀𝐴𝑋
),
(36)
1. 2.
Choose any solution and complete the procedure, Choose the solution using the method of the security configuration rating with respect to the antiideal point. Therefore, two criteria for the configuration rating shall be used: 1. distance from the ideal, which should be the shortest, 2. distance from the anti-ideal, which should be the longest. It should be stressed that moving further away from the anti-ideal does not have to mean getting closer to the ideal (fig. 8). The issue of assessing the utility of the security configurations, using two reference points (the ideal and anti-ideal - bipolar optimization) was omitted in this article. Summary The security of the information (including personal details) processing processes (operations) to a large extent depends on the current utility properties of the security configuration. The desired security configuration may be obtained by reconfiguring the security system. The most desired security configuration is the one which not only allows to process the information resources so as to ensure the required level of security or maintain the continuity of security attributes, but also the one which is characterized by the best utility properties.
249
IDEAL
ANTYIDEAL Fig. 8. Different distances from the anti-ideal with the same distance from the ideal. Source: Own study.
On the basis of the considerations included in this article, the following conclusions may be drawn: To eliminate the impact of a failure – to maintain the required level of the information security, it is justified to distinguish the two phases: a) Definition of the set of permissible security configurations of a given emergency situation, b) Optimization of the security configuration in case of a given emergency situation. 2. To optimize the security configuration, it is intentional to use the method of resolution of such task, as suggested in chapter 2.3. 3. The suggested method for controlling current utility properties of the security configuration, as the basic element of the security system, should constitute an integral part of the Information Security Management System. 4. The proposed concept of assessing the utility of the security configuration may be also used at the stage of designing the ISMS as the "privacy by design" principle recommended under the General Data Protection Regulation (GDPR) (Regulation (EU) No. 2016/679 of the European Parliament and the Council). 5. The article does not provide the "recipe" for design and implementation of efficient security configurations, which are the basic link of the security systems. It is merely a proposal of the authors for partial solution of the problem related to the determination and construction of the security system, which would allow current maintenance of the security level of the information system in any organization. 6. The proposed method for assessing utility of the security configuration is aimed at the reconfiguration and optimization of the security configuration, with an identified emergency situation – loss of the required level of security. 7. The approach to the issue of security, aimed at the reconfiguration process, results, among other things, from the observations and long-term experience of the authors gained: • during observations of the construction and implementation of such security systems in the organizations and corporations, • during research and implementation projects, • during scientific and research projects as well as seminar discussions relating to the issue of corporate security. 8. Using the results outlined herein, it is recommended to pursue further research in the following areas: • improvement of the structure of the security configuration models, while considering, among other things, the guidelines, motives and recommendations under the GDPR, • increase of precision of the proposed model by including more detailed utility properties of the security configuration and qualitative features of the security system. The authors are convinced that further research in the above-mentioned fields may lead to the justified construction of the data protection systems or security systems with better utility parameters. 1.
250
References BLASZCZYŃSKI, J., GRECO, S., SŁOWIŃSKI, R. 2007. Multi-criteria classification - A new scheme for application of dominance-based decision rules. European Journal of Operational Research, 181(3). CICHOSZ, K., BOREK, T. 2007. Wprowadzenie do optymalizacji wielokryterialnej (Introduction to multi-criteria optimization), AGH, Krakow. HOFFMANN, R., KIEDROWICZ, M., STANIK, J. 2016. Risk management system as the basic paradigm of the information security management system in an organization. 20th International Conference on Circuits, Systems, Communications and Computers (CSCC 2016), MATEC Web of Conferences, vol. 76. KIEDROWICZ, M. 2018. Metodyka zarządzania ryzykiem w bezpieczeństwie zasobów informacyjnych. (Methodology of risk management in the security of information resources). In: Collegium of Economic Analysis Annals, Publisher: Warsaw School of Economics (SGH) Collegium of Economic Analysis, vol 49, p. 287-305. KIEDROWICZ, M. 2017. Multi-faceted methodology of the risk analysis and management referring to the IT system supporting the processing of documents at different levels of sensitivity. 21st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017), MATEC Web of Conferences, vol. 125. KIEDROWICZ, M., STANIK, J. 2017. Models and method for the risk assessment of an intellectual resource. WSEAS Transactions on Information Science and Applications, 14: 174-183. PŁONKA, S., 2013. Wielokryterialna optymalizacja procesów wytwarzania części maszyn (Multicriteria optimization of manufacturing processes of machine parts), WNT, Warsaw. ROZPORZĄDZENIE Parlamentu Europejskiego i Rady (UE) 2016/679 z dnia 27 kwietnia 2016 r. w sprawie ochrony osób fizycznych w związku z przetwarzaniem danych osobowych i w sprawie swobodnego przepływu takich danych oraz uchylenia dyrektywy 95/46/WE - ogólne rozporządzenie o ochronie danych (Regulation (EU) No 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC - General Data Protection Regulation), http://www.giodo.gov.pl/pl/1520284/9745. STANIK, J., NAPIÓRKOWSKI, J., HOFFMANN, R. 2016. Zarządzanie ryzykiem w systemie zarządzania bezpieczeństwem organizacji (The risk analysis and the risk management as basic components of the safety management system of the organization). Scientific Papers of the University of Szczecin, Economic Problems of Services. vol. 123, p. 321-336.
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THE ROLE OF THE LAND ADMINISTRATION SYSTEM IN THE PROCESS OF DEVELOPING AND UPDATING THE LAND PARCEL IDENTIFICATION SYSTEM – A CASE STUDY OF HIGH NATURE VALUE FARMLAND IN NORTH-EASTERN POLAND Katarzyna Kocur-Bera, Ph.D.
University of Warmia and Mazury in Olsztyn, Faculty of Geodesy, Geospatial and Civil Engineering, Institute of Geoinformation and Cartography, Olsztyn, Poland e-mail:
[email protected]
Klaudia Piórkowska, M.Sc. OPGK Olsztyn, Olsztyn, Poland Abstract This article analyzes the role of the Land Administration System in the process of developing and updating the Land Parcel Identification System. The compatibility of both systems was evaluated. The Land Parcel Identification System (LPIS) is a computerized database for identifying and monitoring eligibility for areabased subsidies. In Poland, the LPIS was developed after Poland had joined the European Union, adopted the Common Agricultural Policy and implemented the direct payment scheme for farmers. Farmers are eligible to direct payments based on the declared reference parcel. In the EU countries, the reference parcel has been defined based on various criteria (cadastral parcels, agricultural parcels, farmer’s blocks or physical blocks). In Poland, the reference parcel is a cadastral parcel. The article compares the databases of the Polish cadastral system and the LPIS. The analysis covered areas with identical descriptions of land-use type in both systems. The area, length and location of boundary points of the examined parcels were compared. The comparison involved agricultural land whose specifications have been updated. The results of the analysis revealed considerable differences in the compared databases. The noted discrepancies can probably be attributed to differences in the quality of source maps and materials as well as insufficient updates based on the results of local inspections. Keywords: real estate cadaster, Land Parcel Identification System, comparative analysis, land use Introduction The Polish land and building register is a public database containing information about real estate and property rights. Real estate cadasters are kept by counties which also operate numerical databases containing information about parcel boundaries in vector or raster form. The relevant information is regularly updated, and it constitutes a source of reference data for institutions and organizations, including the Agency for the Reconstruction and Modernization of Agriculture (ARiMR). Poland implemented the Common Agricultural Policy and the direct payment scheme for farmers upon its accession to the European Union. The value of the support provided to farmers is determined based on the cadastral model. The paying agency relied on land register data to develop the Land Parcel Identification System (LPIS). The Treaty of Accession defined the terms and conditions for implementing the Common Agricultural Policy in Poland, and it introduced the direct payment scheme for farmers. Polish farmers are entitled to financial support based on the area of farmed land. In the EU countries, direct payments for farmers are managed and monitored by paying agencies. The ARiMR is a Polish paying agency which manages financial aid under the Common Agricultural Policy and controls eligible areas and agricultural land. Direct payments complement and stabilize basic incomes in agriculture, contribute to good agricultural and environmental conditions, compensate for the costs associated with the fulfillment of EU requirements regarding product quality and production methods, contribute to environmental protection and sustainable practices in water management and the generation of energy from renewable sources. The EU operates two direct payment systems: • the Single Payment Scheme (SPS) which has been introduced in the old EU-15 countries as well as in Croatia, Malta and Slovenia. Direct subsidy payments are made to owners of agricultural land based on 252
entitlements. Payment entitlements provide farmers with the right to a predetermined amount per hectare of land. • the Single Area Payment Scheme (SAPS) which is a simplified system offered to the Member States that joined the EU in 2004 and later. The amount of the payment is calculated by dividing the country’s annual financial envelope by the respective agriculturally utilized area (reference area). The annual financial envelope is determined based on reference cereal yields, area of agricultural land and livestock population. The direct support scheme covers more than 1.4 million of Polish farmers, and it is the largest and the most important support mechanism for Polish rural areas. Agricultural producers have to meet the following eligibility criteria for direct payments: (a) the total area of reference parcels in a farm is minimum 1 ha (minimum 0.1 ha per land management unit), (b) land must be kept in good agricultural and environmental condition throughout the calendar year, (c) the farmer has been allocated an identification number in the national register of producers (UOPRSWB, 2015). Direct payments are granted based on the declared reference parcels. In Poland, a reference parcel is a cadastral parcel. The eligible area within a cadastral parcel is composed of land management units which may or may not be eligible for payments. A diagram of LPIS objects localized within a cadastral parcel is presented in Figure 1. cadastral parcel references parcel registered and economic area land management unit
Fig. 1. Diagram of LPIS objects localized within a cadastral parcel. Source: Own elaboration.
The EU Member States are under obligation to develop a system for managing and controlling the utilization of EU financial aid. The Integrated Administration and Control System (IACS) is a computerized tool for implementing the provisions of the Common Agricultural Policy and monitoring the distribution and utilization of the financial support for farmers (ARMiR, 2016). According to Regulation (EU) No. 1306/2013 of the European Parliament and of the Council, the IACS is a computerized database, an identification system for agricultural parcels, aid applications or payment claims and a system for the identification and recording of payment entitlements. The Land Parcel Identification System (LPIS) is part of the IACS. Pursuant to the provisions of Art. 70 of Regulation (EU) No. 1306/2013, the EU Member States are under obligation to establish an identification system for agricultural parcels based on maps, land registry documents and other cartographic references with the use of aerial and spatial orthoimagery and GIS techniques. In Poland, LPIS resources are developed based on digital orthophotomaps and the information found in land and building registers (UOKSEP, 2003). The purpose of the LPIS is to guarantee non-ambiguous identification of agricultural parcels declared for financial support and to determine their location in agricultural and geographic space. Parcels are identified based on the assigned territorial codes (TERYT) and parcel numbers in the land and building register. The LPIS is also used to verify the declared parcel area and the farmers’ payment entitlements. As of 2005, LPIS resources are developed with the use of GIS tools. The database consists of: (1) digital orthophotomaps covering the entire country, (2) boundaries of reference parcels in the form of vector maps, (2) land management units not eligible for payments in the form of vector maps. The LPIS resources are used for administrative control and explanatory proceedings after local inspections (SZDARIMR, 2015). In Poland, the LPIS is developed based on data from the land and building register concerning cadastral parcels, including agricultural land and soil classification data. In many cases, the boundaries of cadastral parcels constitute property/tenancy boundaries, they are easy to identify based on boundary points and field margins, their area is strictly defined, and the relevant data are released at no charge for IACS needs. In the early stages of development, LPIS was based on descriptive data from the land and building register (registered parcels of agricultural land with specified land-use type), and the relevant information was used to classify every parcel into one of the two categories: parcels intended for agricultural production and parcels not used for agricultural purposes (eligible or not eligible for payments). At present, the area of agricultural parcels in the LPIS is defined based on intersections between vector layers containing the boundaries of cadastral parcels and the boundaries of land management units. The area of parcels not 253
eligible for payments is subtracted from the area of cadastral parcels based on orthophotomap data. The graphical part of the LPIS database was developed with the use of cartographic materials from the land and building register with minimum horizontal accuracy corresponding to a topographic map in the 1:10 000 scale. Digital orthophotomaps were used when the eligibility of declared parcels could not be validated based on the existing data or maps. In Poland, agricultural land is highly fragmented; therefore, orthophotomaps are developed based on two standards: orthophotomaps with a resolution of 0.50 m (standard I) and orthophotomaps with a resolution of 0.25 m (standard II). Standard II covers approximately 25% of Poland’s territory, mainly its south-eastern regions which are characterized by high fragmentation of agricultural parcels. New aerial photographs covering most of Poland’s territory have been taken to meet the EU standards for orthophotomaps. In the remaining parts of the country, orthophotomaps have been developed based on archive resources (aerial photographs taken as part of the Phare 1997 project) and Ikonos satellite images (border zones, estimated resolution of 1 m). The LPIS relies on information from various registers and databases kept by government institutions: 1. National Center for Geodetic and Cartographic Documentation – data relating to administrative boundaries from the State Register of Borders (PRG), Database of Topographical Objects (BDOT) and databases of aerial and satellite images (ORTO), 2. County Centers for Geodetic and Cartographic Documentation – descriptive data and maps from the land and building register, maps of conservation areas, 3. Central Statistical Office – TERYT identifiers, 4. Ministry of the Environment – data relating to Natura 2000 areas, National Parks, landscape parks with boundary zones, nature reserves, protection task plans, environmental protection plans, nature and landscape conservation areas, geologically valuable areas, natural monuments, protected landscape areas, ecological corridors, 5. National Water Management Authority – hydrographic survey maps, areas with high risk of nitrate pollution, water intake protection zones, 6. General Directorate for National Roads and Motorways – vector data describing national roads and motorways (BRARMIR, 2015). Pursuant to the provisions of Regulation (EU) No. 1307/2013 of the European Parliament and of the Council, LPIS data have to be regularly updated. Digital orthophotomaps depicting land use types at the time the aerial image was captured are updated every 3 years, and they are highly reliable tools for determining the area of agricultural land eligible for financial aid. The anaglyph method (3D orthophotomap) has been recently introduced to improve the quality of the LPIS database. This 3D imaging technique supports spatial visualization and facilitates interpretation of the analyzed images (UOPRSWB, 2015). The LPIS database is also updated to account for changes in land use. The relevant information is supplied by farmers in the form of a graphic annex to a payment application. Pursuant to the provisions of Art. 17 point 5 of the Commission Implementing Regulation (EU) No. 809/2014, the beneficiary is required to unambiguously identify and declare the area, use and location of each agricultural parcel. If the information provided in the application is not valid or incomplete, the beneficiary has to make the relevant changes in the pre-established form. If necessary, the beneficiary should correct the reference data and indicate the valid boundaries of reference parcels on a map. The relevant changes are processed and entered into the LPIS system by the paying agency (PB.zs.058.1.2017). Eligible areas can also be controlled during local inspections. Local inspections are conducted to gather information about an agricultural parcel and its immediate vicinity within the boundaries of the declared reference parcels. Any discrepancies between GIS data and field data gathered during a local inspection are marked on parcel sketches with the use of postcontrol codes. The LPIS database is also updated to account for changes in source data, including in the land and building register where new data are introduced by county administrators (division and consolidation of cadastral parcels, system upgrades, changes in the name, number and registration number of cadastral districts). The relevant data are imported to the LPIS reference database in the cadastral data exchange standard (SWDE) (UOPRSWB, 2015). The aim of this study was to analyze the compatibility of LPIS and LAS data relating to a selected area in north-eastern Poland (in this part of the country, LAS resources are based on historical data from the Prussian cadaster). This is an important consideration since LPIS and LAS data constitute a basis for the payment of subsidies to farmers under the Common Agricultural Policy.
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Materials and Methods The analysis was performed based on the data obtained from the County Center for Geodetic and Cartographic Documentation in Olsztyn (vector boundaries of cadastral parcels and agricultural land, descriptive data with identifiers, area of cadastral parcels, land-use type and area of agricultural land) and the corresponding LPIS data obtained from the Olsztyn Branch of the Agency for the Restructuring and Modernization of Agriculture (vector reference boundaries, identifiers and area of reference parcels, maximum eligible area, vector boundaries of land management units, digital orthophotomap for 2016). The compatibility of land-use types in the evaluated cadastral parcels (and reference parcels) and agricultural land (land management units) was analyzed, and the boundaries of the studied objects were determined. The compatibility of LPIS and LAS data was analyzed in randomly selected objects. This approach was possible because the Polish LPIS/IACS system contains the “land management unit” category which corresponds to different land-use types in the LAS. The definitions of the land management units in the LPIS and the corresponding land-use types in the LAS are presented in Table 1. The studied area was the municipality of Dobre Miasto in north-eastern Poland. In the analyzed location, the predominant types of agricultural land are arable land, permanent meadows and permanent pastures. In the studied objects, 86% (Object 1), 85.2% (Object 2) and 71.6% (Object 3) of the area was eligible for payments. The land-use structure in the analyzed objects is presented in Table 2. Table 1. List of the studied objects from the LPIS and LAS. Classification in the Land Parcel Identification System
Classification in the Land Administration System
GR – arable land Land under crops; temporarily fallow land in good agricultural and environmental condition; land under greenhouses with permanent or portable structure; land occupied by agricultural machinery for farming operations.
R – arable land Land subjected to permanent mechanical cultivation for the purpose of agricultural or horticultural production; land used for the cultivation of hops, wicker and ornamental trees, including coniferous trees, tree and shrub nurseries; land occupied by agricultural and horticultural machines and equipment outside farmstead parcels; fallow land and temporarily fallow land;
P – potential agricultural land Areas with a non-permanent structure, not eligible for direct payments, situated in the vicinity of or inside an agricultural parcel, can be used for agricultural production without incurring substantial costs; T – permanent grasslands Permanent meadows – land covered with dense perennial vegetation composed on various species of grasses, leguminous and herbaceous plants that form the meadow sward, regularly mowed, including mountain pastures and meadows that are mostly mowed; Permanent pastures – land covered with vegetation similar to that found in meadows, used mostly for livestock grazing, including mountain pastures and meadows that are generally not mowed and are used for livestock grazing; C – protected permanent grasslands Permanent grasslands which are Natura 2000 sites and meet protection criteria;
Ł – permanent meadows Permanent meadows – land covered with dense perennial vegetation composed on various species of grasses, leguminous and herbaceous plants that form the meadow sward, regularly mowed, including mountain pastures and meadows that are mostly mowed; Ps – permanent pastures Permanent pastures – land covered with vegetation similar to that found in meadows, used mostly for livestock grazing, including mountain pastures and meadows that are generally not mowed and are used for livestock grazing, including land occupied by livestock rearing facilities such as canopies and barns, situated outside farmstead parcels;
S – orchards Land under trees, shrubs and perennial berry plants for fruit production, including continuous land with minimum clearance between trees or non-continuous land with large clearances, excluding land under other crops; the minimum area of agricultural parcels eligible for orchard payments is 0.1000 ha;
S – orchards Land with a minimum area of 0.1000 ha, densely planted with fruit trees or shrubs (minimum 600 trees or 2000 shrubs per ha), including land under fruit tree and shrub nurseries and vineyards;
Z – wooded land Land with tree and shrub cover with an area smaller than 0.10 ha, including: 1. midfield clusters of trees and shrubs that are not classified as forests; 2. peatlands partially covered with clusters of shrubs and dwarf trees; 3. land naturally overgrown with wicker and willow shrubs in river valleys and depression basins; 4. land adjacent to bodies of water, covered with trees or shrubs, which constitutes a biological protective zone around water courses and bodies of water;
Lzr – wooded agricultural land Enclaves or semi-enclaves on agricultural land with clusters of midfield trees and shrubs or only trees older than 10 years, not classified as forests or orchards; Lz – wooded land Land with tree and shrub cover with an area smaller than 0.10 ha, including: 1. peatlands partially covered with clusters of shrubs and dwarf trees; 2. land naturally overgrown with wicker and willow shrubs in river valleys and depression basins;
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5. ravines and gullies covered with naturally growing or planted trees and shrubs which prevent erosion, not classified as forests; 6. mounds of rock and rubble overgrown with trees and shrubs; 7. defunct cemeteries overgrown with trees and shrubs, excluding dense forest complexes; 8. clusters of trees and shrubs used as parks, but not equipped with recreational facilities and structures, other types of land covered with shrubs, excluding long-term plantations;
3. land adjacent to bodies of water, covered with trees or shrubs, which constitutes a biological protective zone around water courses and bodies of water; 4. ravines and gullies covered with naturally growing or planted trees and shrubs which prevent erosion, not classified as forests; 5. mounds of rock and rubble overgrown with trees and shrubs; 6. clusters and shrubs used as parks, but not equipped with recreational facilities and structures; 7. defunct cemeteries overgrown with trees and shrubs;
O – land afforested under Rural Development Programs Land afforested after 2008 under Rural Development Programs. R – short-term tree plantations Eligible areas planted with selected tree species. L – forests Land with compact surface and a minimum area of 0.1000 ha, covered with trees, shrubs and sward or temporarily without cover, including forest roads;
Ls – forests Land: 1) with compact surface and a minimum area of 0.1000 ha, covered with trees, shrubs and sward or temporarily without cover, including forest roads; 2) used for forestry and forest management, occupied by buildings and structures, drainage systems, forest district boundaries, forest roads, power lines, tree nurseries, timber storage yards, forest parking lots and tourist facilities;
W - water bodies Land under water courses and inland bodies of standing water, excluding inland bodies of salt water, including rivers, lakes, canals, drainage ditches, ponds, basins and lagoons;
Wm – inland bodies of salt water Wp – land under water courses Ws – land under bodies of standing water W - ditches
K - roadways Land delimited by public and private roadways pursuant to the provisions of the Act of 21 March 1985 on public roads;
Dr - roads Land under roads; Tk – railway lines and structures Land under railway lines and structures; Ti – other transport facilities Airports, sea and inland ports, tram lines, bus stations, car parks, cable cars, flood embankments;
U – industrial areas 1. Industrial areas, including land occupied by industrial buildings and equipment, water intakes, wastewater treatment plants, transformer stations, spoil piles, landfills, storage yards, warehouses, transportation centers, overhaul plants, etc. 2. residential areas, including land not used for agricultural production or forestry, occupied by residential buildings and facilities (yards, driveways, passages, playgrounds, etc.); 3. other developed areas, including land occupied by buildings and facilities related to administration, health care, commerce, religious worship, crafts, services, education, culture, art, recreation, communications, human and animal cemeteries; 4. recreational areas not occupied by buildings; 5. mines, including land occupied by active strip mines;
Ba – industrial areas Land occupied by industrial and storage buildings, structures and devices, transportation centers, overhaul plants, transformer stations, above-ground pipelines, collectors and water mains, spoil piles, landfills, water intakes and wastewater treatment plants; B – residential areas Land occupied by residential buildings, utility buildings and technical facilities (yards, driveways, passages, playgrounds, recreational areas, water wells, water reservoirs, above-ground cable lines) excluding outside farmstead parcels; Bi – other developed areas Land occupied by non-residential buildings and structures, cemeteries and defunct cemeteries not classified as wooded land, and animal cemeteries; Bz – recreational areas Land not occupied by buildings and related structures; Active strip mines;
K - mines
D - farmsteads Developed agricultural land occupied by residential buildings and other buildings and structures for agricultural production (garages, utility buildings, boiler houses, silos, barns, etc.);
Br – developed agricultural land Developed agricultural land occupied by residential buildings and other buildings and structures for agricultural production (garages, utility buildings, boiler plants, silos, barns, etc.), household gardens and flower beds in rural areas;
I – other non-agricultural land Land not suitable for agricultural production
N – fallow land Marshes (swamps, bogs, quagmires, fens, moors), sands (quicksand, wild beaches, coastal sands, dunes), natural geological formations (cliffs, steep slopes, precipices, rocks, rubble), excluding reclaimed mine lands; Tr – other land Land not suitable for the above types of use.
Source: Own elaboration based on the Instructions for inspecting eligible areas.
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Results and Discussion Differences in the area of cadastral and reference parcels were determined by comparing the corresponding areas in the LPIS and LAS, and ineligible areas were subtracted from the area of cadastral parcels. The results are presented in Table 3. The average difference for 100 objects was 0.03 ha, and the maximum difference was 0.35 ha. Table 2. Land-use structure in the analyzed villages. Object 1 (%)
Object 2 (%)
Object 3 (%)
1
No
Arable land
Land-use structure in the analyzed objects
59.7
50.0
42.7
2
Permanent pastures
14.8
26.0
22.9
3
Permanent meadows
11.6
9.2
12.5
4
Fallow land
5.9
6.4
6.0
5
Roadways
4.2
3.0
4.3
6
Developed agricultural land
1.4
2.4
4.0
7
Forests, land covered by trees and shrubs
1.3
1.5
3.3
8
Water bodies
0.7
1.1
2.2
9
Developed and urbanized land
0.4
0.4
2.0
10
Orchards
0.1
0.1
0.1
Source: own elaboration based on the data from the County Center for Geodetic and Cartographic Documentation. Table 3. Differences in the area of cadastral and reference parcels. Statistics
Value [ha]
arithmetic average
0.03
median
0.02
dominant
0.00
maximum value
0.35
minimum value
0.00
Source: Own elaboration.
In the next step, differences between the position of boundary points of parcels in the LAS and the LPIS were determined. The position of boundary points differed in 95% of the analyzed parcels, and linear differences exceeded 0.1 m in 89% of the cases. The maximum linear difference between boundary points was 17.4 m, and the minimum difference (greater than 0.10 m) was 0.15 m. In the evaluated objects, the average maximum linear difference in the position of boundary points was determined at 4.50 m with a median of 3.57 m. The presence of maximum linear differences was also analyzed along river and road boundaries. In 80% of parcels where the linear difference in the position of boundary points exceeded 0.10 m, the greatest differences were noted along road boundaries. The above difference was noted in 78% of parcels bordering rivers. The average differences were determined in parcels where the linear difference in the position of boundary points exceeded 0.10 m. The average maximum difference was 8.6 m and the average minimum difference was 0.15 m. Table 4. Differences in the position of boundary points in the compared parcels. Statistics
Value [m]
arithmetic average
4.50
median
3.57
dominant
null
maximum value
17.40
minimum value
0.15
Source: Own elaboration.
In the last step, differences in the area of the most prevalent land management units (and arable land) with various land-use types were analyzed. The average difference in the area of the corresponding land management units in the compared systems ranged from 0.04 ha to 1.52 ha (Table 5). The greatest maximum differences in area were determined at 9.79 ha for arable land, 9.36 ha for permanent grasslands 257
and 4.48 ha for other types of non-agricultural land. The smallest maximum difference in area was determined at 0.10 ha for roadways. The mode value of the analyzed datasets ranged from 0.00 ha to 0.03 ha. Forests and areas covered by trees and shrubs did not have a mode value. The median ranged from 0.04 ha to 0.96 ha. The greatest discrepancies in area resulted from different interpretations of land use, in particular in permanent meadows and pastures which were identified as arable land in the LPIS or, if confirmed by an orthophotomap, as other non-agricultural land. Such differences were also observed in relation to fallow land which was identified as water bodies or land covered by trees and shrubs in the LPIS. Table 5. Differences in the area of farmland with various land-use types. Name of land use
arable land
permanent pastures/meadows
land covered by trees and shrubs
forests
water bodies
roadways
farmsteads
other land
Statistics
Value [ha]
arithmetic average
1.25
median
0.45
dominant
0.01
maximum value
9.79
minimum value
0.00
arithmetic average
1.52
median
0.96
dominant
0.00
maximum value
9.36
minimum value
0.00
arithmetic average
0.34
median
0.28
dominant
null
maximum value
1.15
minimum value
0.02
arithmetic average
0.33
median
0.30
dominant
null
maximum value
0.48
minimum value
0.22
arithmetic average
0.13
median
0.04
dominant
0.01
maximum value
0.89
minimum value
0.00
arithmetic average
0.04
median
0.04
dominant
0.02
maximum value
0.10
minimum value
0.01
arithmetic average
0.11
median
0.05
dominant
0.03
maximum value
0.37
minimum value
0.01
arithmetic average
0.31
median
0.13
dominant
0.03
maximum value
4.48
minimum value
0.00
Source: Own elaboration.
The tolerance limit in measurements of agricultural parcels is an important parameter in field inspections which determines the allowable margin of error in the declared eligible area. Regardless of the applied measurement method, tolerance is calculated as the product of an agricultural parcel’s perimeter and the width of the buffer zone surrounding the parcel. The buffer zone is determined by the applied 258
measurement method. Tolerance is expressed in hectares to the nearest 100 m 2. The maximum tolerance may not exceed 1.00 ha, and minimum tolerance is 0.01 ha. Conclusions The Land Parcel Identification System is developed based on data from the land and building register, and it is a part of the Polish Integrated Administration and Control System. In the first years of LPIS operation, financial support for farmers was granted based on information relating to the boundaries, area and location of cadastral parcels and agricultural land (eligible and ineligible areas). With time, the ARiMR developed new LPIS system layers known as reference boundaries (reference parcels) and land management units. The reference boundaries were determined based on cadastral parcels, and land management units were identified based on definitions of agricultural land. The new layers have been developed to meet the EU requirements relating to system updates, and to eliminate discrepancies between cadastral data and actual land use. Most discrepancies relating to cadastral parcels, such as the location of drainage ditches or rivers, result from shifts in the shoreline of water bodies. The analysis also revealed that databases of agricultural parcels often contain outdated information which cannot be used in the process of applying for subsidies. Each year, the ARiMR uses the data imported from county centers for geodetic and cartographic information to update the reference database. The cadastral data in payment applications constitutes a basis for the identification and localization of agricultural parcels. The analysis of compatibility between LAS and LPIS data revealed considerable discrepancies. The maximum difference in the area of cadastral and reference parcels was determined at 0.35 ha. The maximum difference in the location of boundary points exceeded 17 m, and it was noted in a parcel bordering a river. With regard to agricultural land, discrepancies in land-use type were observed in 66% of the analyzed parcels, and the greatest difference exceeded 9 ha. In most cases, the noted discrepancies resulted from different interpretations of land use, in particular in permanent meadows and pastures which were identified in the LPIS as arable land, land covered by trees and shrubs or other non-agricultural land. Differences in land-use type were observed in 55% of the analyzed parcels. The analyzed area is covered by a project entitled “e-map – supplementation and digitalization of data for comprehensive access to the geodetic and cartographic resources of Olsztyn county”, co-financed by the European Regional Development Fund under the Regional Operational Program for Warmia and Mazury 2007-2013. As part of the project, the boundaries of developed and urbanized farmland were verified based on orthophotomaps and the results of local inspections. The portion of land occupied by internal roadways, technical devices and household gardens was zoned as non-agricultural land. References UOPRSWB, 2015. Ustawa z dnia 5 lutego 2015 r. o płatnościach w ramach systemów wsparcia bezpośredniego (Dz. U z 2016r. poz. 337, z późn. zm.). UOKSEP, 2003. Ustawa z dnia 18 grudnia 2003 r. o krajowym systemie ewidencji producentów, ewidencji gospodarstw rolnych oraz ewidencji wniosków o przyznanie płatności (Dz. U. z 2017 poz. 5). SZDARIMR, 2015. Sprawozdanie z działalności Agencji Restrukturyzacji i Modernizacji Rolnictwa 2015 (http://www.arimr.gov.pl/dla-beneficjenta/biblioteka/sprawozdania-z-dzialalnosci-agencjirestrukturyzacji-i-modernizacji-rolnictwa.html). BRARMIR, 2015. Bazy referencyjne w ARiMR, LPIS, Ewidencja producentów. Access online: http://www.arimr.gov.pl/fileadmin/pliki/Tam_bylismy/Centrala/GIS/prezentacje/DZIEN_1_01_ ARiMR_GIS_w_rolnictwie_2015.pdf (access 10.03.2018). PB.ZS.058.1.2017. Minister Rolnictwa i Rozwoju Wsi Krzysztof Jurgiel, Znak sprawy: PB.zs.058.1.2017 odpowiedź na implementację Pani Poseł Ewy Lieder nr 11481 z dnia 4 kwietnia 2017r. dotyczące zmian wielkości powierzchni ewidencyjno-gospodarczej, Warszawa 21 kwietnia 2017. ARIMR, 2016. Instrukcja realizacji kontroli w zakresie kwalifikowalności powierzchni, wersja 2.0. Warszawa. Access online: http://www.arimr.gov.pl/uploads/media/zal_2_do_umowy__instrukcja_.pdf (access 10.03.2018). 1306/2013. Regulation (EU) No. 1306/2013 of the European Parliament and of the Council. Access online: https://eur-lex.europa.eu/legal-content/PL/TXT/?uri=CELEX%3A32013R1306 (access 10.03.2018). 1307/2013. Regulation (EU) No. 1307/2013 of the European Parliament and of the Council. Access online: https://eur-lex.europa.eu/legal-content/PL/ALL/?uri=uriserv:OJ.L_.2013.347.01.0608.01.POL (access 10.03.2018).
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809/2014. Regulation (EU) No. 809/2014 of the European Parliament and of the Council. Access online: https://eur-lex.europa.eu/legal-content/PL/TXT/?uri=CELEX%3A32014R0809 (access 10.03.2018).
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THE IMPORTANCE OF GREEN INFRASTRUCTURE FOR THE INSURANCE RISK REDUCTION WITH PARTICULAR EMPHASIS ON URBANISED AREAS Prof. Wiesław Koczur, Ph.D. Department of Social and Economic Policy University of Economics in Katowice Katowice, Poland e-mail:
[email protected]
Agnieszka Lorek, Ph.D. Department of Social and Economic Policy University of Economics in Katowice Katowice, Poland e-mail:
[email protected] Abstract The issue of environmental threats related to climate change is currently one of the most important global problems. The increase in the number of threats mainly concerns urban areas. Already over 75% of the population of Europe lives in cities that are the main centres of economic and cultural activity, innovation centres and the place of employment of the majority of Europeans. The presence of city-specific hazards is typical for contemporary cities for example the risk of catastrophic events associated with: flooding due to torrential rains, or an increased risk of disease associated with adverse environmental conditions prevailing in urban areas. It should be noted, however, that these risk may be reduced due to the use of infrastructure enhancing the level of ecological safety. This infrastructure can be created by people, but it is also possible to use the so-called „green” and „blue” infrastructure. This approach brings a number of benefits to urban development. It supports the functioning of urban ecosystems and is also economically justified. The purpose of this article is to present problems related to the specificity of ecological risks affecting urban areas and the importance of infrastructure in mitigating or reducing them. The design of the study has been subordinated to the thesis that a properly planned ecological infrastructure network can significantly reduce the level of insurance risk. Key words: urban areas, ecosystem services, green infrastructure, ecological risk, insurance risk Introduction The issue of environmental threats related to the climate changes is currently one of the most important global problems. The increase in the number of threats mainly concerns urbanised areas. At present, more than 75% of Europe's population lives in cities that are the main centres of economic and cultural activities, as well as innovation centres and a place of employment of the majority of Europeans. Such a high level of urbanisation in Europe means that the climate changes will have a serious impact both on the dynamics of urban development and, consequently, on the economic condition of individual EU Member States, as well as on the quality of life of their inhabitants. For contemporary cities, the presence of their specific hazards, such as: a risk of catastrophic events associated with, for example, heavy rain, or an increased risk of disease associated with adverse environmental conditions in urban areas, e.g. the occurrence of urban heat islands, is typical. The occurrence of these types of risks is related both to the global climate changes and to the specific structure of the urban fabric, which strengthens negative climatic phenomena. The urban areas, due to their nature, are more strongly affected by the effects of the climate changes than other areas. These risks may be reduced owing to the use of infrastructure enhancing the level of ecological safety. This infrastructure can be created by man, but it is also possible to use the so-called "green" and "blue" infrastructure for this purpose. Such an approach brings a number of benefits for the development of urban areas. Such solutions are more durable, as well as they support the functioning of urban ecosystems and they are also economically justified. It needs to be emphasised that an important role in stimulating desired actions in the scope of indicated matter can and should be played by the insurance sector, for which searching for optimal solutions in this area is a new and difficult challenge. However, it is worth taking them, because it is supported by both social and economic aspects related to a large scale of compensation and other benefits provided by insurers in relation to damage,
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both property and personal ones, caused by the occurrence of the above-mentioned types of the insurance risk. The possibility of using the insurance prevention instruments is also significant. The objective of this article is to present problems related to the specificity of ecological risks affecting the urbanised areas and the importance of green infrastructure 1 in their levelling. The design of the development was subordinated to the thesis, according to which, a properly planned natural infrastructure network may significantly reduce the level of the insurance risk. Material and methods The presented development is of a theoretical nature. Therefore, the basic research method is the analysis of available sources. The strategy of searching for relevant materials for the analysis was based on answers to the following research questions: • Does the term “insurance value of ecosystems” appears in the subject literature? • What are the basic types of risks associated with natural phenomena affecting the urbanised areas? • How does the insurance industry react to new challenges? On this basis, the Internet resources were searched using the Google Scholar browser with the use of the following search terms: insurance value of ecosystems, insurance value of urban ecosystems, urban ecosystem services, green infrastructure, natural infrastructure, ecological risk, catastrophic insurance. The search results allowed to carry out the analysis of: • national and foreign literature dealing with the issues that constitute the subject of interest to the authors, • available statistical data related to the discussed issues, • good practices in the matter discussed in this development, recorded in the selected European and non-European countries. Due to the topicality of the subject, the Internet portals have become an important source of information, in particular: • THE NATURE OF CITIES: https://www.thenatureofcities.com/ where we can find a discussion of scientists and practitioners on: What is the insurance value of urban ecosystems and their services? • The portals providing current news on the practice of implementing the concept of using the insurance value of ecosystems by the insurance industry: o OCEANS DEEPLY - https://www.newsdeeply.com/oceans, o WORLD BUSINESS COUNCIL FOR SUSTAINABLE DEVELOPMENT (WBCSD) https://www.wbcsd.org/ , o THE CARIBBEAN CATASTROPHE RISK INSURANCE FACILITY (CCRIF SPC) http://www.ccrif.org/content/ccrif-spc-10th-anniversary-celebrations o MUNICH RE - https://www.munichre.com/en/homepage/index.html. However, it should be emphasised that the subject matter that constitutes the subject of this article has not been an excessively broad scope of interest in the subject literature so far. The analysed developments are of the contributory nature, and they concern the most frequently selected issues in the submitted article. Insurance value of ecosystems The theory that natural ecosystems reduce the level of a potential risk associated with natural threats was firstly proposed by BAUMGARTNER (2007). The indicated author states that: “biodiversity has an insurance value, which is a value component in addition to the usual value arguments, such as direct or indirect use or non-use values. In this respect, biodiversity and financial insurance are substitutes” (BAUMGARTNER, 2007). MC PHEARSON et al. (2015) claim that the insurance value reflects the maintenance of benefits of ecosystem services despite the volatility, anomalies and uncertainty regarding the management methods. GÓMEZ-BAGGETHUN and DE GROOT (2010) define the contribution of ecological infrastructure and ecosystem services for increased resilience and reduced vulnerability to shocks as the insurance value. PASCUAL et al. (2015) mention the "natural insurance value" (NIV) as a component of the "total economic value", with more conventional components (use and non-use values) classified as the "total production value" (TOV). PASCUAL et al. still divide NIV to "self-defence" (reducing the risk of a disturbing event) and "self-insurance" (reducing the level of the loss resulting from the event). NIV is a rather specific concept referring to the "value of one very specific function of resilience: reducing the risk for the ecosystem user associated with the use of ecosystem services under uncertainty conditions" (BAUMGÄRTNER, STRUNZ, 2014). GREEN et al. (2016) define the insurance value of ecosystems and In the subject literature, various terms are used within the scope of the indicate matter. In this article, two terms are treated synonymously and used interchangeably: "green infrastructure" and "natural infrastructure". 1
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biodiversity in a slightly different way, at the same time, emphasising social values related to buffering of shocks, and thus, maintaining the resilience of socio-ecological systems. The authors write about the "insurance value metaphor", which can be used to inform about urban planning and to make decisions focused on investing in the ecosystem resilience. One of the most difficult problems to solve in this scope is the measurement of the insurance value of ecosystems. FIGUEROA and PASTEN (2015) were the first who perform such valuation, and it was related to the insurance value of forests. These authors concluded that the ecosystem services related to the climate regulation provided by forests can be economically valued by assessing the reduction (increase) of an insurance premium, which risk-prone people are willing to pay when the forest cover is slightly increased (reduced). However, if we think about the long-term valuation of resilience to extreme scenarios and threats – as in case of adaptation to various climate change scenarios – then, the conventional economic valuation faces serious limitations. In this case, we have to deal with very diverse conditions, e.g. related to the socio-economic structures, technology or human preferences. There is also a high degree of uncertainty about the risk of disturbances, and such an assessment would require extrapolation that goes far beyond the current experience. Green urban infrastructure and its importance for reducing insurance risks The cities require appropriate areas of efficiently functioning ecosystems necessary to ensure their consumption and assimilation of waste. However, it should be added that the majority of ecosystem services consumed in cities is generated by ecosystems located outside the cities. An example can be the study carried out by FOLKE et al. (1997), who estimate that 29 largest cities in the Baltic Sea region, considering only the most basic ecological services, such as food production, as well as nitrogen and carbon assimilation, requires the appropriate areas of ecosystems corresponding to the size of the entire basin, several hundred times crossing the area of the cities. A similar analogy can be applied to various types of risks affecting the urbanised areas. It is possible to distinguish the risks: 1. Resulting from phenomena of a general nature, the causes and effects of which go beyond the city area –e.g. storms, hurricanes, floods, etc. related to the changes in weather and climate (see Fig.1).
Fig. 1. Philippines after passing the Haiyan super- typhoon on 07.11. 2013. Source: CHROŃMYKLIMAT.PL.
2.
The phenomena characteristic of the urbanised areas – related to the development of urban areas, e.g. increased threat of urban floods caused by sealing of urban areas (see Fig. 2), and the formation of heat islands that are hazardous for health.
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Fig. 2. City flood in Gdańsk`2016: traffic paralysis at the intersection of Grunwaldzka/Żołnierzy Wyklętych. Source: PORTAL OF THE CITY GDAŃSK, author: MEHRING, G.
The general risks are impossible to be eliminated, however, it is possible to mitigate their effects, and thus to reduce the losses for insurers, through the maintenance and protection of natural areas, e.g. wetlands and forests that protect against floods or through their regeneration. For example, it is estimated that up to 65% of Hurricane Katrina’s losses could be avoided if mangroves and other wetlands on the coast of the Gulf of Mexico had not been damaged. The costs associated with the reconstruction of these ecosystems are estimated at USD 14 billion, and the losses amounted to USD 100-150 billion according to various estimates (KOUSKY, ZECKHAUSER, 2006). According to the studies by NARAYAN and BECK with the team (2017), wetlands on the north-eastern coast of the United States allowed to avoid $ 625 million of direct flood damage during Hurricane Sandy in 2012. These scientists cooperated with several major insurance companies (Risk Management Solutions – RMS and Guy Carpenter and Co.), which have accumulated a lot of data on the effects of weather-related disasters and losses in properties for decades. With the use of RMS risk models and data on properties, a model for 2,000 storms was constructed, and it was found that every year, wetlands reduce the flood damage in properties by 16%. The results of another study referring to 34 hurricanes that have damaged the United States since 1980, indicate that the scale of damage largely depended on the availability and size of wetlands (backwaters). The loss of 1 ha of such areas increased the costs of damage by an average of USD 33,000 (COSTANZA et al., 2008). According to data cited by EVAN MILLS (2007), the largest European insurer, Allianz, stated that the climate changes increased the insurance losses resulting from extreme events by 37% in just a decade. The losses in a year abounding in such events may exceed USD 1 trillion. The above-cited data indicate the necessity to take measures that protect the natural areas surrounding the cities. It is particularly important due to the observed climatic changes, which increase the frequency and intensity of extreme weather phenomena, which creates growing challenges related to adaptation of the cities to these phenomena (which is well illustrated by the following map – Figure 3, where we can observe the concentration of extreme phenomena in the areas with a high level of population).
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Fig.3. Loss events worldwide 2017. Geographical overview. Source: MUNICH RE.
One of the first attempts to use insurance in order to protect the "natural infrastructure" protecting the coastal properties worth billion dollars is the coral reef insurance project in Mexico. On 8 March 2018, Nature Conservancy and the state government of Quintana Roo announced the creation of the Coastal Zone Management Trust, which will purchase the world’s first coral reef insurance policy. If a hurricane of 4 or 5 category strikes a sixty-kilometre section of the coastline, funds will be paid to finance the repair and reconstruction of the reef (OCEANS DEEPLY, 2018). Another example of how the insurance can be used in order to motivate the “natural infrastructure” development is National Flood Insurance Program (NFIP) in the United States. NFIP offers flood insurance to house owners, tenants and business owners if their community participates in the adoption and enforcement of regulations regarding the flood risk reduction. The NFIP insurance premiums are calculated on the basis of a degree of risk for a given community, which can be reduced by appropriate use of the "natural infrastructure" (WBCSD, 2017). The second group of the above-indicated risks includes characteristic risks and those related to the development of urban areas. They are easier to be eliminated or to limit the effects of their occurrence. One of the methods for reducing these types of risks is the wider use of the so-called natural infrastructure and protection of ecosystem services in the urban areas. The ecosystem services, which are key to the resilience of cities in response to specific disturbances, relate to the urban temperature regulation, water supply, limitation of rainwater outflows and food production. As it is mentioned by GREEN et al. (2016), in order to have the insurance value, these natural structures must be spatially adjusted to sensitive areas (e.g. by providing a barrier between a potential source of disturbances and areas at risk) and they must be large enough to match the disturbance size. As mentioned above, a special role in the process of protection of urban areas should be played by the so-called green (natural) infrastructure. The green infrastructure can be defined in various ways: 1. First of all: in a narrower sense, as a network of green areas planned and managed as an integrated system in order to provide synergistic benefits through its multifunctionality (LANDSCAPE INSTITUTE,
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2009). This concept is used in relation to the "planned" green areas functioning in public space, such as: parks, avenues, squares. 2. Secondly: in a broader sense, as the infrastructure supporting the functions of ecosystems (Ecosystem Infrastructure), it includes natural or man-made infrastructure that supports the functioning of ecosystems in the cities. For example, WBCSD (2017) uses the "natural infrastructure” term and defines it as: „planned or managed, natural or semi-natural system designed to provide a specific benefit.” In the context of development of urban areas, the most important kinds of this type of infrastructure may include: • forest areas located in the cities (urban forests), • natural and artificially created wetlands and water areas (ponds, lakes, small ponds, etc.), • green roofs, walls and facades, • urban parks and other green spaces available to the public, • gardens owned by individual residents (SYMBIOTIC CITIES NETWORK). One of the basic risks and problems faced by the cities includes the surface sealing that leads to deterioration of the living conditions of plants in the city, and consequently, to adverse changes in the microclimate and an increase in temperatures in summer and a decrease in winter. These phenomena also increase a risk of flooding associated with the surface sealing. In order to counteract the aforementioned threats, the urban authorities should pay attention to the restoration of retention capacities of the basin, protection of natural floodplains, and the natural restoration of urban watercourses and drainage of ecological corridors. The integrated planning within the urban basins will allow not only for the improvement of safety and comfort of living of inhabitants, but also for regeneration of urban ecosystems. In order to slow down and reduce the run-off, it is necessary to implement decentralised systems of the rainwater and thaw water management based on local retention, infiltration, purification and reuse of rainwater (LOREK, 2015). The city authorities, wishing to be guided by the principles of sustainable development of urban areas, should take into account such activity directions as (JANUCHTA-SZOSTAK, 2012): • management of rainwater in the place of the precipitation occurrence. In order to slow down and reduce the run-off, it is necessary to implement decentralised systems of the rainwater and thaw water management based on local retention, infiltration, purification and reuse of rainwater. Such methods for limiting the outflow of water associated with urban storms may be the construction of linear infrastructure (bioswale), green roofs and rain gardens. • wider use of the “green infrastructure”, i.e. development of the retention potential of the urban green areas, the use of natural filtration capacities of the enlivened ground and vegetation, and also planning and composition of rainwater management systems in combination with the landscape architecture. • reconstruction of urban basins and river valleys. In the spatial planning and designing the city buildings, it is necessary to take into account different levels of a flood risk and to restore the basin retention capacities, as well as to protect natural floodplains, to restore urban watercourses and to drain ecological corridors. Examples of green infrastructure that protect the city against urban floods illustrate Fig. 4 and 5.
Fig. 4. Examples of curbside rain gardens. Source: SAVE IT GREEN INFRASTRUCTURE FACT.
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Fig. 5. A bioswale alongside a neighbourhood street in Seattle. Source: NATURE WORKS EVERYWHERE.
ELMQVIST (2015) indicates the effectiveness of such activities, citing the information that according to the data collected by the Korea Environment Institute, it can be predicted that a 1-percent increase in coverage of green infrastructure, including parks, urban forests and green roofs, may result in 6.4-percent reduction of economic losses caused by floods in the Korean cities (ELMQVIST, 2015). Another problem affecting urban areas and increasing the risk of disease is air quality. The degradation of green areas in the city is associated with the deterioration of air quality, and the possibilities of recreation and effective regeneration of a human body are limited. In this context, a very important challenge is the proper way of spatial planning by public authorities, especially the location and structure of green areas. The research shows that urban parks have the ability to neutralise over 85% of air pollution reaching their area (in case of roadside trees, it is 70%) (BERNATZKY, 1983). The share of the area covered with tree crowns has a clear impact on the average surface temperature of the area, as illustrated by the results of measurements carried out in Munich. At the same time, when in almost treeless areas, i.e. wooded up to 5%, the average surface temperature was more than 40oC, and in the areas planted with trees above 75%, the surface temperature was only 22 0C. Similar results were obtained in Warsaw, where the temperature differences between the sunlit asphalt surface and the wooded area amounted to 19.5oC, at the air temperature of 250C. A particular threat to the cities is the construction of peri-urban areas, where the population increase is ten times faster than in the cities themselves. It irreversibly degrades viable ecological rings surrounding the cities, which are the areas covered with forests and fields, necessary to maintain the health of the urban environment and the surrounding areas. Also, further reduction of the open areas leads to deterioration of the living conditions of the inhabitants. The result of such a state of affairs is an increase of nuisance related to vehicle traffic, fragmentation and reduction of the area covered with vegetation which results in the creation of the so-called "heat islands” in the city centres. In Warsaw, for example, the temperature difference between a city centre and peripheral areas can reach 7-80 C, and even up to 100 C with the anticyclonic and windless weather (SZCZEPANOWSKA, 2012). A good example of a city that uses a wide range of green infrastructure to improve the quality of life is New York. The pictures below show one of the initiatives in this area- High Line Park. The High Line is a public park built on a historic freight rail line elevated above the streets on Manhattan’s West Side (FRIENDS OF THE HIGH LINE).
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Fig. 6. Location of The High Line Park. Source: URBAN GARDENS.
Fig. 7. Landscape of The High Line Park (1). Source: WWW.AMERICANTRAILS.ORG.
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Fig. 8. Landscape of The High Line Park (2). Source: WWW.ETSY.COM.
The importance of the insurance industry in supporting solutions based on nature Extreme weather phenomena, such as droughts, heat waves, excessive rainfall, major disasters as well as natural disasters, such as floods, landslides and earthquakes usually cause significant human and economic losses. These events involve high costs for people who would be willing to pay for avoiding such disasters. BARRO (2009), for example, has shown that the society would voluntarily reduce its GDP by about 20% per year in order to eliminate large-scale economic costs, such as costs caused by natural disasters. According to EVAN MILLS (2007), the challenges related to climate and risk changes resulting from this fact will have a significant impact on the insurance industry. As in the past, the insurance industry was the leader of changes aimed at, among others, minimising the risk associated with fires in buildings, as well as the threat of collapse in the event of an earthquake (by stimulating relevant changes in the building law), today, the insurers have a great opportunity to develop creative solutions to prevent losses associated with the occurrence of the above-indicated risks and insurance products that will reduce the losses related to the climate changes. The concept of active inclusion of the insurance industry in the conditions of the American economy to protect the coasts from violent phenomena is presented by MITCHELL CHESTER in the discussion on the insurance value of ecosystems (https://www.thenatureofcities.com/2015/09/29/what-is-the-insurance-value-of-urban-ecosystemsand-their-services/). According to Chester, these activities should concern: 1. The insurance consumer education on how the support of public authorities for the nature-based solutions can mitigate the effects of catastrophic events related to the climate. The public support for the use of natural systems to protect regions and cities is a way of provoking the political will to approve such action programmes, which many public officials are missing now. As it is stated by Chester, according to the information of the Insurance Institute, in September 2014, there were the examples of supporting the insurance industry for revised building regulations. Furthermore, he states that the promotion of the use and construction of natural coastal safeguards should be added to a list of the insurer’s tools used to reduce the risk. 2. Large insurers can agree to insurance for the development of coastal areas, provided that certain criteria are met as prerequisites, e.g. protection of wetlands that protect other areas from flooding. In places, where the wetlands and other shoreline reinforcements cannot be protected or properly restored, the insurers can refuse to issue the insurance, and at the same time, persuade potential insured people by financial incentives to transfer their projects to more sustainable locations. Such incentives can be the main motivating factor for the strategic, climate-adapted arrangement of new hotels, office buildings, other commercial and private properties in the areas that are less prone to potential risks. 269
3.
The insurers can cooperate with municipal bond rating agencies to persuade public authorities and consumers to activities that use the nature to protect against disasters. Such an activity can help identify the needed infrastructure improvements at the “micro” level. The "local government credit quality", measured by the assessment of the municipal bond yields from the perspective of climate threats, is already observed by powerful entities such as Standard & Poor's, Moody's Investor Service and Fitch Ratings. If local governments do not take measures to lower the risk related to climate threats, they will obtain lower credit ratings, which may reduce the insurance readiness in these areas. 4. The insurers can already directly invest (e.g. within the framework of public-private partnership) in infrastructure projects regarding the creation and/or reconstruction of natural defence systems in exchange for payments from users (companies, local governments and house owners). The information included in the World Business Council for Sustainable Development (WBCSD) report confirms the existence of activities concerning the investments financed by insurance companies. For example, Tokyo Marine & Nichido Fire Insurance Co., Ltd. were involved in planting 8,994 hectares of mangroves in nine countries throughout the Asia and Pacific regions. Zurich Insurance Group and Zurich Foundation have established cooperation with Global Resilience Partnership in order to solve a problem of communities being at risk of flooding in the Sahel, the northern part of Africa, as well as South and South East Asia. In March 2016, the Prudential Financial company announced it would invest $ 1.7 million for new pilot cooperation between The Nature Conservancy and Encourage Capital, the so-called District Stormwater LLC (DS). The investment will be used for financing the green infrastructure development in the District of Columbia, which measurably reduces the run-off of rainwater (WBCSD, 2017). However, the WBCSD report states that while the mentioned initiatives and partnerships show a strong interest in the insurance sector, the data collected in the form of interviews by WBCSD show that the benefits on reducing the risk provided by the "green infrastructure" are not systematically included in the insurance products. Some of the reasons given by the respondents are as follows (WBCSD, 2017): • it is not clear who would cover the costs associated with maintenance/renewal of natural areas that perform protective functions (insurance costs) or who will be a beneficiary of the insurance values provided by the "green infrastructure"; • the challenges associated with measuring and quantifying the benefits resulting from the risk reduction by the “green infrastructure” in a way accepted by the insurance industry are significant. Many specialists in the financial and insurance sector believe that if it is managed to overcome the indicated challenges, the "natural infrastructure" can be an area of growth, taking into account the potential of ecosystems to reduce the risk (WBCSD, 2017). GREEN et al. (2016) also emphasise the insurance value and long-term benefits of using the "green infrastructure", but they believe that in the short time, the high market values of properties in urban areas will often exceed the economic value that can be attributed to the insurance value, thus eliminating these types of investments. These authors call for wider recognition of the long-term social and economic significance of the insurance values, but they discourage its monetisation in order to support a decision-making process, primarily because this approach creates a risk that the loss of the insurance value associated with the ecosystem degradation can be compensated by financial capital. Instead, they are in favour of carrying out an ecological economic and management analysis aimed at ensuring the continuity of the provision of ecosystem services that are a basis of the long-term prosperity. Conclusions Until now, the insurance value of ecosystems has been largely neglected in scientific research (as indicated by the lack of a coherent definition and methods of valuation of the insurance value) and practice. However, this concept has recently gained a lot of interest. The latest initiatives undertaken in many countries are aimed at basing the economic development on nature-based solutions, where the basis is to maintain and strengthen the insurance value of ecosystems. The reason for this interest is partly the fact that global disasters show a clear upward trend, and their range often affects the urbanised areas. People living in the developing urban centres around the world are exposed to various risks associated with the climate changes – storms and extreme weather conditions, sea level rise, limited access to drinking water, and these are just some of the risks to people's lives, livelihoods and property (MICHALSKI et al., 2016). The urban ecological infrastructure and ecosystem services may play an important role in increasing the resilience of cities by increasing their capabilities of dealing with disturbances and adapting to the climate changes and other. These challenges also pose new fields of activity for the insurance sector. On the basis of the carried-out analysis, it is possible to observe geographical diversity regarding the practice of using the insurance value of ecosystems as a method for minimising the disaster risks. In EU countries, the solutions 270
based on public policies dominate. The USA is focused on wider use of market solutions. Market instruments (including insurance) are also used in the developing countries (mentioned reef insurance in Mexico or CCRIF SPC.-Caribbean Catastrophe Risk Insurance Facility operating in the Caribbean Sea region), where public policies are poorly developed, and the countries do not have sufficient funds. An additional argument in favour of including the insurance instruments in the process of ecosystem protection is the lack of trust in public authorities that is often observed in these countries (e.g. in Mexico, the insurer’s share was well received by the hotel industry, which has to bear the insurance costs, and the insurance company was considered to be a guarantor of honesty and correct expenditure). Thus, it may seem logical that we should try to appreciate this "insurance value" to make attempts to take into account the value of ecosystems in the decision-making process, urban planning, and as the area of a new activity of the insurance industry. References BARRO, R. 2009. Rare disasters, asset prices and welfare costs. American Economic Review, 99(1): 243–264. BAUMGARTNER, S. 2007. The insurance value of biodiversity in the provision of ecosystem services. Natural Resource Modeling, . 20: 87-127. BAUMGÄRTNER, S., STRUNZ, S. 2014. The economic insurance value of ecosystem resilience. Ecol. Econ., 101: 21– 32. BERNATZKY, A. 1983. The effects of trees on urban climate. In Trees in the 21st Century: Based on the First International Arboricultural Conference, A.B. Academic Publishers, Berkhamster, p. 59-76. CHESTER, M. 2015. Voice in the discussion: What is the insurance value of urban ecosystems and their services? Online access: https://www.thenatureofcities.com/2015/09/29/what-is-the-insurance-value-ofurban-ecosystems-and-their-services/ (access 20.03.2018). CHROŃMYKLIMAT.PL, Philippines after passing the Haiyan super- typhoon on 07.11. 2013. Online access: http://www.chronmyklimat.pl/projekty/wiadomosci/113/haiyan-najsilniejszy-tajfun-whistorii?ajax=1&print=1, (access 19.04.2108). COSTANZA, R., PÉREZ-MAQUEO, O., MARTINEZ, M.L., SUTTON, P., ANDERSON, S.J., MULDER, K. 2008. The value of coastal wetlands for hurricane protection. Ambio, 37(4): 241-248. ELMQVIST, T. 2015. Voice in the discussion: What is the insurance value of urban ecosystems and their services? Online access: https://www.thenatureofcities.com/2015/09/29/what-is-the-insurancevalue-of-urban-ecosystems-and-their-services/ (access 19.04.2108). FIGUEROA E., PASTEN, R. 2015. The economic value of forests in supplying local climate regulation. Australian Journal of Agricultural and Resource Economics, 59: 446–457. FOLKE, C., JANSSON, Å., LARSSON, J., CONSTANZA R. 1997. Ecosystem appropriation by cities. Ambio, 26 (3): 167– 172. FRIENDS OF THE HIGH LINE. Online access: http://www.thehighline.org/visit (access 19.04.2108). GÓMEZ-BAGGETHUN, E., DE GROOT, R. 2010. Natural capital and ecosystem services: The ecological foundation of human society. In R. M. HARRISON, R. E. HESTER (Eds.), Ecosystem Services. Cambridge: Royal Society of Chemistry,30: 105–121. GREEN, T. L., KRONENBERG, J., ANDERSSON, E., ELMQVIST, T., GÓMEZ-BAGGETHUN, E. 2016. Insurance value of green infrastructure in and around cities. Ecosystems 19: 1051–1063. JANUCHTA-SZOSTAK, A. 2012. Usługi ekosystemów wodnych w miastach (Services of water ecosystems in cities). Zrównoważony Rozwój – Zastosowania, 3: 22. KOUSKY, C., ZECKHAUSER, R. 2006. JARring actions that fuel the floods. In R.J. DANIELS, D.F. KETTL, H. KUNREUTHER (Eds.), On risk and disaster: lessons from Hurricane Katrina, University of Pennsylvania Press, Philadelphia, p. 59 – 73. LANDSCAPE INSTITUTE, 2009. Green Infrastructure: Connected and Multifunctional Landscapes. Online access: http://www.landscapeinstitute.org (access 29.10.2014). WWW.AMERICANTRAILS.ORG. Landscape of The High Line Park (1). Online access: http://www.americantrails.org/resources/railtrails/High-Line-New-York-Andberg.html (access 12.03.2018). WWW.ETSY.COM. Landscape of The High Line Park (2). Online access: https://www.etsy.com/listing/172626470/new-york-high-line-photo-nyc-photography (access 19.04.2018). LOREK, A. 2015. Usługi ekosystemów w aspekcie zrównoważonego rozwoju obszarów miejskich (Ecosystem services in the aspect of sustainable urban development). Folia Oeconomica, 2(313): 97-112. MCPHEARSON, T., ANDERSSON, E., ELMQVIST, T., FRANTZESKAKI, N. 2015. Resilience of and through urban ecosystem services. Ecosystem Services, 12: 152-156.
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MICHALSKI, T., ŚLIWIŃSKI, A., PAJEWSKA – KWAŚNY, R., TOMASZEWSKA, I. 2016. Ryzyko katastroficzne (Catastrophic risk). Polskie Wydawnictwo Ekonomiczne, p. 212. MILLS, E. 2007. Responding to climate change –THE INSURANCE INDUSTRY PERSPECTIVE. Online access: evanmills.lbl.gov/pubs/pdf/climate-action-insurance.pdf (access 14.03.2018). MUNICH RE. Loss events worldwide 2017. Geographical overview. Online access: https://www.munichre.com/en/homepage/index.html (access 20.03.2018). NARAYAN, S., BECK, M. W., WILSON, P., THOMAS, CH. J., GUERRERO, A., SHEPARD, CH. C., REGUERO, B. G., FRANCO, G., INGRAM, J. C., TRESPALACIOS, D. 2017. The value of coastal wetlands for flood damage reduction in the Northeastern USA. Scientific Reports. Online access: www.nature.com/scientificreports (access 20.03.2018). NATURE WORKS EVERYWHERE presented by The Nature Conservancy. A bioswale alongside a neighbourhood street in Seattle. Online access: https://www.natureworkseverywhere.org/resources/sustainableurban-design-toolkit/18/ (access 19.04.2018). OCEANS DEEPLY 2018. Premium protection: Why insurers are eager to cover coral reefs. Online access: https://www.newsdeeply.com/oceans/articles/2018/03/15/premium-protection-why-insurersare-eager-to-cover-coral-reefs (access 20.03.2018). PASCUAL, U., TERMANSEN, M., HEDLUND, K., BRUSSAARD, L., FABER, J. H., FOUDI, S., LEMANCEAU, P., JØRGENSEN, S. L. 2015. On the value of soil biodiversity and ecosystem services. 15: 11-18. PORTAL OF THE CITY GDAŃSK. City flood in Gdańsk`2016: traffic paralysis at the intersection of Grunwaldzka/Żołnierzy Wyklętych. Author: MEHRING, G. Online access: http://www.gdansk.pl/wiadomosci/12-miesiecy-po-wielkiej-ulewie-Jak-zmniejszyc-skutkipotencjalnej-kolejnej-RAPORT,a,83241 (access 19.04.2018). SAVE IT GREEN INFRASTRUCTURE FACT. Examples of curbside rain gardens. Online access: http://www.saveitlancaster.com/local-projects/sidewalks/ (access 19.04.2018). SYMBIOTIC CITIES NETWORK. Online access: http://www.symbioticcities.net/index.cfm?id=47825 (access 29.10.2014). SZCZEPANOWSKA, H. B. 2012. Miejsce terenów zieleni w strukturze zintegrowanego projektowania, zarządzania i oceny ekologicznej inwestycji miejskich (The place of green areas in the structure of integrated design, management and ecological assessment of municipal investments). Człowiek i Środowisko, 36(1–2): 25-49. THE CARIBBEAN CATASTROPHE RISK INSURANCE FACILITY (CCRIF SPC). Online access: http://www.ccrif.org/content/ccrif-spc-10th-anniversary-celebrations (access 20.03.2018). THE NATURE OF CITIES. What is the insurance value of urban ecosystems and their services? Online access: https://www.thenatureofcities.com/ (access 20.03.2018). URBAN GARDENS. Location of The High Line Park. Online access: http://www.urbangardensweb.com/2013/11/13/new-york-high-line-at-rail-yards-the-spururban-green-space (access 10.04.2108). WBCSD 2017. Incentives for natural infrastructure, Online access: https://www.wbcsd.org/contentwbc/download/3332/43656 (access 20.03.2018).
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USE OF CROP-ZOOM OPPORTUNITIES FOR THE INVESTIGATION OF THE QUANTITY AND QUALITY OF AGRICULTURAL LAND ON THE TERRITORY OF VINNYTSIA REGION Pavlo Kolodiy, Сandidate of economic Sciences, Assoc. Prof. Department of Geodesy and Geoinformatics Lviv national agrarian university Lviv,Ukraine e-mail:
[email protected]
Maryna Pidlypna, M.Sc.
Department of Geodesy and Geoinformatics Lviv national agrarian university Lviv,Ukraine e-mail:
[email protected]
Vitalii Yanovych, Ph.D.
Head of the Department of Processes and equipment of processing and food industries Vinnytsia National Agrarian University, Vinnytsia, Ukraine e-mail:
[email protected] Abstract The article is disclosed the method of study of the classification of crops in the automatic mode, the dynamics of the index ndvi, the calculation of the areas under separate crops, all at the level of each field and the state as a whole. The speed of the required information is obtained at the same speed as in the Land Viewer software product, which is based on the merging of the satellite data Landsat - 7.8 and Sentinel-2. The selection of the data of the research area of Vinnytsia district is carried out in the CROPZOOM software interface with the choice of the best resolution and visibility of the studied objects simultaneously with the public cadastral map of Ukraine. Selected data is generated on request of the user in real time, which allows to use the most diverse data in further investigation and to achieve the perfect result of the study. Key words: CROP-ZOOM, the classification of crops, the dynamics of the index ndvi Introduction The development of new research technologies for the quantitative and qualitative state of land is being made thanks to the development of technologies offered by the developers of the Land Viewer interface. Crop zoom software the product of EOS Data Analytics was founded by a native of Ukraine Maxim Polyakov, and is specialized in the analysis and processing of large GIS data. The tasks set out to be implemented in the future are applied in practice as in science, related to the reflection of differences in the state of vegetation in the process of their germination and predicting of their yields. Crop zoom ensures the automatic reproduction in diagrams or spectral profile the crop growth during their maturation over a certain period with dynamics over the last 3 agricultural years. If it is also possible to use the function of measuring the area in the visible contour of the area. Problem formulation The research of the quantitative and qualitative state of agricultural land in Vinnytsia region is carried out thanks to the development of technologies. The Crop zoom software provides a number of new operations that are required to perform specific tasks in a separate area study. The analysis of previous research Scientists of Ukraine are engaged in the study of the territories according to the data received from satellites. Lviv Polytechnic National University, Department of Photogrammetric and Geoinformatics 273
(Prof. O. Dorozhynsky), Kyiv National Technical University of Construction and Architecture (Professor S.Voytenko), Research Institute of Geodesy and Cartography (Professor Y.Karpinsky). Significant practical experience in using geoinformation technologies in Ukraine for various needs of the state, including land resources, is in SSPE "Geosystem", and their developments are used in practice on the territory of Ukraine and Europe. Study of the problem The intensive and modern pace of development of the society and the state of Ukraine as a whole includes new requirements for the protection and rational use of agricultural land, the accounting of quantitative and qualitative conditions, the accurate accounting of lands by their categories and the targeted use of lands of all forms of ownership. Since the beginning of 2018, tax legislation has changed, which in turn led to inventory of land registrations and their quantitative and qualitative characteristics. The relevant government agencies received the task, to provide fast reliable data, in accordance with the basis of the State Land Cadastre, and compare them with the statistical data of village councils that were provided since 2001. Relevant information and certain changes were entered 2 times in 1 year in the software of the corresponding form, in which the information about the owners and users of the land plots and their transition by categories of land, form of ownership, type of use, change of land were displayed. This entailed a complicated procedure for accounting of the use of land for the reporting past periods. Particular attention was paid to agricultural land since the Vinnytsia region is the leader among the regions of Ukraine in the volume of gross agricultural production, production rates, production per capita, grain production, sugar beet, potatoes, fodder products, meat, milk, cattle population, cows and poultry. Particular emphasis is placed on the economic feasibility of the use of arable land, farms and large farms of "agroholdings", which are used on a legislative level in accordance with lease agreements or use land shares (units),or use without legal documents land shares(units),the plots for conducting private peasant farms, land stock, agricultural reserve (state property). According to the report provided by the Department of Agricultural Development, Ecology and Natural Resources of the State Administration of Vinnytsia region, programs of support of agricultural producer are introduced in the framework of the implementation of tasks in economic development programs of Ukraine. The total amount of support to the agrarian sector is more than 6 billion UAH. 2,5 bln. UAH. Vinnytsia region has one of the most powerful agro- industrial complex in Ukraine, which demonstrates high rates of development and important results of management. In 2017, in January-October 2017, the total agricultural output increased by 13% compared to the same period of last year, including by 19.2% in crop production and by 1.2% in livestock production. According to the results of 10 months, the Vinnytsia region has taken the first place. The production of sugar beets has a direct dependence on the work of sugar factories. To date, there are only 6 factories remaining, but the modernization of their production allows processing of the same volumes of sugar beet, as in previous years. Potato production is also gradually increasing, but this product is produced by 99.7% in households by conventional technology. Land registries in the Vinnytsia region on the number of land users and landowners in the use of land, timely payment of land tax and rent, with the Department of Regional Statistics and registration of land in the form of 6-earth and 2-earth struck by their distinction. And the results of the village councils were generally different from true reality in real time. Quantitative accounting of the total area was very different. This is even very visible by using the Public Cadastral Map of Ukraine. It is impossible to reduce the data due to differences in the data provided by different services. The reports were expected, but unreliable. Specialists who go to the area and substantiate the data are not provided at all by the procedure of verification of reliability and comparison of statistical data. Relying on the data provided by the agronomists and lawyers of the existing private farms that rent the land on lease rights of formed land properly. Only the Head of the Vinnytsia Regional Agro industrial Complex tried to reproduce the true results for the district as a whole, went to the area and made an approximate report. Again, the results of coordinated activities to achieve the set goals did not give the desired result in the field of protection and rational use of agricultural land, the accounting of quantitative and qualitative state of land in terms of their categories and the targeted use of lands of all forms of property in the field of taxation. And the results presented by village councils were impressive in accordance with the "real picture". Quantitative accounting of the total area was very different. To bring data for a clear understanding of the present situation of the agricultural complex, requires a lot of human labor costs and the reliability of data, which is practically impossible to implement at the set time. For the possibility of realizing the tasks in the investigated areas of Vinnytsia region, a new software interface is used to ensure that information is obtained reliable, fast and qualitative for further coordination with relevant departments of the state land cadastre of Ukraine. We can, in our heavy 274
research, without any technical errors, relying on computer user knowledge, by applying Crop zoom the original product of EOS Data Analytics, founded by Maxim Polyakov, a Ukrainian native, who specializes in the analysis and processing of large GIS data. Crop zoom is oriented to the European market, while developers have left the service available free of charge for Ukraine. At least, this is the merit of a highly skilled specialist Nazariy Panchiy, who has achieved a high result. Direct cooperation and a clear understanding of the problems of modern Ukraine provided us with user access for further research in Ukraine. The problems in practice, as well as in science, are related to the reflection of the area of crops, types of crops, differences in the state of vegetation as they sprout, and predicting the yield of quantitative and qualitative state. Due to the capabilities of Crop zoom it became possible to obtain reliable data on the number of sowing areas of crops, their classification, state, development, deduction by the easiest means of dynamics of the NDVI index, reproduction of results in diagrams or profiles for a certain period with dynamics. It is also possible to use the functional measurement of the area along the visible contour of the area with an overlay on the Ukrainian "Public Cadastral Map" for targeting and linking to the area of users and owners; to compare the pace of changes in the quantitative and qualitative characteristics of different categories of land, type of land use, the definition of land, which is used without legal documents, which entails the administrative responsibility for avoiding payment of land tax. To solve a series of tasks it is easy to use in the browser Crop zoom, which is freely available, only on request of the registered user in the system, the necessary information can be obtained. The data on the request of a given task, which is readily available to the browser, it’s only necessary to select the research area and the Input Location data. We are exploring, in particular, Vinnytsia region, in particular, Stepanivka village council of Vinnytsia district as of August 2017 (Figure 1)
Fig. 1. Display of crops August 2017. Source: Own study based on the data from (KOLODIY, PODLIPNAY, YANOVYCH, 2018).
While exploring the object, we can draw a conclusion on the intensive use of agricultural land, as well as recognizing the crops in the colors specified in Legend. So, in the fields, we decipher the sown areas and crops, growing on them: orange - corn, pink - sunflower, green - winter wheat, yellow - winter rape, blue - soybean. To determine the owners of the users, we impose on the Public Cadastral Map of Ukraine by applying the same area of study for solving the required task, namely the coincidence of lease agreements in accordance with existing legal documents and the procedure for land use and statistical data provided on the above-mentioned reports. Relying on the data, provided by the agronomists and lawyers of the existing private and state owned enterprises, that rent the land on the right to lease the formed land properly. Or the use of land by the owners of agricultural land. The result is impressive with its data, which is very clearly reproduced from the comparison of data on certain fields that are being processed. Public cadastral map with overlapping data of Input Location on the territory, according to the previous picture(Fig. 1), located on the territory of Stepanivka village council of Vinnytsia district as of August 2017. (Figure 2) reflects the division into land shares (units), owned by citizens with the corresponding cadastral numbers, in turn, it allows us to conclude on the use of land with legal documents in the form of lease agreements and properly registered in accordance with the current legislation of Ukraine. 275
Fig. 2. Display of crops at once with the Public cadastral map of Ukraine August 2017. Source:Own study based on the data from (KOLODIY, PODLIPNAY, YANOVYCH, 2018).
Based on the information provided, inparticular, of the users of the fragment of the investigated object, the State Property Rights Service on real estate - compliance is only 73%. The rest of the territory is used without proper legal documents for a variety of reasons. Among them the main are the acceptance of the inheritance, re-registration of ownership at the stage of initial registration, the left land without owners and users, the disability of the population to make the documents properly at their own expense, accompanied by long-term manipulations on the part of authorities, which are empowered, unauthorized occupation of lands, etc. Thanks to Crop zoom in Crop Monitoring, it's possible to track the information about growing crops in certain areas of the research object for 3 years. The results obtained in percentage terms reproduce the following data on crops sown during 2016, 2017, 2018. Analytical accounting of main crops in percentages for 3 years (Fig. 3) and (Fig. 4).
Fig. 3. Analytical accounting of main crops for 3 years. Source:Own study based on the data from (KOLODIY, PODLIPNAY, YANOVYCH, 2018).
Summing up the research work with the new capabilities, provided by the specialists of the Crop zoom software, we were able to achieve the objectives and really evaluate the resource potential of Ukraine. We have highlighted the disadvantages of extensive use of land, estimated close to reality the economic feasibility of using arable land, farms and large farms of "agroholdings", using the resource potential of an agrarian country at the legislative level.
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Fig. 4. Chart showing the data of the studied cultures. Source:Own study based on the data from (KOLODIY, PODLIPNAY, YANOVYCH, 2018).
Conclusions Using the latest Crop zoom software will allow to receive simultaneously the necessary information in the attachments of Input Location and Crop zoom application with subsequent implementation, provide an opportunity to comprehend the authenticity of the provided information to match the number of data, but nowadays it is difficult for Ukraine, as there is a lack of State bodies funding for equipping of workplaces and even partially for conducting the courses for specialists of relevant organizations, territorial bodies. These all lead to negative shadow schemes for "no taxes" and rational(irrational) land use, to the enrichment of users, who use land in an intensive manner, not observing the protection and rational use with application of different chemicals against pests, which have a negative impact on agricultural products and in the future will lead to thediseases among consumers in general. Also, this software solve applied problems in various sectors of industry, water management, forestry, help to solve problems in construction monitoring, pipeline transportation and it is the most valuable in agriculture. References KOLODIY, P., PODLIPNAY, M. 2016. International Academy of Science and Higher Education “Innovative approaches to the solution of systemic problems of fundamental sciences and matters of practical implementation of innovations”, “Combination of factors of productivity, efficiency and aesthetics in modern requirements to functions and quality of technical devices and construction projects”: Peer-reviewed materials digest (collective monograph) published following the results of the CXV and CXVI International Research and Practice Conference and III stage of the Championship in Physics and Mathematics, Chemistry, Earth and Space Sciences, Technical sciences, Architecture and Construction. (London, December 18 - December 24, 2015), London: 31-32. PODLIPNAY, M., KOLODIY, P. 2015. Patent na korysnu model “Geoinformatiinyi metod dystantsiinogo zonuvannia zemli” (Patent for utility model “Geoinformation method of land zoning”). J. Biulyten, 24, UA 103624 U. ДОРОЖИНСЬКИЙ, O., ТУКАЙ ЛЬВІВ, P. 2008. Підручник. Фотограмметрія Львів: Видавництво Львівської політехніки, 332 с. Войтенко C. Збірник наукових праць Західного геодезичного товариства УТГК "Сучасні досягнення геодезичної науки та виробництва", Випуск І, 21: 2011. Карпінський Ю. Аналіз міжнародного досвіду створення інфраструктури геопросторових даних. Львів.: Сучасні досягнення геодезичної науки та виробництва. — Збірник наукових праць Західного Геодезичного Товариства. — Видавництво Національного університету «Львівська політехніка», випуск 1(11), 2006, p. 151—164. Raising the standard to new heights: http://www.harrisgeospatial.com. Land Viewer :https://lv.eosda.com (access 09.08.2018). 277
https://crop-monitoring.eos.com (access 09.08.2018). https://crop-monitoring.eos.com/crop-type (access 09.08.2018). https://crop-monitoring.eos.com/crop (access 09.08.2018).
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INFLUENCE OF INTERNATIONAL REGULATIONS ON SPATIAL PLANNING POWER IN POLAND – SEA AND MEDIATION Agata Kosieradzka-Federczyk, Ph.D. Faculty of Christian Philosophy Cardinal Stefan Wyszyński University Warsaw, Poland e-mail:
[email protected] – contact person
Wojciech Federczyk, Ph.D. Faculty of Christian Philosophy Cardinal Stefan Wyszyński University Warsaw, Poland e-mail:
[email protected] Abstract Local planning power (autonomy) refers to the local planning rights constitutionally guaranteed to local authorities. The basis for planning autonomy is the constitutional right of municipal self-government. Apart from national law, local planning power is shaped by international regulation. The aim of the article is to analyze the influence of the SEA and mediation on local planning power. The basis for the analysis is the polish legal system. The results of the SEA and associated public participation are not binding upon the local authority, they do play an important role in shaping the planning power enjoyed at local level. They cannot be seen as tools that limits power, but rather as sources of knowledge that allow a fully-conscious decision to be taken. Key words: physical development, spatial planning power, SEA, mediation Introduction The issue of spatial management and related real-estate disposal has many aspects that must be taken into account. This is a matter of the architectural order, but not only in the aesthetic dimension. The environment has a direct impact on the quality of life and work of people. The development of space affects the value of a property, and, above all, may limit the owner's intentions, e.g. a factory cannot be built in the center of a residential area. Due to the increasing dimension of public administration activity, it also requires the use of space for public facilities like: schools, hospitals, sewage treatment plants and power plants. They are necessary for further economic or social development, but they should not distort spatial order. All the indicated aspects should be taken into account as public authorities create spatial policy. Essential decisions regarding spatial order are made locally, at the level of the gmina in local physical development plans. The ability of the municipality to determine land development and the destination of particular properties for specific purposes is considered a manifestation of the planning authority of local authorities, as well as their independence where planning is concerned. They are concepts introduced in the Polish doctrine, but refer to concepts also developed in other countries. For example, in the German doctrine, the concept of planning authority "Planungshoheit" (NIEWIADOMSKI, 2003) is used. Planning authority is linked to the constitutional regulation passing the implementation of some public tasks to the municipality – under Art. 15 of the Constitution of the Republic of Poland. The doctrine also indicates that planning authority is the municipality's right to carry out relevant procedure and adopt a local plan (CZARNIK, 2010). However, in accordance with Art. 6 of the Act of 23 March 2003 on spatial planning and development (Dz. U. of 2000, item 1073 with amendments), the local plan is one of the determinants of the content of the right of ownership of real estate covered by it. Planning authority means the ability to make decisions binding upon other entities, e.g. property owners, unilaterally; as well as the ability to enforce local plan provisions (BĄKOWSKI, KASZUBOWSKI, 2012). A local authority's planning authority does not mean overall independence in determining the content of the local plan. It is limited, not only by the norms of the 2003 Planning Act, but also by other legal acts that also restrict the use of real estate (LEOŃSKI, et al., 2012). Gmina-level freedom to define the content of a local plan has also received analysis in the jurisprudence of the Constitutional Tribunal (MAJCHRZAK, 2010).
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Municipal competences in the field of spatial planning are also shaped by international regulations implemented in the Polish legal system in relation to the procedure for the adoption of a local plan, in the form of a strategic assessment of the impact of a local plan on the environment and resort to mediation as one of the forms of public participation. What, therefore, is the relationship between international regulations and the planning authority at gmina level in Poland? Do the former limit the latter? If not, how do they shape the scope of this power? The analysis takes account of two aspects: the first concerns the integration of the strategic environmental impact assessment (SEA) into a planning process, which creates an obligation for the gmina to prepare an environmental impact statement, ensure public participation in the proceedings, take comments and proposals in to account - which means not only a formal meeting to learn society’s positions, but also consideration of them, and, if they are adequate – the introducing of changes to the draft plan being prepared. The second aspect is the formalization of public participation in the planning procedure, in addition to the public discussion provided by the 2003 Act, and the possibility of remarks on the draft local plan being submitted. Procedure for adopting a local plan The spatial planning system developed in Poland under the 2003 Act corresponds to the structure of public administration and is implemented on three basic levels: national, regional and local. The main instruments for creating spatial order are at the local-authority level (of the so-called gmina). They are supplemented by planning standards at the regional level (voivodeship), while issues important for the whole country are determined at the national level (GÓRSKI, 2017). As indicated in the introduction, the local physical development plans are the typical acts dedicated to shape the spatial order. They may cover the entire municipality or a part. The plan determines the designation, the arrangement of the land and the land (Art. 4 par. 1 of the 2003 Act). The decision about starting a local plan procedure is made by the local council specifying the scope of the future plan. The Mayor is then obliged to announce in the press and by announcement, as well as in a manner customarily adopted in a given town, reveal that preparation work on the plan has started. Also specified are the form, place and time of the submission of proposals relating to a plan, not shorter than 21 days from the day of announcement. Proposals are considered by the head of a gmina as its local plan is being drawn up. Following preparation of the draft plan and the environmental impact statement, the local authority is to announce in the same way as before – at least 7 days prior to the date of exposition - that the draft plan has been completed. The draft plan and environmental impact statement are made available to the public for a period of 21 days (or longer), and after that time the local authority organizes a public discussion on the solutions adopted by it. The announcement sets the deadline for submitting comments on the draft plan. It may not be shorter than 14 days from the end of the project's presentation period. The nature of the comments depends on the public. They may question planned solutions or propose their alternatives (NIEWIADOMSKI, 2016). The head of the gmina is not bound by the content of the remarks, but he must examine them within 21 days of the deadline for submission. In case of acceptance, relevant changes to the local plan design are necessary. If the remarks are not found reasonable, the local authority head shall submit them to the municipal council, together with the draft plan. The council will ultimately decide on these remarks. Under the 2003 Act, the possibility of reservations and objections being submitted should remarks not be accepted was canceled. They were considered by the head of gmina, but not accepted by the council. The decision of the latter might be questioned before the administrative court. As a consequence, this was an instrument that postponed the final adoption of local plans (BĄKOWSKI, 2004). Under binding law, a local plan can be appealed against to the administrative court, once it has been accepted. The failure to consider comments on a draft plan can be questioned in that way. As a part of the planning procedure relating to the draft of a local plan, an SEA is carried out. The legal basis for this is in the Act of 3rd October 2008 on sharing information about the environment and its protection, public participation in environmental protection and environmental impact assessments (Dz. U. of 2017, item 1405). This Act assures the public participation in an SEA implemented as part of the planning procedure. However, it should be remembered that the comments made during an SEA could have a wider scope, as they may concern, not only the draft plan itself, but all environmental issues (FOGEL, 2014).
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Strategic environmental impact assessment An SEA is carried out in the process of a plan and program being adopted. The EIA relates to particular projects, while an SEA estimates the environmental effects of the entire plan. Chronologically, the EIA was applied earlier, though with time the attention turned to the necessity of estimating environmental effects of plans and programs. The need for better environmental protection led to the inclusion of impact assessment at the strategic planning level. The fact of the assessment only being carried out at project level, while general parameters, such as location, are decided upon at the planning stage, limited significantly any possibility of changes to a project being introduced, with the consequence that environmental protection (KOSIERADZKA, 2010). SADLER & VERHEEM (1996) define the strategic assessment as a formalized, systematic and comprehensive process of identifying and evaluating, the status ensuring that the relevant issues are on a par with economic and social considerations. The benefits that arise from proper application of the SEA are multidimensional: a high level of environmental protection is provided for, efficiency of development is raised, the capacity to adapt to climate change is increased, the prevention of costly mistakes is encouraged, governance is strengthened, and transboundary cooperation is facilitated. Polish law makes SEA mandatory for all planning acts, i.e. local physical development plans, as well as spatial planning studies at gmina level, etc. With few exceptions, an SEA is necessary in the event of changes to plans already adopted. The main features of the SEA have proved to be influenced greatly by international regulations. Although international law lacks a globally-applicable convention on SEA, mention can be made of the Protocol on Strategic Environmental Assessment to the Convention on Environmental Impact Assessment in a Transboundary Context, drawn up in Kiev on May 21, 2003, and applicable in Poland since 19 September 2011 (later known as the Kiev Protocol). This creates an international (32-party, 31 states mainly from Europe and the European Union) legal framework for carrying out an SEA in regard to plans and programs whose implementation may have a potentially significant impact on the environment, including health. The general obligation to carry out an SEA covered both sectoral programs (concerning agriculture, forestry, etc.) and spatial development plans or land-use plans that set the framework for future development consent for specific projects (as listed in Annexes I and II to the Protocol), and requiring an EIA under national legislation. In relation to plans and programs defining the use of small areas at the local level (small modifications of already adopted plans and programs, respectively), the Kiev Protocol allows a country to decide whether it requires an SEA or not. Polish law also extended the obligation that an SEA should be carried out to include plans covering only a small area. This is due to specific national conditions: a local plan can cover only part of the area of a given gmina. Usually the latter in fact decides to adopt a plan for a part of the overall area, and often only for selected plots. In such cases, failure to respect the obligation to carry out an SEA could result in one being carried out exceptionally, and not as a typical element of the planning process, as it is currently. This would have a negative impact on environment, and thus on the entire planning process at local level. The scope to be assessed as part of the SEA has been defined very broadly in the Protocol. It covers the impact on human health, flora, fauna, biodiversity, soil, climate, air, water, the landscape, natural areas, material assets, cultural heritage and interactions between these factors. Due to the preceding wording "any effect on the environment, including", it should be recognized that a study covers any impact on any element of the environment. The Protocol requires inclusion, in the procedure for adoption of a plan, of: the conclusion of the environmental report: the conclusions of the environmental statement, the measures to prevent, reduce or mitigate the adverse effects identified in the environmental statement, and comments received from public. Although the Kiev Protocol, which is a binding instrument of international law, plays a fundamental role in shaping the planning authority enjoyed by a local authority, other documents cannot be ignored. Particular attention should be devoted to the Voluntary Guidelines on Biodiversity-inclusive Impact Assessment, adopted during the eighth meeting in 2006 in Brazil. Although these are not binding, their impact on the planning authority at gmina level should be seen in view of the strong position that the Convention on Biological Diversity occupies among international environmental regulations. The Voluntary Guidelines underline the variety of possibilities across the world in which SEA is applied. It is for this reason that the focus is on biodiversity in the SEA, rather than procedural issues. The main role of the SEA is to equip the decision-maker with knowledge of the possible impact on the environment of a plan. The unquestionable relationship between planning procedure and the SEA lies in the way that the latter is carried out as communal planning acts are being prepared, and therefore at the stage when planning power is exercised.
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Public participation – mediation One of the features of planning power is its democratic character, which should be recognized in the wide participation of citizens in the planning procedure (LEOŃSKI et. al., 2012). The question is whether the Act of 2003 ensures such real participation. Elements of social participation are: • the submission of proposals before the draft of a plan is prepared; • participation in public discussion; • the submission of comments on the draft plan. The regulations in force do not impose any limits on the public who can take advantage of these forms of social participation. This means that everyone is entitled to participate. At the same time, however, the conclusions and comments are not binding on the decision-maker. Introducing spatial order naturally leads to conflicts of interest. There are many possible areas of such conflicts: public and individual interest, different private interests or competing public policy goals (WOŹNIAK, 2012). Some claim that the procedure does not allow for the resolving of conflicts, but only for the choice of one option from among many, on how develop land. The solution adopted looks like social consultations, rather than public participation, which should involve cooperation and not only the expressing of opinions (HAŁADYJ, 2014). On the other hand, public discussion may be limited to the presentation of different views, even without conclusions being reached. The Act of 2003 indicates only its public nature, while prohibiting restrictions on access to participation in the discussion. However, there are no regulations on how the discussion should be organized. The main effect of the discussion is a protocol that is not formally binding in the further procedure. Empirical research indicates that, in practice, discussions might be organized for the sole purpose of compliance with the statutory obligation, as opposed to as a debate on spatial order (DAMURSKI, 2014). This legal regulation is criticized as insufficient to ensure protection of a local community’s interests. It is therefore necessary to look for more effective methods of participation. One of them is mediation – i.e. proceedings with the participation of an impartial person, whose main aim is to resolve disputes arising during planning. Such a form of resolving disputes is inter alia indicated by the Council of Europe in its (2001) Recommendation 9. Under this, the widespread use of alternative means of resolving administrative disputes can allow these problems to be dealt with; and can bring administrative authorities closer to the public. The necessity of mediation techniques being used by decision-makers has been noticed around the world for many years (FORESTER, 1987). Mediation with the participation of an independent person provides for a reduction of emotions in a conflict and, above all determines the parties in the conflict and the focus on their real expectations. Mediation is successful when parties reach a compromise. But even if the matter ends with a clarifying of doubts, this is important for the decision on the content of a local plan. In Poland, mediation in spatial planning matters has not been introduced into the legal system, despite the fact that, in 2008-2010, during governmental work on amendments to the 2003 Act, mediation was foreseen as an obligatory method of resolving conflicts arising around comments to a draft local plan. However, it is possible to point to an example of mediation carried out in Gdańsk and allowing for a change in a draft in line with the expectations of the public as regards a conflict over the development of a city park (FEDERCZYK, 2013). However, it is necessary to use such procedure within the framework of the applicable planning procedure - as an extensive form of public discussion, especially when a particular project raises many emotions and conflicts. It must be remembered that the passing of a plan does not denote an end to conflict, as its introduction means changes in the space stakeholders must live in. Conclusions If the answers to the questions set out in the introduction do not raise any doubts, international regulations (on SEA) do influence the shape of gmina’s planning power, though they do not limit it. The relationship between planning power and international regulations (on SEA) should be seen as increasing the amount of knowledge held by a local authority preparing the draft of a local plan. Acquisition of new knowledge allows the authority to make a more informed decision regarding the adoption of the plan, or to make changes. This is because the result of an SEA does not bind an authority to the final decision it is to take. The environmental statement prepared as part of the process of planning provides comprehensive information on the draft plan being prepared, the environmental condition to which it relates, the environmental objectives established at international, Community and national levels relevant to the plan
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being drawn up, and the ways in which these objectives and other environmental problems were taken account of in the development of the plan. Similarly, comments and applications submitted by the public allow the authority to get to learn of residents’ opinions regarding the solutions proposed in the draft plan, while the body is not obliged to take them into account. Assessment is an important element of the process by which interests for the instruments in spatial management at local level are balanced, with relevant spatial data supplied to the entities active in spatial policy (FOGEL, 2011). The non-binding nature of the results of the SEA and public participation does not mean that they are unnecessary or useless. Additional knowledge gained by the body in two aspects so important for environmental protection – integration of environmental issues into the planning system and strengthening public participation in matters related to environmental protection (both present so commonly in numerous international acts), represents an important aspect of the implementation of sustainable development. Mediation allows arrangements that will be included in the local plan to be made. The necessity of these being taken into account by local authorities (the head and council) cannot be seen as a limitation of planning power. The gmina as an area administered by a local authority does nevertheless represent a community of residents, as Art. 166, para. 1 of Poland Constitution makes clear. There is more involved here than just the authorities. Mediation is one of the solutions that allows to for a minimizing of social conflicts and the development of spatial solutions acceptable to a local community; with maximum possible account being taken of the reconciling and pursuit of different interests. While the results of the SEA and associated public participation are not binding upon the local authority, they do play an important role in shaping the planning power enjoyed at local level. They cannot be seen as tools that limits power, but rather as sources of knowledge that allow a fully-conscious decision to be taken. References BĄKOWSKI, T. 2004. Ustawa o planowaniu i zagospodarowaniu przestrzennym. Komentarz. (Commentary to the Act of 23 March 2003 on spatial planning and development). Kantor Wydawniczy Zakamycze, Kraków, p. 327. BĄKOWSKI, T., KASZUBOWSKI, K. 2012. Regulacje tak zwanych specustaw inwestycyjnych wobec samodzielności i władztwa planistycznego gminy. In: Skrzydło-Niżnik I, (Editor) Przestrzeń i nieruchomości jako przedmiot prawa administracyjnego: publiczne prawo rzeczowe. (Regulations of the so-called investment specializations against the independence and planning authority of gmina. In: Space and real estate as a subject of administrative law: public property law). Wydawnictwo Prawnicze "LexisNexis", p. 263-276. CZARNIK, Z. 2010. Istota i zakres władztwa planistycznego gminy (The essence and scope of the planning power of gmina). Administracja: teoria, dydaktyka praktyka, 3(20): 5- 30. CZARNIK, Z. 2017. Ochrona interesów społeczności lokalnej i gminy w planowaniu przestrzennym, In: Kmieciak Z. (Editor), Partycypacja w postępowaniu administracyjnym. W kierunku uspołecznienia interesu prawnego (Protection of the interests of the local community and gmina in spatial planning, In: Participation in administrative proceedings. Towards socialization of the legal interest). Wolters Kluwer, p. 169-192. DAMURSKI, Ł. 2014. Dyskusja (nie)publiczna. Problem dostępności dokumentów planistycznych na poziomie gminy (Discussion (not) public. The problem of the availability of planning documents at the gmina level). Samorząd Terytorialny, 4: 38-50. FEDERCZYK, W. 2013. Mediacja w procesie planowania przestrzennego w prawie polskim (Mediation in spatial planning in polish law). In: Alternative methods of legal disputes resolving (ADR),. Lwów, p. 100110. FOGEL, A. 2010. Środowiskowe aspekty uprawnień społeczeństwa w sporządzaniu studiów uwarunkowań i planów miejscowych (Environmental aspects of the public's entitlements in the preparation of studies of conditions and local spatial plans). Samorząd Terytorialny, 5: 46-61. FOGEL, A. 2011. Prawna ochrona przyrody w lokalnym planowaniu przestrzennym (Legal protection of nature in local spatial planning). Instytut Gospodarki Przestrzennej i Mieszkalnictwa, Warszawa, p. 225. FORESTER, J. 1987. Planning in the Face of Conflict: Negotiation and Mediation Strategies in local Land Use Regulation. Journal of the American Planning Association, 9: 443-446. GÓRSKI, M. 2017. Strategie, plany i program (Strategies, plans and programs). In: (Editors) Hauser R., Niewiadomski Z., Wróbel A., System prawa administracyjnego. Prawo administracyjne materialne ( Administrative law system, material administrative law). Ch BecK ,Warszawa, p. 187-230.
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HAŁADYJ, A. 2014. Konsultacje czy partycypacja? Refleksje terminologiczne w odniesieniu do udziału społeczeństwa w ochronie środowiska (Consultation or participation? Terminological reflections regarding public participation in environmental protection). In: Dolnicki B. (Editor) Partycypacja społeczna w samorządzie terytorialnym (Social participation in local government). Lex a Wolters Kluwer business, Warszawa, p. 671-686. KOSIERADZKA, A. 2010. Strategiczna ocena oddziaływania na środowisko planów i programów w prawie włoskim – porównanie rozwiązań przyjętych w prawie polskim (SEA impact of plans and programs in Italian law - a comparison of solutions adopted in Polish law). In: (Editors) Cieślak Z., Fogel A., Wartości w planowaniu przestrzennym. Instytut Gospodarki Przestrzennej i Mieszkalnictwa, Warszawa, p. 117-130. LEOŃSKI, Z, SZEWCZYK, M., KRUŚ, M. 2012. Prawo zagospodarowania przestrzeni (The law of spatial development). Lex a Wolters Kluwer business, Warszawa, p. 59, 61. MAJCHRZAK, B. 2010. Wartości w planowaniu przestrzennym w wybranych orzeczeniach Trybunału Konstytucyjnego (Values in spatial planning in selected rulings of the Constitutional Tribunal). In: (Editors) Cieślak Z., Fogel A., Wartości w planowaniu przestrzennym. Instytut Gospodarki Przestrzennej i Mieszkalnictwa, Warszawa, p. 51-64. NIEWIADOMSKI, Z. 2002. Zagospodarowanie przestrzenne. Zarys systemu (Spatial planning. Outline of the system). Wydawnictwo Prawnicze LexisNexis, Warszawa, p. 178. NIEWIADOMSKI, Z. 2016. Planowanie i zagospodarowanie przestrzenne. Komentarz (Spatial planning and development. Ch Beck, p. 667. SADLER, B., VERHEEM, R. 1996. Strategic Environmental Assessment. Status, Challenges and Future Directions, Ministry of Housing, Spatial Planning and the Environment. The Netherlands, and the International Study of Effectiveness of Environmental Assessment, p. 188. WOŹNIAK, M. 2012. Rola mediacji w rozwiązywaniu konfliktów przestrzennych (Role of mediation in solving spatial conflicts). ADR Arbitraż i Mediacje, 2: 33-47.
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TERRITORIAL SCOPE OF APPLICATION OF THE GENERAL DATA PROTECTION REGULATION Sylwia Kotecka-Kral, Ph.D. Center for Legal and Economics Issues of Electronic Communications Faculty of Law, Administration and Economics University of Wroclaw Wroclaw, Poland e-mail:
[email protected] Abstract As a result of the rapid development of the information society, the intangible good that is information – and particularly personal data – has become an exceptionally valuable product. We are also in the midst of a phenomenon entirely unknown in the 1990s – methods of processing personal data using such means as cloud computing technology, so-called big data. The previous model of EU regulation that made the applicability of EU law dependent on economic activity being conducted by a data administrator within the territory of a Member State, or the use of data processing means located within that territory, is today insufficient and obsolete. It became necessary to abandon the principle of territoriality introduced by Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data, replacing it with a more elastic means of regulating the application of EU law. The objective of the present work is to present the territorial scope of the Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). Keywords: personal data, data subject, personal data processing, personal data controller, processing entity, territorial scope of application of GDPR Introduction As a result of the rapid development of the information society, the intangible good that is information – and particularly personal data – has become an exceptionally valuable product. Functioning in the information society is inextricably linked with the processing of personal data, which has evolved into something resembling almost a new currency. It is estimated that the market value of the total volume of data processed online within the borders of the European Union will reach EUR 739 bn by the year 2020. The ease with which information is transmitted and the universality of access to the open teleinformatics system that is the internet have led to the development of an entire segment of services provided online with tremendous significance for the economy. Previously unknown business models and means of providing services have emerged. Importantly, we are also faced with means of processing personal data completely unknown in the 1990s, such as with the use of cloud computing technology id est so-called big data. In the era of globalization, expansion of trans-border services, and the information society, in which online activities can be conducted from virtually any place on the planet, the territorial scope of application of legal regulations is taking on an increasing significance. The previous model of EU regulation that made the applicability of EU law dependent on economic activity being conducted by a data administrator within the territory of a Member State, or the use of data processing means located within that territory, is today insufficient and obsolete. Presently, the omnipresence of the internet is leading to the data of EU residents being processed – frequently on a mass scale – outside the EU itself, by personal data controllers who are not governed by the stringent European standards applicable to personal data protection. American entities are particularly distinct in this respect, as in many fields of technology they tend to be more innovative than their European counterparts. They are offering with increasing frequency services with more robust functionalities than those offered by European competitors, thereby acquiring large numbers of customers within the borders of the EU. As concerns standards of personal data protection, there is at present a great deal of diffusion; in an age of expansion of services provided globally, combined with the strong position on the internet of service providers from outside the EU, this is by no means a beneficial trend. In particular, data subjects from states offering high personal data protection standards are frequently unaware that they are using the services of personal data controllers who themselves are not governed by regulations that would ensure a
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level of personal data protection aligned with EU standards. It became necessary to abandon the principle of territoriality introduced by Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data, replacing it with a more elastic means of regulating the application of EU law. In recent years, the Court of Justice of the European Union (CJEU) has engaged in the broad interpretation of the provisions of Directive 95/46 concerning the scope of its territorial applicability. Of particular importance to the subject of this paper are the Court’s rulings in the cases C-131/12, Google Spain, C-230/14, Weltimmo, and C-191/15, Verein für Konsumenteninformation versus Amazon EU Sárl. All these cases, while from different perspectives, addressed the issue of the territorial scope of application of the regulations contained in Directive 95/46 and their implementation by the national regulations of EU Member States. The territorial scope of the Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) is aligned with the guidelines set out in the CJEU’s judgments in those cases. One of the primary objectives to be achieved by the General Data Protection Regulation, in replacing Directive 95/46, is the adaptation of provisions of EU law to the realities of the information society and the present state of technology. For these changes to achieve their stated goal and to provide real protection of data subjects, it was vital to expand the territorial scope of EU law on the protection of personal data. Protection of natural persons in conjunction with the processing of personal data, which results directly from Art. 8(1) of the Charter of Fundamental Rights and Art. 16(1) Treaty on the Functioning of the European Union, has been elevated to the status of a fundamental right. The references provisions state that each individual has the right to the protection of personal data concerning him or her. This protection should be ensured regardless of the location of the controller or entity engaged in processing, as well as the location of technical means used for such processing. In the information society, jurisdiction based on the principle of territoriality means that data subjects are finding it increasingly difficult to pursue effective protection of their rights regarding personal data protection; these difficulties result from the inability of EU oversight bodies to effectively exert control over personal data controllers operating on the internet. Pursuant to Art. 288 TFEU, the Regulation is of general reach, its provisions are binding in their entirety, and they are directly applicable in all Member States. By its very nature it constitutes an element of municipal legal systems without the necessity of any acts of transposition, and evokes direct effects in relation to individuals. Regulations encompass both vertical and horizontal effect without exception. The General Data Protection Regulation is of this very same nature, performing the role of a harmonizing act with regard to the law on protection of personal data within all Member States. The employment of a Regulation as the form of harmonization means the derogation of the legal basis for the applicability in Poland of the Personal Data Protection Act in its present form (as legislation implementing Directive 95/46), which constitutes comprehensive regulation of the rules of conduct in the processing of personal data and the rights of people whose personal data is processed. From the perspective of the General Data Protection Regulation, the application of solutions not provided for in the Regulation and not expressly left for regulation by municipal law is prohibited. However, GDPR does not introduce full harmonization understood as the total (complete) shaping of regulations in a given area and the impermissibility of application of national legislation. Territorial scope of Directive 95/46 in the context of the CJEU judgment in C-131/12, Google Spain While the judgment handed down in 2014 in C-131/12, Google Spain, primarily addresses the “right to be forgotten,” it also contains an interpretation of the provisions of Directive 95/46 concerning its territorial scope. The Court acknowledged Spanish jurisdiction over a controller of personal data with its seat located in the United States. To this end, the CJEU engaged in interpretation of the provisions of Directive 95/46 in respect of the conducting of economic activity. It held that Art. 4(1)(a) of Directive 95/46 is to be interpreted as meaning that processing of personal data is carried out in the context of the activities of an establishment of the controller on the territory of a Member State, within the meaning of that provision, when the operator of a search engine sets up in a Member State a branch or subsidiary which is intended to promote and sell advertising space offered by that engine and which orientates its activity towards the inhabitants of that Member State. It thus held that the Spanish data protection authority exercised jurisdiction over Google Inc., a company incorporated in the United States, and which had only a subsidiary engaged in the promotion and sale of advertisements. A different interpretation of that provision of Directive 95/46 and different ruling by the Court would lead in that particular case to a situation difficult to accept in which a Spanish citizen, using an internet search engine offered in the Spanish languages to find the webpage of a Spanish newspaper with information about events taking place within the borders of Spain
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and directly affecting that citizen, in which that individual’s personal data was given, would be unable to pursue the enforcement of rights under Spanish jurisdiction. Territorial scope of Directive 95/46 in the context of the CJEU ruling in C-230/14, Weltimmo Differently than in the judgment in C-131/12, Google Spain, when ruling in C-230/14, Weltimmo, issues concerning the scope of jurisdiction related to determining the applicable law within the European Union, and more specifically – in relation to the facts of that particular case, was the authorized oversight body that of Slovakia, or of Hungary, and also under which national regulations that oversight should be exercised. Weltimmo, a company incorporated under Slovakian law, claimed that it was engaged in economic activity exclusively in Slovakia, id est in the Member State in which it has its registered seat. At the same time, the Hungarian oversight authority, basing on interpretation of Art. 4(1)(a) of Directive 95/46, claimed jurisdiction over that company, arguing that the activity of Weltimmo, the operator of an internet webpage with announcements, was focused on the territory of Hungary. In this case as well the Court supported a broad interpretation of Art. 4(1)(a) Directive 95/46, in its judgment taking into account the role of the internet. The position taken by the CJEU was that the provisions of Directive 95/46 supply “a flexible definition of the concept of ‘establishment’, which departs from a formalistic approach whereby undertakings are established solely in the place where they are registered. Accordingly, in order to establish whether a company, the data controller, has an establishment, within the meaning of Directive 95/46, in a Member State other than the Member State or third country where it is registered, both the degree of stability of the arrangements and the effective exercise of activities in that other Member State must be interpreted in the light of the specific nature of the economic activities and the provision of services concerned. This is particularly true for undertakings offering services exclusively over the Internet.” The Court adopted a very broad interpretation of the notion of an “establishment,” holding that “the presence of only one representative can, in some circumstances, suffice to constitute a stable arrangement if that representative acts with a sufficient degree of stability through the presence of the necessary equipment for provision of the specific services concerned in the Member State in question.” In the judgment analysed here, the Tribunal stated that for recognition of the jurisdiction of the Hungarian authority it was sufficient for the claimant to operate on the internet a website with listings for real estate located in Hungary, provided in the Hungarian language, possessing a representative that conducted in a continual manner the undertaking’s business in Hungary by inter alia representing the undertaking in administrative and judicial proceedings, with a bank account opened in Hungary, and possessing a postal address in Hungary for conducting the undertaking’s business. Such activity is sufficient to rule that Weltimmo conducts economic activity within the territory of Hungary. It would therefore seem that the notion of an “organisation” is obviously more flexible and broader than its definition under Polish law, which we shall discuss later on. This judgment is of exceptionally far-reaching significance – it lends support to the application of a broad interpretation of the notion of “engaging in economic activity” and confirms the correctness of the interpretation under which the understanding of Art. 4(1)(a) Directive 95/46 should be based on the territory where the effective and actual performance of economic activity is done through continual measures, and not on the location of the registered seat of the organization processing personal data. Territorial scope of Directive 95/46 in the context of the CJEU judgment in C-191/15, Verein für Konsumenteninformation versus Amazon EU Sárl In a successive judgment, handed down on the basis of Directive 95/ but which remains applicable also after the implementation of GDPR, the CJEU held that an “organization” is located in the territory of a Member State to which the undertaking directs its activity if it occurs that the undertaking processes data in the context of economic activity within that Member State. The determination as to whether such circumstances exist is a matter for national courts. Regulations contained in GDPR The territorial scope of application of GDPR is provided for in Art. 3 of the Regulation and explained in paragraphs 22-25 of the preamble.
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Article 3(1) GDPR Pursuant to Art. 3(1), the Regulation applies to the processing of personal data in the context of the activities of an establishment of a controller or a processor in the Union, regardless of whether the processing takes place in the Union or not. The Regulation thus applies to processing activities related to the activity of the controller or the processor which possesses an establishment within the territory of the EU. It should be emphasized that “processing of personal data in the context of the activities of an establishment of a controller or a processor” does not mean that such processing must be performed by that particular establishment. For the provisions of the GDPR to be applicable, it is sufficient that there be a connection between the act of processing data and the activity of a given establishment of a controller or processor located within the territory of the EU. Concerning the content of Art. 3(1) GDPR, it is essentially analogical to Art. 4(1)(a) Directive 95/46. In the Polish version, the English phrase “in the context of” from the Directive was translated as “w kontekście”, while in GDPR, the English version remains unchanged, but the Polish translation now reads “w związku”. Apart from the complicated matter of translation of the notion of an “establishment” (to be addressed later on), two significant differences in comparison to Directive 95/46 are: 1) the addition of reference to “processor”, which was not given in the now-invalid Directive – and thus another element expanding the scope of application of EU legislation which referred in Directive 95/46 solely to controllers, and 2) the indication that this provision is applicable regardless of whether such processing is taking place within the EU – also emphasized by the extraterritorial aspect of Art. 3(1) GDPR, despite the fact that that article, through the criterion of location of the establishment of a controller or a processor within the EU, is de facto based on the principle of territoriality. It is undoubtedly crucial to elaborate three notions employed in Art. 3(1) GDPR, specifically: “działalność” (operated by an organization), “jednostka organizacyjna”, and “podmiot przetwarzający”. Because the notions of “dane osobowe” and “przetwarzanie danych osobowych” are already wellestablished on the basis of previous legislation, the reader is referred to the rich literature related to it. The notion of “activities (of an establishment)” The provisions of GDPR do not directly define the notion of “activities of an establishment of a controller or a processor”; interpretation within this scope should, however, strive to encompass the broadest possible understanding of this notion. Doubtlessly this does not mean only the notion of economic activity, which is in a way confirmed by Recital 6 GDPR, which mentions the use by both private companies and public authorities of personal data in their activities in an unprecedented scale. This can thus be understood as both public activity interpreted very broadly to include the activity of public administration, as well as activity without a profit motive, undertaken by foundations and other similar organizations. Indeed, there is no reason to assume this should not mean the undertakings of natural persons, including those not operating establishments. For the application of GDPR it is irrelevant where the processing of personal data takes place – the only important thing is whether the processing is done in the context of the activities of an establishment of a controller or a processor in the Union. Circumstances such as the physical location of servers or the use of services from subcontractors outside the EU are thus irrelevant to determining the scope of application of GDPR. The notion of an “establishment of a controller or a processer” A key element in the modified territorial scope of EU regulations on protection of personal data is the notion of an “establishment” employed in Art. 3 GDPR. This notion, equally important in Directive 95/46, was translated there as “prowadzenie działalności gospodarczej”, whereas in the new Regulation it reads as “działalność prowadzona przez jednostkę organizacyjną”. The phrase “establishment” was for years repeated in judgments of the CJEU, as well as in opinions of the Article 29 Working Group. In the course of work on the Polish translation of the General Data Protection Regulation, many different versions were considered for translation of the English notion of “establishment”, including “siedziba”, “jednostka”, “oddział”, “miejsce prowadzenia działalności”, “miejsce prowadzenia przedsiębiorstwa”, and “zakład”. Ultimately, however, the phrase “jednostka organizacyjna” was adopted. This change, itself revolutionary, thus only took place in reference to the Polish version of the text of GDPR. What results from this is that the phrase employed by translators in the Polish version of Directive 95/46 “prowadzenie działalności gospodarczej” had a narrower scope than the notion of “establishment” as understood by the Court of Justice, and did not accurately reflect the intentions of the European legislator.
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One of the arguments in favour of such a translation into Polish was the imprecision of the previous solution – indeed, GDPR is applicable also in respect of personal data and processors who are not engaged in operating an establishment. For example, the activity of public administration, churches and faith unions, as well as of many nongovernmental organizations cannot be considered economic activity, but it is encompassed by the scope of application of the Regulation. At the logical level, this entirely excludes the possibility of invoking in Art. 3 GDPR the notion of “prowadzenie działalności gospodarczej” (which we may translate into English as “conducting economic activity”. In light of the foregoing, despite the commencement of the application of GDPR, the indications of CJEU referring directly to interpretation of the notion of “establishment” contained in judgments handed down during the period in which Directive 95/46 was in effect, particularly in the cases C-131/12 Google Spain, C-230/14 Weltimmo, and C-191/15 Verein für Konsumenten-information, retain their relevance also in relation to interpretation of the notion of “jednostka organizacyjna” (as the Polish translation of “establishment”) following the entry into force of the GDPR. The General Data Protection Regulation does not contain a legal definition of the notion of an establishment, which would seem a deliberate act on the part of the European legislator, one designed to give the Regulation greater flexibility in defining the territorial scope of application of its provisions. In the absence of a definition, the Court of Justice or the European Data Protection Board will be able to exert greater influence on the interpretation of that notion and adapt its understanding to new models and the state of the art in personal data processing. Through the broad scope of application of European legislation, it will also facilitate more effective protection of the rights of data subjects in the information society, particularly the broad applicability of EU supervisory authorities. Because “jednostka organizacyjna” is a concept deeply rooted in the Polish legal system, in both civil law and administrative law regulations, the notion is deserving of particular attention. At the same time, there shouldn’t be even the slightest doubt that the notion of “establishment” in Art. 3 GDPR should be treated as an autonomous notion of EU law in respect of protection of personal data, and should thus be interpreted without reference to national regulations. The notion of an “establishment” is broader than the notion of seat, place of residence, branch, or office of an enterprise. In this context, Recital 22 in the preamble of GDPR indicates that the notion of an establishment assumes the effective and real conducting of activity through stable structures. The legal form of those structures, regardless of whether a branch or a subsidiary with juridical personhood, is not the deciding factor in this respect. It is of no relevance in what legal form the activity of an establishment is conducted. There is thus no reason to exclude branches or subsidiaries solely on grounds of the form of the establishment from the application of GDPR. The Regulation puts emphasis on the factual circumstances and does not require the existence of a name, seat, or body. Although on grounds of Art. 3 GDPR there is no formal distinction between personal data controllers from the public and private sector, the particular solutions provided for in the Regulation in areas like the scope of legal bases for the processing of data exhibit certain differences depending on whether a given entity is part of the public or the private sector. The scope of application of GDPR encompasses entities in both the public and the private sectors. In respect of public entities, the scope of application of GDPR encompasses organs of public administration, id est organs of central governmental administration, local self-government, and all entities or organizations granted by statute competences within the scope of administration. Regulation of territorial scope within national legislation is important in the context of a situation in which the GDPR allows the law of Member States to modify the general principles provided for in that legal act. Here we should point out an issue of potentially large practical significance – in particular, the Regulation, in the event of discrepancies within national legislation, does not harmonise the territorial scope of their application, nor does it provide any conflict of laws rules. This means that, contrary to the original intentions of the European legislator, the same controller or processor of personal data operating in a trans-border manner can be governed by provisions of the legislation of particular Member States that are in conflict with one another. This can occur in a limited number of cases, particularly when national regulations seek to add detail to the issue of the expression of consent by a (Art. 8(1) GDPR), the processing of genetic, biometric, or other data concerning health (Art. 9(4) GDPR), and in respect of exclusion of the possibility of expressing consent to the processing of particular categories of personal data (Art. 9(2)(a) GDPR). For example, the Polish regulations adopted on the basis of Art. 8(1) GDPR set a threshold of 13 years, Austrian regulations – 14 years, and German regulations – 16 years. When it comes to services of the information society, the processor processing the personal data of children from those three Member States will thus be governed by three national rules in conflict with one another, as the Regulation does not provide for separate rules to avoid conflict of laws issues. This is why it will also be of importance to determine the territorial scope of application of particular national legislation. It should be considered that the primary criterion for determining the territorial scope of the
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provisions of the General Data Protection Regulation is possessing an establishment within the territory of the EU, and only in the event that condition is not fulfilled, proceeding to the conditions provided for in Art. 3(2 and 3) GDPR. The notion of the processor The General Data Protection Regulation contains a legal definition of data processor. Pursuant to Art. 4(8) GDPR, the notion of “processor” means a natural or legal person, public authority, agency or other body which processes personal data on behalf of the controller.” The definition of a processor thus encompasses an equally broad scope of entities as the definition of a controller. This notion plays an important role in the context of ensuring the confidentiality and security of data processing when considering that it serves to indicate the entity engaged in processing operations on behalf of the controller, and in consequence establishes a certain framework for its activity. The controller and the processor are participants in the primary mechanism of processing undertaken with a specified goal and scope. However, the mere presence of a processor within the processing process is dependent on a decision of the controller, who is free to select a mode of processing requiring the exclusive participation of people directly subordinate to the controller and authorized to engage in processing under that controller’s direct supervision, but which can also potentially decide to engage other entities acting on its behalf in the process of data processing. It should, however, be kept in mind, and with regard to the wording of Art. 28, that in certain circumstances the fact of entrustment of data processing does not result from the autonomous decision of the controller, but rather from legal instruments regulating a given processing. Such cases can arise primarily in the public sphere. In the light of Art. 28(3)(a), the processor can essentially work based exclusively on the documented instructions of the controller. This means that it is the controller that determines the purposes and modes of processing, including the decision to entrust data to a processor for the processing of that data in the controller’s name. The activity of a processor must thus remain within the framework defined by the controller and is essentially devoid of any discretion and freedom. The binding of a processor by the controller by way of purposes and modes of data processing sets out the boundaries of the processor’s activities. Article 3(2) GDPR Far more revolutionary is Art. 3(2) GDPR, which states that “(t)his Regulation applies to the processing of personal data of data subjects who are in the Union by a controller or processor not established in the Union, where the processing activities are related to: a) the offering of goods or services, irrespective of whether a payment of the data subject is required, to such data subjects in the Union; or b) the monitoring of their behaviour as far as their behaviour takes place within the Union. Indeed, this provision entirely decouples the application of EU rules from the principle of territoriality, in practice essentially marginalising the meaning of the condition set out in para. 1 of that provision, itself repeated from Directive 95/46. Instead of this, a solution was introduced which can be defined as “targeting”, abandoning territoriality in favour of the principle of protection. New EU data protection principles will be applicable to everyone offering goods and/or services to data subjects in the EU or monitoring the conduct of such entities, to the extent it is done within the EU – and thus “targeting” data subjects with their activities. They are applicable regardless of whether the data subject engages in any activity at all. It is for the controller or processor of data to assess whether the nature of their activity can lead to assuming obligations arising from the provisions of the General Data Protection Regulation. The provisions of GDPR encompass entities providing services via the internet, and also – because of the reference to monitoring of behaviour – those which employ methods based on profiling, such as for marketing purposes, or processing personal data within the context of so-called big data. This is the case regardless of the location of the individual processing personal data. This means that even entities located outside the EU will be required to apply European personal data protection legislation. This is a very significant change with respect to the previous regulations in force, under which entities with their seat in a third-party state and engaged in the processing of personal data from outside the European Economic Area or employing technical measures located within the territory of Poland exclusively for the purpose of transmitting data to a third-party state were not subject to the Polish Personal Data Protection Act of 29 August 1997. The previous legal environment made it possible to escape from the regime of strict and formalized personal data protection standards provided for in Polish regulations. International capital groups could also organize their personal data processing processes in such a manner that the entity deciding on purposes and means of data processing is in fact e.g. a holding
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company with its seat in the United States, while the activity of the local Polish subsidiary was limited to forwarding data to its parent company. In this manner it was possible to escape the rigorous Polish personal data protection laws. GDPR does not allow for such a possibility. For example, under the Regulation, a company with its seat in the USA and operating a worldwide internet shop available also in Poland will have to operate the Polish portion of its business in compliance with GDPR, even if it processes data via technical means located within the borders of the USA. A long-term consequence of this formulation of territorial scope will be the necessity of many data controllers and processors from third-party states (i.e. from outside the European Economic Area) adopting the assumption that specific personal data processing operations are governed by the provisions of GDPR, as there is a risk that some of the users of a given service are EU data subjects. It thus comes as no surprise that such a far-ranging expansion of the territorial scope of application of EU law is causing concern among controllers of personal data in third-party states. In particular, small and medium enterprises from such states may not be aware of the existence of EU rules on personal data protection, nor of the fact that they are obliged to follow them. Article 3(2) GDPR, which introduces the previously mentioned jurisdiction based on “targeting”, is intended to protect data subjects in the EU irrespective of the location of the controller or processor of the personal data (id est the entity which has been entrusted with the processing of personal data) and the location of the technical means employed in that processing. This approach is clearly different from that employed by e.g. Directive 2000/31/EC of the European Parliament and of the Council of 8 June 2000 on certain legal aspects of information society services, in particular electronic commerce, in the Internal Market ('Directive on electronic commerce'), which uses the principle of the state of origin, as the location of the data processor or controller is irrelevant to “targeting”. The provisions of Art. 3(2) GDPR should be interpreted in connection with the content of Recitals 23 and 24 of the preamble. Recital 24 clearly indicates that in the case of “monitoring behaviour” referred to in Art. 3(2)(b), the European legislator was concerned with observation and profiling, id est activities which are universal on the internet. This observation is done using such means as cookies, which are files saved on the computes of users visiting particular webpages. Profiling is a practice of social media portals, internet shops, and also search engines, the vast majority of which (including the largest) have their seat outside the EU. It is slightly more difficult to understand the intentions of the European legislator as concerns Art. 3(2)(a) and the offering of goods and services. Recital 23 of the preamble to GDPR indicates such factors as “ the use of a language or a currency generally used in one or more Member States with the possibility of ordering goods and services in that other language, or the mentioning of customers or users who are in the Union, may make it apparent that the controller envisages offering goods or services to data subjects in the Union.” This is, however, only a partial list. In the future it will be possible to interpret this provision even more broadly. Presently, the reference in Art. 3(2)(a) to the irrelevance of payment stems from the fact that many services in the internet, such as e-mail, social media accounts, some games, and activities based on Web 2.0 are offered on a free basis. The Union legislator thus desired to clearly indicate that these services as well would be encompassed by the scope of the new regulation. It should be emphasized that Art. 3(2) GDPR establishes an exceptionally broad territorial scope for the application of the Regulation. Particularly with regard to online activities, many of them, regardless of who is engaged in them, could potentially be encompassed by the territorial scope of application of EU provisions. At the same time, this approach seems largely justified in times where a single individual with a portable computer can process millions of records of personal data. It should, however, be given special attention, and with all certainty should be analysed during the nearest evaluation referred to in Art. 97. The determination of whether we may speak in a given case of targeting can in practice give rise to doubts. On the one hand, invoking case-law and scholarly writings to assist in grasping the question of liability on the internet, it should be said that, when referring to targeting, the mere potential accessibility in a given state of information uploaded to a publicly accessible portal is an insufficient criterion. This is confirmed in Recital 24 in the preamble to GDPR, pursuant to which the determination of whether a controller or processor is offering goods or services to people located in the Union and whom that data concerns, the mere accessibility within the Union of the webpage of the controller, processor, intermediary, email address, or other contact data, nor the use of a language generally spoken in the third-party state in which the controller has an undertaking, is insufficient. On the other hand, if the addressing of an offer to citizens of an EU state is clear owing to the selection of language in which an order may be placed or a list of states in which the client may reside, the processing of data is governed by GDPR.
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Article 3(3) GDPR In accordance with its wording, the Regulation is applicable to the processing of personal data by a controller without an undertaking in the Union, but which has an undertaking in a place where it results from application of the provisions of public international law the law of a Member State is applicable. Public international law may be defined as a group of norms regulating the legal relations among states, among states and other entities active in the international arena, and among those entities with the capacity to act in international relations. These other entities are primarily international organizations. Public international law is among those public laws whose domain is the admission of the priority of the state in relations with persons. The primary source of public international law is the international agreement, but also international custom, the case-law of international courts, scholarship, the legislation of states, unilateral acts (notification, protect, recognition, renunciation), the resolutions of international organizations, and general principles of international law. We should also recall situations in which GDPR is applied pursuant to conflict of laws provisions in private international law, which is not, however, encompassed by the scope of Art. 3(3). Conclusions The General Data Protection Regulation introduces a range of changes to EU law. One of them, important not only for the European but also the global personal data protection system, is the European legislator’s departure from the scope of application of EU rules based exclusively on the criterion of territory. The new model, while still retaining references to territory, is based on a mechanism that can be referred to as “targeting” and is intended to ensure effective protection of personal data in the information society. These changes should doubtlessly be judged positively. However, the key issue that comes to the fore in conjunction with the territorial scope of GDPR application is the real possibility for European bodies to enforce decisions issued against entities from outside the EU. References BARTA, P., LITWIŃSKI, P., KAWECKI, M. 2018. Komentarz do art. 3 (Commentary to Article 3 GDPR)(in:) Litwiński, P. (ed.), Barta, P., Kawecki, M., Rozporządzenie UE w sprawie ochrony osób fizycznych w związku z przetwarzaniem danych osobowych i swobodnym przepływem takich danych. Komentarz (EU regulation on the protection of individuals with regard to the processing of personal data and the free movement of such data. Commentary), Warsaw, p. 151-160. CLOUD COMPUTING. STUDY, 2012. Online access: http://www.europarl.europa.eu/RegData/etudes/ etudes/join/2012/475104/IPOL-IMCO_ET(2012)475104_EN.pdf, p. 8. CZERNIAWSKI, M. 2015. Aktualny i projektowany zakres terytorialny unijnych przepisów o ochronie danych osobowych (The current and planned territorial scope of the EU provisions on the protection of personal data), Europejski Przegląd Sądowy, 5: 4-9. CZERNIAWSKI, M. 2016a. Rozdział 4. Zakres terytorialny stosowania polskich i unijnych przepisów o ochronie danych osobowych w kontekście najnowszego orzecznictwa Trybunału Sprawiedliwości Unii Europejskiej (Chapter 4. Territorial scope of application of Polish and EU provisions on the protection of personal data in the context of the latest case law of the Court of Justice of the European Union) (in:) Bielak-Jomaa, E. (ed.), Lubasz, D. (ed.), Polska i europejska reforma ochrony danych osobowych (Polish and European reform of personal data protection), Warsaw. CZERNIAWSKI, M. 2016b. Zakres terytorialny a pojęcie "jednostki organizacyjnej" w przepisach ogólnego rozporządzenia o ochronie danych – zarys problemu (Territorial scope and the notion of an "establishment" in the provisions of the General Data Protection Regulation - outline of the problem) (supplemental to Monitor Prawniczy, 20), Monitor Prawniczy, 20: 22-28. CZERNIAWSKI, M. 2018. Komentarz do art. 3 (Commentary to Article 3) (in:) Bielak-Jomaa, E. (ed.), Lubasz, D. (ed.), RODO. Ogólne rozporządzenie o ochronie danych. Komentarz (General Data Protection Regulation. Commentary), Warsaw. EUROPEAN DATA MARKET SMART 2013/0063, Final Report of 1.01.2017, 2017. Online access: http://datalandscape.eu/study-reports/european-data-market-study-final-report. KAMIŃSKI, I.C., WARSO, Z. 2014. Czy można zniknąć z Google’a? Orzeczenie Trybunału Sprawiedliwości Unii Europejskiej w sprawie Google Spain SL i Google Inc. przeciwko Agencia Española de Protección de Datos (AEPD) i Mario Costeja González (C-131/12) (Can you disappear from Google? Judgment of the Court of Justice of the European Union regarding Google Spain SL and Google Inc. against the Agencia Española de Protección de Datos (AEPD) and Mario Costeja González (C-131/12)) (in:) BychawskaSiniarska, D. (ed.), Głowacka, D. (ed.), Wirtualne media - realne problemy: materiały z konferencji zorganizowanej w dniu 15 kwietnia 2014 r. przez Obserwatorium Wolności Mediów w Polsce
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Helsińskiej Fundacji Praw Człowieka, Zakład Praw Człowieka Wydziału Politologii Uniwersytetu im. Marii Curie-Skłodowskiej w Lublinie i Zakład Praw Człowieka Wydziału Prawa i Administracji Uniwersytetu Warszawskiego (Virtual media - real problems: materials from the conference organized on 15 April 2014 by the Observatory of Freedom of Media in Poland The Helsinki Foundation for Human Rights, Department of Human Rights, Faculty of Political Science, University of Maria Curie-Skłodowska in Lublin and the Human Rights Department of the Faculty of Law and Administration of the University of Warsaw), Warsaw, p. 51–66. KLOC, K., GAWROŃSKI, M. 2018. Przedmiotowy i terytorialny zakres stosowania RODO (Material and territorial scope af application of GDPR) (in:) Gawroński, M. (ed.), RODO. Przewodnik ze wzorami (GDPR. Guide with patterns), Warsaw, p. 45-46. KOMENTARZ do art. 4 pkt 8 (Commentary to Article 4(8) GDPR), 2018 (in:) Bielak-Jomaa, E. (ed.), Lubasz, D. (ed.), RODO. Ogólne rozporządzenie o ochronie danych. Komentarz, (GDPR. General Data Protection Regulation. Commentary), Warsaw KOMENTARZ do art. 8 (Commentary to Article 8), 2013 (in:) Wróbel, A. (ed.), Karta Praw Podstawowych Unii Europejskiej. Komentarz (The Charter of Fundamental Rights of the European Union. Commentary), Warsaw LUBASZ, D., 2018, RODO. Zmiany w zakresie ochrony danych osobowych. Porównanie przepisów. Praktyczne uwagi (GDPR. Changes in the protection of personal data. Comparison of legal provisions. Practical notes), Warsaw, p. 19 SIBIGA, G. 2016. Dopuszczalny zakres polskich przepisów o ochronie danych osobowych po rozpoczęciu obowiązywania ogólnego rozporządzenia o ochronie danych – wybrane zagadnienia (Permissible scope of Polish provisions on the protection of personal data after the date of application of the General Data Protection Regulation - selected issues), supplemental to Monitor Prawniczy, 20. SZAFRAŃSKI, B. 2014. Realizacja zadań publicznych a Big data (Implementation of public tasks and Big data) (in:) G. Szpor (ed.), Publiczne bazy danych i Big data (Public databases and Big data), Warsaw. SZYMIELEWICZ, K. 2017. Śledzenie i profilowanie w sieci: w czym problem? Co się zmieni w prawie? Jak może wyglądać przyszłość? Raport Fundacji Panoptykon (Tracking and profiling on the web: what's the problem? What will change in the law? What can the future look like ? Report of the Panoptykon Foundation), Warsaw. Online access: https://panoptykon.org/sites/default/files/publikacje/ sledzenie_i_profilowanie_w_sieci_scenariusze_po_reformie_ue_wrzesien_2017.pdf. ŚWIERCZYŃSKI, M. 2017. Rozdział IV. Jurysdykcja krajowa w świetle ogólnego rozporządzenia o ochronie danych (Chapter IV. National jurisdiction in the light of the general Data Protection Regulation) (in:) Kawecki, M. (ed.), Osiej, T. (ed.), Ogólne rozporządzenie o ochronie danych osobowych. Wybrane zagadnienia (General Data Protection Regulation. Selected issues), Warsaw. THE EUROPEAN DATA MARKET MONITORING TOOL REPORT 20.04.2018, 2018. Online access: http://datalandscape.eu/sites/default/files/report/EDM_D2.2_First_Report_on_Policy_Conclusio ns_20.04.2018.pdf. WIEWIÓROWSKI, W. 2012. Nowe ramy ochrony danych osobowych w Unii Europejskiej (New framework for the protection of personal data in the European Union) (in:) Sibiga, G. (ed.), Aktualne problemy ochrony danych osobowych (Current problems of personal data protection), supplemental to Monitor Prawniczy, 7. WIRSKA, P. 2017. Rozdział V. Rozszerzenie zakresu stosowania unijnych przepisów na administratorów danych i podmioty przetwarzające z państw trzecich (Chapter V. Extending the scope of application of the EU provisions to data controllers and processors from third countries) (in:) Kawecki, M. (ed.), Osiej, T. (ed.), Ogólne rozporządzenie o ochronie danych osobowych. Wybrane zagadnienia (General Data Protection Regulation. Selected issues), Warsaw.
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APPLICATION OF UAV DATA IN CITYGML DEVELOPMENT Filip Kovačić, M.Sc.
GEO OMEGA d.o.o. Zagreb, Croatia e-mail:
[email protected] - contact person
Kristijan Krznarić, Eng. GEO OMEGA d.o.o. Zagreb, Croatia e-mail:
[email protected]
Petar Božičević, M.Sc.
GEO OMEGA d.o.o. Zagreb, Croatia e-mail:
[email protected] Abstract Aero photogrammetric images acquired with the unmanned aerial system senseFly eBee were used for point cloud creation of the inhabited part of the Silba Island. The automatic point cloud classification that relies on machine learning was processed in the Pix4D program. DSM, orthomosaic and CityGML were created from the classified point cloud. Apart from classified point cloud as a basis for buildings heights, topographic map created from high-resolution orthomosaic of the area was used as a basis for buildings boundaries. CityGML was created using 3dfier software for detail level 1 (LoD1), encompassing all external surfaces of objects. A unique identification, along with house number, floor area, height and volume attributes were assigned to the buildings. The realistic preview of the recorded area in 3D was achieved inside Pix4D Cloud platform. Information and analytical preview of objects was achieved by loading and stylizing CityGML inside QGIS 3.0. Information preview holds buildings outline with house numbers, while stylizing buildings according to the attributes of height, floor area, accomplished the analytical preview and volume attributes. The information preview of the objects provides insight into the basic attributes of buildings and along with the realistic and the analytical preview creates a base for complete modern 3D buildings inventory. Key words: 3D buildings, UAS, CityGML, DSM, point cloud Introduction The purpose of every model is to represent reality in as much as possible credible way. Modeling large-scale data like cities brings attention to model’s substantiality and heterogeneity. A key feature of every 3D city model is representation of georeferenced urban spatial data (DÖLLNER et al., 2006). Such georeferenced spatial data consists of terrain elevation, buildings, land use, vegetation and roads (IÑAKI et al., 2014), among others that are necessary to govern cities sustainably. After being used mainly for 3D visualization in last decades, 3D city models became matter of necessity for wide range of tasks like area population estimation, solar-radiation models, building models, visibility analysis, urban planning, and potential assessment (BILJECKI et al., 2015a). Croatian cadaster is in great rate originated in 19 th and 20th century (ROIĆ et al., 1999) which causes topological incompatibilities with reality, due to various datums and precisions of surveys. Condition of not implementing changes and their registration in cadaster during the second half of 20 th century (IVKOVIĆ, VLAŠIĆ, 2006) caused large number of unregistered objects and changes on registered ones, along with unregistered changes in position and shape of parcels. The result of this is unusable cadaster as topological basis for 3D objects creation, except 10% of cadastral municipalities generated in new surveys (KLEKOVIĆ et. al., 2014). Nowadays, the core data for 3D city models generation is point cloud generated from LIDAR of SAR (ZHU, SHAHZAD, 2014) data. Our exordial data for 3D buildings model in this work is also point cloud but generated from aerial images acquired with UAS. We decided to rely our 3D buildings model on aerial photogrammetry point cloud in order to enhance geospatial data registration rate and positional accuracy, and at the same time deploying model as rich as possible.
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Material and methods For showcasing 3D buildings generation we have chosen the Island of Silba located in the southern part of the northern Adriatic sea. The Island of Silba is almost 15 km2 large and has constant population of around 300 people. Populated part of Silba covers about 2 km 2 which holds 512 objects on the southern part, as we have mapped in this work, and even so much on the northern part as divided by the line connecting a eastern and western dock. Silba is one of 6761 Croatia’s settlements (BUDIMIR et al., 2015), thus settlements present considerable challenge to local governments and authorities in reconstruction and regular maintenance of building registries, in order to provide accurate assessments. As told in the introduction majority of cadastral municipalities’ data is not accurate enough to be paired with up to date technologies or outdated with missing key data for 3D buildings development. Cadastral municipality of Silba is also one of these municipalities unusable as topological basis for 3D buildings creation. Inaccurate and missing buildings data is shown on Croatian official orthophoto from year 2011 in Fig. 1.
Fig. 1. Part of Cadastral municipality of Silba on Geoportal. Source: (http://geoportal.dgu.hr/#/).
For creating input data used for modern buildings registry which can also be used for cadastral parcels enhancement and GIS development we have chosen aerial photogrammetry method with data acquired with unmanned aerial system (UAV). We have set up geodetic basis of 12 ground control points (GCPs) and 14 control points (CPs) all over the populated part of the island for purpose of aerial photogrammetry. GCPs were used for referencing the model and CPs were used for accuracy control of the model. Geodetic basis was set up with Global Navigation Satellite System (GNSS) Real-time Kinematics (RTK) and very precise positioning service (VPPS) on network of GNSS reference stations - Croatian Positional System (CROPOS). Survey has been proceeded in HTRS96/TM datum. We have used senseFly eBee UAV for aerial images acquisition. We have acquired images with 80% lateral overlap and 75% longitudinal overlap at approximate 148 m altitude. Images acquisition was proceeded in 4 UAV flights and total of 1140 georeferenced images was acquired. Images were processed both in Pix4Dmapper desktop and in Pix4D cloud. Main desktop outputs are automatically classified point cloud in LAS format, which is relied on machine learning in processing progress (BECKER et al., 2017). Machine learning algorithms consider both geometry and color information from point cloud. Automatically classified point cloud was used for digital terrain model (DTM) generation, considering only points classified as ground and road surfaces. Cloud processing provided the same outputs as desktop processing and enables online preview of orthomosaic and digital surface model (DSM) in 2D georeferenced on satellite base map. Average ground sampling distance (GSD) of outputs is 4.03 cm, except DTM with five times smoother GSD of 20 cm. Georeferencing the model in processing equaled mean RMS error of 0,015 m in all three dimensions. Georeferencing details for GCPs is shown in Table 1 and for CPs in Table 2. Table 1 shows very accurate model georeferencing in absolute aspect according to GCPs surveyed in Croatian official datum (HTRS96/TM) with nominal accuracy of 0.02m horizontally and 0.03m vertically for VPPS. Table 2 shows very accurate model georeferencing in aspect relative to GCPs. 295
Table1. GCPs georeferencing details. GCP Name
Error X [m]
Error Y [m]
Error Z [m]
Projection Error [pixel]
gcp1
-0.018
0.046
-0.007
0.443
gcp3
-0.009
0.000
0.016
0.546
gcp5
-0.006
0.002
0.013
0.409
gcp7
0.005
0.020
-0.030
0.589
gcp10
0.026
-0.003
-0.003
0.493
gcp13
0.001
0.002
-0.002
0.444
gcp16
0.019
-0.024
0.022
0.720
gcp18
-0.007
-0.017
0.017
0.442
gcp20
0.004
-0.005
0.000
0.421
Source: Own study based on own data. Table 2. CPs georeferencing details. Check Point Name
Error X [m]
Error Y [m]
Error Z [m]
Projection Error [pixel]
gcp2
-0.010
0.013
0.035
0.426
gcp4
-0.051
0.020
0.230
0.894
gcp6
-0.007
-0.019
0.098
0.642
gcp8
0.036
-0.008
-0.144
0.601
gcp9
-0.019
0.022
0.048
0.293
gcp11
-0.010
-0.029
-0.092
0.425
gcp12
0.038
-0.021
0.165
0.336
gcp14
0.029
0.027
0.095
0.628
gcp15
0.016
0.032
-0.170
0.358
gcp17
-0.054
-0.003
0.035
1.127
gcp19
-0.069
0.001
-0.112
1.189
gcp22
-0.060
-0.012
0.031
0.684
gcp24
-0.038
-0.010
0.002
0.647
gcp26
-0.043
0.070
0.287
0.544
Source: Own study based on own data.
After generation of centimeter precision orthomosaic, which can be used for cadaster enhancement, we have used it as a basis for buildings topography layer. Topography layer was created in Spatial lite format containing a basic buildings features as house number and building type. Buildings topography included all outer buildings borders along with all their constructive parts like outer stairways, balconies and terraces on floors. Buildings with such defined topography can be used for CityGML generation of Level of detail (LOD) 1.2 or higher as shown in Fig. 2.
Fig. 2. Refined series of 16 LODs. Source: (BILJECKI et al., 2016).
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After completing the building topography main inputs for CityGML were ready. CityGML LOD1 generation was proceeded in 3dfier, an open-source software (source: https://github.com/tudelft3d/3dfier). 3dfier uses 2D topography data, in our case only the buildings, and point cloud data in LAS format, in our case an aerial photogrammetry point cloud. While defining CityGML lifting options in 3dfier we have set up percentiles for buildings height and roof read from the LAS files. 90th percentile of all point heights in buildings footprint was used for the roofs in LOD1, thus filtering outliers and roof features like chimneys. 10th percentile of all point heights in buildings footprint was used for floor height. For input elevation options we have set up omitting point cloud (LAS) classes 1, 3, 4 and 5, representing respectively unclassified, low vegetation, medium vegetation and high vegetation points according to ASPRS Standard LIDAR Point Classes (ASPRS, 2011). Omitting unclassified and vegetation points from classified point cloud prevented false roof and floor height definition in LOD1 generation. 3D buildings were generated in CityGML and OBJ format (Fig. 3).
Fig. 3. CityGML 3D preview in QGIS 3.0. Source: Own work.
Results and discussion Pix4D cloud processing enabled basic 2D preview of orthomosaic and DSM on the base map, thus placing project area on world’s map. Except the 2D preview, Pix4D cloud provides 3D preview for 3D model (mesh model) and point cloud with project coordinates, although not placing them on the globe. Both previews are available on URL1. CityGML provided main buildings data as floor and roof height, which conceal absolute and relative building heights, and buildings area as defined in buildings topology. Both area and relative height include outward buildings volume into attribute data. Fig. 4 shows buildings heights emphasizing lowest buildings, which are actually bedrocks for future buildings with heights of 0,98 m and taller, and highest building, local church with height 15,20 m.
Fig. 4. CityGML heights. Source: Own work.
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Comparing relative heights with point cloud data, difference of 20 cm has been measured on the highest building. This indicated good trail for analyzing relative heights data but also involved oversized volume data, as expected in the simplified LOD1 data. Area, 2D buildings data created digitizing aerial photogrammetry orthomosaic can be used for enhancing and reconstructing cadaster data (Fig. 5).
Fig. 5. CityGML area. Source: Own work.
Enhancing cadaster data in the dimension aspect is the core value of CityGML as volume (height) data significantly enriches building information inside the Registry. Volumes calculated using area and relative height data is shown in Fig. 6.
Fig. 6. CityGML volumes. Source: Own work.
CityGML holds attributes form the spatial units Registry, in this case only house numbers, but normally it holds and streets nomenclature. CityGML should also be enriched with basic buildings attributes from cadaster, indicating building type. We have used only two basic building types, residential buildings and auxiliary buildings. Separating buildings by type enables analyzing their use in the target area and which helps in future urban planning and regulation definitions. Buildings should be enriched with as many attributes as possible, thus compellingly heading towards a multipurpose land administration system (MLAS) (ROIĆ et al., 2017).
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Multipurpose of land administration is highly contained in 3D buildings data, as it’s briefly shown in Fig. 4 and Fig. 6. Previewing both of them together, i.e. in 3D, gives us insight into building trend in this area and helps creating assessments in future resources needs. Analyzing Fig. 6 we get to conclusion that building with highest volume is sacral building, and other building gravitate around 2000 m3 as their main use is for tourists’ accommodation. Analyzing the absolute building heights can result in enactment of zones or areas with maximum buildings height, in order to preserve sea view in objects further from the sea. Similar analyses exists in building shadows analyses, visibility analyses (BILJECKI et al., 2015a) and solar irradiation analyses (BILJECKI et al., 2015b). Conclusions Today's cadaster in Republic of Croatia still falls behind modern 3D cadasters, while still in great need for enhancement and registration of 2D data. On the other hand growing abilities of modern surveying technologies and software advancement gives great deal of time saving and accurate methods for not only quality but also structure uplift providing 3D data for high-end interference. Aligning on growing UAV industry, which we use in surveying more with every day, we have created inputs accurate and rich enough to recreate 2D and create 3D buildings using 3dfier. Richness is mainly contained in point cloud classified in machine learning algorithm. Creating LOD1.3 CityGML gave fast solution for 3dfieing Croatia’s large number of settlements that do not require grater details than contained in stated LOD. On the other hand cities with large number of buildings and growing population surely need 3D buildings in LOD2 or higher. Once 3dfied buildings provide insights and possibilities like shadow analyses, solar irradiation analyses and visibility analyses. Last two could find great application in Adriatic region. Solar irradiation analyses can provide insight in possibilities of solar panel implementation and thus improve competitiveness in tourism sector, while visibility analyses can provide enactment of maximum buildings height zones in order to preserve sea view line of sight in desired locations. References THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY & REMOTE SENSING 2011. LAS specification version 1.4 – R6. USA, 2011. BECKER, C., HÄNI, N., ROSINSKAYA, E., D’ANGELO, E., STRECHA, C. 2017. Classification of aerial photogrammetric 3D point clouds. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-1/W1. ISPRS Hannover Workshop: HRIGI 17 – CMRT 17 – ISA 17 – EuroCOW 17, 6–9 June 2017, Hannover, Germany. BILJECKI, F., LEDOUX, H., STOTER, L. 2016. An improved LOD specification for 3D building models. Computers, Environment and Urban Systems, Vol. 59, p. 25-37. BILJECKI, F., STOTER, J., LEDOUX, H., ZLATANOVA, S., ÇÖLTEKIN, A. 2015a. Applications of 3D City Models: State of the Art Review. ISPRS International Journal of Geo-Information, 4: 2842–2889. BILJECKI, F., HEUVELINK, G. B. M., LEDOUX, H., STOTER, J. 2015b. Propagation of positional error in 3D GIS: estimation of the solar irradiation of building roofs. International Journal of Geographical Information Science, 29(12): 2269-2294. BUDIMIR, I., GRGIĆ, I., ŠUSTIĆ, A. 2015. Evidencija naselja i katastarskih općina u Registru prostornih jedinica (Record of Settlement and Cadastral Districts in the Register of Territorial Units). Geodetski list 2015, 3:207-220. DÖLLNER, J., KOLBE, T., H., LIECKE, F., SGOUROS, T., TEICHMANN, K. 2006. The virtual 3D city model of Berlin managing, integrating and communicating complex urban information. 25th International Symposium on Urban Data Management UDMS. IÑAKI, P., IZKARA, J. L., DELGADO, F. J. 2014. From point cloud to web 3D through CityGML. Proceedings of the 18th International Conference on Virtual Systems and Multimedia, VSMM 2012: Virtual Systems in the Information Society. https://www.researchgate.net/publication/235635196_From_ point_cloud_to_web_3D_through_CityGML (access 25.04.2018). IVKOVIĆ, M., VLAŠIĆ, I. 2006. Usporedba površina katastarskih čestica stare i nove izmjere (Comparison of Cadastral Parcel Areas in the Old and New Surveys). Geodetski list, 4: 285-294. KLEKOVIĆ, B., LIPOVŠČAK, G., PAJ, R., SMOLJAN., Z. 2014. Poboljšanje modela katastarskih izmjera (Improvement of cadastral survey models). Croatian Chamber of Charted Geodesy Engineers, Zagreb. ROIĆ, M., VRANIĆ, S., KLIMENT, T., STANČIĆ, B., TOMIĆ, H. 2017. Development of Multipurpose Land Administration Warehouse. FIG Working Week 2017, Surveying the world of tomorrow – From digitalization to augmented reality, Helsinki, Finland, May 29 – June 2, 2017. ROIĆ, M., FANTON, I., MEDIĆ, V. 1999. Katastar zemljišta i zemljišno knjižni registry (Land Cadaster and Land Registry). Zagreb.
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ZHU, X., X., SHAHZAD, M. 2014. Facade Reconstruction Using Multiview Spaceborne TomoSAR Point Clouds, IEEE Transactions on Geoscience and Remote Sensing, 52(6): 3541-3552. URL 1: https://cloud.pix4d.com/pro/project/280470/map?shareToken=b1ab314b22384b0aa6d38f38b 970c7b2 (access 25.04.2018).
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DEVELOPMENT AND ANALYSIS OF A COMMUNICATION NETWORK SYSTEM MODEL FOR FIRE SERVICE OPERATIONS Anna Maria Kowalczyk, Ph.D. Institute of Geoinformation and Cartography Faculty of Geodesy, Geospatial and Civil Engineering University of Warmia and Mazury in Olsztyn Olsztyn, Poland e-mail:
[email protected] Abstract Models are built for the purpose of analysis and making optimal decisions in all aspects of life. Network models represent a very large group of systems occurring in space. Creating network models, their analysis and identification in terms of construction and character allows for optimization of activities related to the analysed system and issues. The communication system can be presented as a network model. It is part of important spatial structures and plays a very important role in the vitality of these structures, such as cities and villages, as well as in people's everyday lives and their safety. In this aspect, it is an important part of critical infrastructure. The communication system is a necessary element for ensuring proper operations of Fire Brigade groups. His analysis carried out by building a network model and defining its character, allows undertaking actions related to the improvement of the Fire Brigade's accesses to events. The research which has been done on the tested area are a proposal of a complete network analysis method of the communication system for the Fire Brigade actions. Key words: network model, safety, GIS, spatial analysis Introduction Communication systems are among the most important spatial structures shaping daily human life. Enabling free and organised movement of people, they constitute an important element of the safety system as part of critical infrastructure (KOWALCZYK, 2013). One of the functions of roads, walkways, wheeled and pedestrian traffic routes of all kinds is to facilitate effective (i.e. efficient and safe) movement of persons, property and rescue units in the event of danger, in the shortest time possible. The Fire Service, being the organised formation responsible for prevention of and response to all sorts of threats (except crime), in order to protect human life and health, property, and the environment, requires effective communication structures. Their effectiveness should be the result of not only good repair, but also distribution – location and capacity ensuring accessibility. Communication structures should allow the Fire Service to reach the site of an incident not only when the entire system is functional, but also when some of its elements have been disabled. Network modelling and geospatial data analysis (BAJEROWSKI, KOWALCZYK, 2013) are necessary for understanding the relations between various elements of a communication system and safety operations in the purview of the Fire Service. The Network Model One could say that modelling is the essence of science (CIEŚLIŃSKI, 2002). Half the battle for one’s research is choosing the right model, which will correctly describe the fragment of reality one is investigating, irrespective of whether the model is verbal, graphic or mathematical (BAJEROWSKI, KOWALCZYK, 2013; CIEŚLAK et al., 2016; RENIGIER-BIŁOZOR, BIŁOZOR, 2015; BIŁOZOR, RENIGIER-BIŁOZOR, 2016; OGRODNICZAK et al., 2017a; OGRODNICZAK et al., 2017b; OGRODNICZAK, RYBA, 2017). The concept of a model is ubiquitous in the literature. Its two primary meanings are presented in CHOJNICKI (1966). The first meaning of the word model provided by Chojnicki is that of a good example, worthy of emulating. In the second meaning, the word signifies a simplified, approximate version of another thing or structure. Models can be used to schematically represent individual objects or whole classes of objects. The model does not represent the original entirely but is only capable of representing some of its properties – especially those which make imagining the entire original easier (CHOJNICKI, 1966). The classical model theory has a slightly different view of this concept. It rests on structural similarity, or isomorphism, between the modelled thing and its representation. The relations between those structures are reduced to a one-to-one correspondence (bijection) between them. In keeping with
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the classical concept, BAJEROWSKI (2003), following CHOJNICKI (1966), distinguishes two fundamental models. In the stricter sense, model E and model Ē, and in the generalised sense: • Template model E(w) and Ē(w), • Representation model E(o) and Ē(o). In the first case, object P is the template model E(w) of an object or class of objects P’ if and only if person O maps object P’ or class of objects P’ to object P in such a way that structure S’ or part of structure S’ of object P’ is isomorphic to structure S of object P (BAJEROWSKI, 2003). In the second case, object P is the representation model E(o) of an object or class of objects P’ if and only if person O maps object P to object P’ in such a way that structure S of object P is isomorphic to structure S’ of object or class of objects P’ (BAJEROWSKI, 2003). A network model can be defined as a structure composed of nodes and connections between those nodes. Connections may be physical (e.g. crossroads connected by roads) or they may represent relationships (e.g. people connected by literature citations). Networks may have different structures and characters. Mapping structures existing in the real world onto network models lets one gain information and knowledge on their forms, and consequently – their properties. Geospatial data analysis makes a very important distinction between random networks and scale-free networks. Apart from common elements, i.e. nodes and connections, they are significantly different from each other, as shown in Table 1. Table 1. General characteristics of random networks and scale-free networks. Random networks The random network structure has roughly the same number of connections to nodes, and the distribution in such a network is represented by the characteristic Poisson distribution curve.
Scale-free networks The structure of scale-free networks is characterized by different number of connections to nodes, and the distribution of this network is represented by the power function.
No centers (hubs) - nodes that have more connections than the average number of connections to nodes.
Occurrence of centers (hubs - red spot) - nodes with more connections than most nodes of the entire network structure.
There is no preferential connection selection in a particular hierarchy.
There is a preferential selection of connections in a given hierarchy - when a new node appears, it tends to bind to nodes with a high number of bindings, and this favorable feature makes the nodes more and more interconnected in opposition to their neighboring nodes with fewer connections. Resilience to random attacks - An accidental attack on a node does not have such a devastating impact on scale-free network as it has on random network Thanks to the heterogeneous structure, there are always connections that continue to hold the entire network in active state.
Random cutoff (sometimes referred to as an attack on a node or nodes), that is, the permanent or temporary destruction of a given number of nodes, leads to break down of the whole network structure into smaller, separately functioning networks. The structure can be severely damaged.
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No centers in the network structure.
Huge sensitivity to the deliberate exclusion of centers from the network structure - these networks are very sensitive to attacks organized intentionally at a given point - the network center. Intentional attack on several centers can lead to complete network disruption and structural disfunction.
Rarely appearing in real world.
They characterize many spatial structures and are universal in usage.
Source: (BEDNARCZYK et al., 2018; KOWALCZYK, 2015; KOWALCZYK, 2017; BARABASI et al., 2000; BARABASI, 2003; BARABASI, 2005; BARRAT et al., 2004; BIŁOZOR, SZUNIEWICZ, 2008; KOCUR-BERA, 2014).
Therefore, deciding whether the network in question is random or scale-free is crucial since it lays a scientific foundation for the optimisation of activities and decision-making. A network identified as scale-free must have hubs in its structure. This information may be vital when it comes to the structure’s proper functioning or preventing its failure. For more information on random and scale-free networks, see: BEDNARCZYK et al., 2018; KOWALCZYK, 2015; KOWALCZYK, 2017; BARABASI et al., 2000; BARABASI, 2003; BARABASI, 2005; BARRAT et al., 2004; BIŁOZOR, SZUNIEWICZ, 2008; KOCUR-BERA, 2014. For the purpose of this analysis, it should be assumed that a communication system’s network model is an approximate version of its structure, exhibiting only those characteristics which are necessary for geospatial data analysis for Fire Service operations. The model schematically represents certain individual elements of the communication system: intersections as nodes and roads as connections. These generate the model’s network structure and can, in such form, undergo full analysis and modifications simulating the structure’s specific behaviors. The nodes and connections of the network, besides existing and representing physical connections, can endow the network structure with parameters expressing, for instance, the number of passing cars (in the case of nodes) or the flow direction (in the case of connections).
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A number of useful model definitions relating directly to communication structures or systems has been presented by DOMAŃSKI (1963). The anisotropic model and models leading to its development are especially noteworthy. Among these are: • the travelling salesman model – having the simple requirement to find the shortest route from a given residential area of type p through all n residential areas of that type in a region, this model, however, requires defining a hierarchy of routes in the network, starting with the layout of main routes, through the secondary, tertiary and miscellaneous. A shortcoming of this model is an insufficient cohesion of routes (DOMAŃSKI, 1963). One of the solutions to the travelling salesman problem is the Hamiltonian cycle (BIAŁYNICKI-BIRULA et al., 2014). It is a closed path through a graph which visits each vertex of the graph only once (except for the first vertex, being at once the beginning and the end of the cycle). Finding a Hamiltonian path remains an open question since there are methods for finding near-optimal solutions, but none that are conclusive. This method can be effectively employed mainly with a small number of vertices, since as the number of potential solutions grows, it becomes more problematic to check all the solutions and select the path which is, in fact, the shortest. • the telephone exchange model – derived from construction of telephone networks, this model defines the location of a network’s central office so that ‘its connection with street cabinets, which gather lines from individual telephones, requires the least length of copper wire’ (DOMAŃSKI, 1963). The central point Q of such a network is defined by: (1) where ci is a positive number proportional to the cost of a unit length of wire connecting the exchange Q with the street cabinet Pi, and ri is the length of wire QPi’ (DOMAŃSKI, 1963).
•
The advantage of this model is having variables proportional to the cost of a unit of length of the path. Its disadvantages are: the incompleteness of the layout, disregard of the regional hub already present, and disregard of factors other than the minimisation of economical distances in defining the hub location. This model is best employed analysing small local areas, especially those with new investments in which the location of the hub is discretionary (DOMAŃSKI, 1963). the centralised network model – stemming from a number of assumptions, this model defines the optimal shape of a road network in order to minimise the cost of communication. It begins with a given area with a defined border and a center towards which all traffic is directed. Also given is the number of roads m, and their endpoints – R, which are located at the area’s border. Furthermore, access roads must be parallel to each other. The solution is arrived at with calculus of variations. For more information on the centralised network model, see: Zespoły sieci komunikacyjnych (DOMAŃSKI, 1963).
The analysis of these three models and their shortcomings has revealed the need for a different model describing a communication network – the anisotropic model. According to DOMAŃSKI (1963) it is a function of the hierarchy, relative positioning, and dimensions of roads of various kinds constituting a system. (2) where: Mz – construction of a communication system network, φ – relative positioning of roads, β – dimensions of roads in the system, γ – hierarchy of roads. One of the assumptions of this model is that it would generate lower cost than road systems constructed based on more traditional models of communication networks. It rests on the following principles of operation: • the flow of traffic on a main (primary) road is greater than on a side (secondary) road, • the relative angle of roads should not exceed 180 degrees, • the number of main roads should be less than the number of side roads, in a node the number of main roads should be less or equal to the number of side roads,
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•
the cost of main road construction is greater than the cost of side road construction, the cost of movement of mass on main roads is lower than on side roads, and total unit cost of main communication is lower than that of side communication, • the ratio of total unit cost of main communication to total unit cost of side communication is constant, • if the unit cost of intermodal transport is lower than the cost of direct transport on a side road, the side and main road are complementary, whereas if the unit cost of intermodal transport is higher than direct transport on a side road – the side road substitutes the main road, • access traffic (short range) and direct traffic (middle and long range) on side roads are equal, • cargo density in an intermediate area, serviced by side roads, which is located between two main roads, is less than the cargo density in the area adjacent to the main road. DOMAŃSKI (1963) bases his model on the concept of anisotropy since he has proven that the main properties of roads are anisotropic, i.e. dependent on direction. He distinguishes between the directions of main roads and side roads serviced by different kinds of communication. Fig. 1 shows a layout of roads in an anisotropic model. In a communication system relying on main and side roads, access roads are perpendicular to the main road, whereas in direct communication, aiming for the shortest connections, the regular grid of side roads is flattened towards the main road.
Fig. 1. A theoretical anisotropic layout. Source: (DOMAŃSKI, 1963)
Fig. 2 shows the entire anisotropic model. The influence of deforming factors noticeably weakens with the distance from the main road, which results in a tendency for a square or equilateral triangular layout. However, some places show irregularities, resulting from the continuity of roads which must be connected to the main road (DOMAŃSKI, 1963).
Fig. 2. Anisotropic model of a system of communication networks. Key: 1 – 1st class nodes; 2 – 2nd class nodes; 3 – 3rd class nodes; 4 – 4th class nodes; 5- rivers; 6 – railroads; 7 – roads. Source: (DOMAŃSKI, 1963).
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Domański’s analysis (1963) shows that the shape of a communication network depends on two distinct tendencies: • The tendency of each node (residential area, intersection) to connect with other nodes. A geometric representation of this behaviour would be the set of straight lines connecting all nodes to each other • The tendency to merge many directions into one, with the assumption that traffic can only use roads technically intended for it. “Advantageous” directions attract more traffic and thus the hierarchy of main and access roads is formed. Building a communication network model A network model of a communication system has been created for a typically urban test area. It has comprised a residential area with semi-detached housing of two or more residences, as well as apartment buildings of up to seven storeys. The communication system model reflects the existing road network for wheeled transport (Fig. 3).
Fig. 3. Research area – part of Olsztyn, Poland. Warmińsko-Mazurskie Voivodeship. Source: Own analysis.
Construction of the model began with data collection and standardisation for the purpose of creating a database. Inventory has been taken in the field. This form of data gathering is especially useful for information about mobile spatial elements, e.g. parked cars and other objects that can change their location. The next step was the development of a vector network model of the communication system. An open-source software suite QGis 3.0 was used for this purpose. Two models, A and B, were developed as a result. Model A (Fig. 4) shows the communication system network with nodes representing intersections and connections representing physical connections within the space of the test area.
Fig. 4. Model A - the network model of the communication system. Nodes – crossroads. Connections – physical connections between nodes. Source: Own analysis.
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Model B (Fig. 5) shows the same structure but includes other features and relationships relevant for the analysis. These include: directions of traffic (one-way and two-way roads), access gates to fenced areas, speed bumps, road capacities and mobile features (parked cars preventing the passage of a fire engine). Traffic direction is generally irrelevant for rescue units, but civilian inhabitants, even under special circumstances such as evacuation, will follow normal traffic rules.
Fig. 5. Model B - the network model of the communication system with additional features. Source: Own analysis.
Geospatial Data Analysis of the Network Model of a Communication System Digital cartographic modelling methods allow for the inclusion of additional information in the form of thematic layers, e.g. about roads on which pavements and part of the road are filled with parked cars. This is a common impediment to reaching the site of the incident quickly. Analysis of model A revealed 79 nodes, including: 70 3-way intersections, and 9 4-way intersections. No 5, 6, 7, or 8-way intersections have not been identified. Tab. 1. Inventory of intersection types and their numbers. The total of all intersections of all types Intersection type Number of intersections
0
3
4
5
6
7
8
7
9
0
0
0
0
79
Source: Own analysis.
A network of this kind (model A), where nodes represent intersections and connections are roads for vehicular traffic (with no specified direction), can be characterised as random. The distribution of nodes and connections has a single maximum. The network structure has no apparent hubs, i.e. nodes with an exceptionally high number of connections. Under the criteria of model A construction, no vital points whose disabling could seriously impair the whole system can be identified within the network. But are the nodes of the network indeed equivalent and all connections representative of the same type of road? Analysis of model B, including additional characteristics and relations such as traffic directions, speed bumps and mobile features (parked cars), reveals other attributes of the network. Analysing model B, it is apparent that it possesses features resembling an anisotropic model. The foremost of these is the road hierarchy. Fig. 5 shows the main roads and side roads connected to them. Traffic flow on main roads is greater than on side roads. Another feature also exhibited by the discussed model is the smaller number of main roads as compared to side roads. One can observe that in the
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network model of the communication system, access roads are perpendicular to main roads. The anisotropic model typically exhibits two kinds of road layouts: triangular and rectangular. The developed model also exhibits these kinds of structures. In some parts of the structure one can also observe the typical flattening of the road layout. Some of the roads do not connect at right angle but converge in a single point. Layout flattening is meant to shorten the travel time between two points. Models A and B developed for this analysis constitute two networks (Fig. 4 and 5) with the same number of nodes N. One of the differences between these networks is the character of their connections. Model A presents a network in which connections between the nodes have no defined direction. In the other model, connections are defined either for one or two directions. Thus, the number of connections (or edges) E is different for the two models, as is the node degree distribution P(k). Degree distribution describes the number of nodes with a given number of connections within a network (KOWALCZYK, 2017). Model B presents a network in which one can distinguish hub nodes strategic for the operations of the Fire Service. The disabling of those hubs will greatly impede the functioning of the whole network and, in consequence, delay the arrival of Fire Service to the site of the incident. The nodes in question are marked in the figure with Roman numerals I through X. Although these nodes physically have only 3 or 4 connections, in fact they can be said to have many more since they funnel traffic from other streets and thus form additional connections. Knowing this enables planning rescue operations in the event of any of these nodes being disabled. It provides the basis for constructing nodes and connections which will increase the robustness of the communication system network as a whole. An example of such an alteration to the model is shown in Fig. 6. Adding new connections and creating new main nodes increases the resilience of the communication system in the event of other nodes being damaged (in this case I, II, and V especially). New connections enable alternative routes.
Fig. 6. Network model with new connections and main nodes. Source: Own analysis.
Conclusions The purpose of this study was to develop a network analysis method of a communication system for Fire Service operations. This objective has been achieved through particular goals including: • accumulation and standardisation of data concerning the number of road connections and the number of intersection nodes in the network model, types of roads, traffic volumes, • development of the communication system’s network model, using cartographic modeling, • model analysis, using random and scale-free model theory, • forming conclusions. This method of geospatial data analysis enables to optimise Fire Service operations and is a useful tool for increasing safety, e.g. in developing evacuation plans, analysing communication system resilience to node or connection failure, and designing new elements of a communication network. Network modelling and geospatial data analysis allows for a better understanding of the relationships existing between communication systems and safety measures. It proves useful in
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identifying strategic network elements in a given structure. This enables the implementation of preventive measures, such as ensuring smooth traffic flow or protecting nodes from damage (e.g. by introducing traffic control signals or collision-free intersections allowing for one traffic direction at a time). This minimises the chance of vehicle collisions or accidents, which would impede traffic flow. These measures will allow prompt arrival of rescue units at the incident site. The geospatial data analysis presented above shows the importance of properly defining the model. Relying solely on an analysis of scale-free structures based on intersection types may lead to erroneous results, showing only random structures. That is why a communication-system-type analysis was performed first, in order to determine that the network exhibits features of an anisotropic structure: that it has a characteristic road hierarchy, access roads are perpendicular to main roads in the model, and in direct communication, which optimises for shortest connection time and side roads are flattened towards the main road. The model includes directions of traffic and capacity modified by mobile spatial features – parked cars. Further analysis revealed vital points (nodes), which testifies to the presence of an underlying scale-free structure. Therefore, the developed model and its geospatial data analysis open up new possibilities for research into the dependencies in the network structures of communication systems. Beyond the present analysis treating intersections as nodes, further research should investigate traffic flow through each intersection, and again analyse the model for scale-free structures. Altering the character of a node may reveal completely different dependencies than the ones identified in random structures. References BAJEROWSKI, T. 2003, Podstawy teoretyczne gospodarki przestrzennej i zarządzania przestrzenią (Theoretical foundations of spatial management and space management). Wydawnictwo Uniwerystetu Warmińsko – Mazurskiego w Olsztynie, p. 34-35. BAJEROWSKI, T., KOWALCZYK, A. 2013. Metody geoinformacyjnych analiz jawnoźródłowych w zwalczaniu terroryzmu (The methods of Geoinformation open-source analysis in combating terrorism). Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego w Olsztynie. Olsztyn. BARABÁSI, A. L, ALBERT, R., JEONG, H. 2000. Scale-free characteristics of random networks: the topology of the world-wide web. Physica A: Statistical Mechanics and its Applications, 281.1: 69-77. BARABÁSI, A. L. BONABEAU, E. 2003. Scale-free networks. Scientific American, 288(5): 50-59. BARABÁSI, A. L. 2005. Taming complexity. Nature physics, 1(2): 68-70. BARRAT, A., BARABÁSI, A. L., CALDARELLI, G., DE LOS RIOS, P., ERZAN, A., KAHNG, B., AMARAL, L. A. N. 2004. Virtual round table on ten leading questions for network research. European Physical Journal B, 38.EPFLARTICLE-147435: 143-145. BEDNARCZYK, M., KOWALCZYK, K., KOWALCZYK, A. 2018. Identification of pseudo-nodal points on the basis of precise leveling campaigns data and GNSS. Acta Geodynamica et Geomaterialia, 15: 5-16. BIAŁYNICKI-BIRULA, I., BIAŁYNICKA-BIRULA, I., BIAŁYNICKA-BIRULA, Z., SOWIŃSKI, T. 2014. Modelowanie rzeczywistości: jak w komputerze przegląda się świat (Modeling reality: how the world is viewed in the computer). Wydawnictwa Naukowo-Techniczne, p. 15-178. BIŁOZOR, A., SZUNIEWICZ, K. 2008. Struktura sieci powiązań w układzie miast i regionów (The structure of the network of connections in the system of cities and regions). Rozwój Regionalny i Polityka Regionalna. Uniwersytet im. Adama Mickiewicza, 3: 7-19. BIŁOZOR, A., RENIGIER-BIŁOZOR, M. 2016. The use of geoinformation in the process of shaping a safe space. Informatics, Geoinformatics and Remote Sensing. Cartography & GIS. SGEM2016, Book2, Vol. 3, p. 391-398. CHOJNICKI, Z. 1966. Zastosowanie modeli grawitacji i potencjału w badaniach przestrzenno-ekonomicznych (Application of gravity and potential models in spatial and economic research). Studia KPZK PAN, 14. CIEŚLAK, I., SZUNIEWICZ, K., TEMPLIN, T., CZYŻA, S. 2016. Use of Ant Algorithms to Optimize Pedestrian Communication Routes with the Application of GIS Tools: A Case Study of Olsztyn. Procedia engineering, 161: 2006-2010. CIEŚLIŃSKI, P. 2002. Gazeta Wyborcza. Review of the book Modelowanie rzeczywistości (Modeling of reality). Web page: http://wyborcza.pl/1,75400,1009171.html (access 13.04.2018). DOMAŃSKI, R. 1963. Zespoły sieci komunikacyjnych (Communication network units). PWN. Warszawa. p. 1880. KOCUR-BERA, K. 2014. Scale-free network theory in studying the structure of the road network in Poland. PROMET-Traffic&Transportation, 26(3): 235-242. KOWALCZYK, A. 2013. Określenie odporności układu komunikacyjnego jako jednego z elementów infrastruktury krytycznej Uniwersytetu Warmińsko-Mazurskiego
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w Olsztynie ( Determination of the resistance of the communication system as one from the critical infrastructure elements of the University of Warmia and Mazury in Olsztyn). Żuber (Editor). Katastrofy naturalne i cywilizacyjne - zagrożenia i ochrona infrastruktury krytycznej. Wyższa Szkoła Oficerska Wojsk Lądowych im. Gen. T. Kościuszki we Wrocławiu. Wrocław. p. 153 – 166. KOWALCZYK, A. M. 2015. The use of scale-free networks theory in modeling landscape aesthetic value networks in urban areas. Geodetski vestnik, 59(1): 135–152. KOWALCZYK, A. M. 2017. The Analysis of Networks Space Structures as Important Elements of Sustainable Space Development. Environmental Engineering” 10th International Conference. KOWALCZYK, A. M., OGRODNICZAK, M., BAJEROWSKI, T. 2017. Fire Department interventions mapping with the usage of the GIS tools. 17th International Multidisciplinary Scientific GeoConference SGEM 2017, Informatics, Geoinformatics and Remote Sensing, 17: 497-504. OGRODNICZAK, M., KOWALCZYK, A.M., BAJEROWSKI, T. 2017a. Network structures in developing uniformed service intervention maps. 17th International Multidisciplinary Scientific GeoConference SGEM 2017, Informatics, Geoinformatics and Remote Sensing, 17: 619-624. OGRODNICZAK, M., RYBA, J., RYBA, B. 2017b. Analiza stanu bezpieczeństwa ruchu drogowego z wykorzystaniem narzędzi GIS na przykładzie miasta Olsztyn (Analysis of road safety with the use of GIS tools on the example of the city of Olsztyn). Autobusy: technika, eksploatacja, systemy transportowe, 6: 360363. OGRODNICZAK, M., RYBA, J. 2017. The implementation of the GIS tools in crisis management. World Scientific News, p. 211-218. RENIGIER-BIŁOZOR, M., BIŁOZOR, A. 2015. The analysis of the spatial relationships of urban networks with the use of Thiessen polygons. 15th International Multidisciplinary Scientific GeoConference SGEM 2015. Informatics, Geoinformatics and Remote Sensing. Cartography & GIS. Book2 Vol. 2, p. 11151122. RYBA, J., OGRODNICZAK, M. 2016. Ocena pracy służb w związku z wypadkami komunikacyjnymi z wykorzystaniem narzędzi GIS (Evaluation of service work in connection with traffic accidents with the use of GIS tools). AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe, 6: 356-360.
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THE POSSIBILITIES OF USING DRONES IN ROAD ENGINEERING Kamil Kowalczyk, Ph.D.
Faculty of Geodesy, Geospatial and Civil Engineering University of Warmia and Mazury in Olsztyn Olsztyn, Poland e-mail:
[email protected] – contact person
Roman Węglicki, M.Sc.
Geopartner sp. z o. o. & Logik sp. z o.o. Company President Gdańsk, Poland e-mail: rweglicki@geopartner .gda.pl Abstract The 3D models, orthophoto maps or orthophoto plans that are made with using drones (UAVUnmanned Aerial Vehicle) are very popular type of data used in BIM. The obtained accuracy of the final results depends on few factors e.g. the measuring equipment (the quality of the camera), the quality of the GPS receiver, the plan of flight for measurement mission and software. The aim of the article is to assess the suitability of the flying measurement set in the inventory of construction works and their compliance with the design documentation. As a test field, several sections of the expressway no. 7 Warsaw - Gdansk have been selected. The quality of the photos and the accuracy of the model have been assessed. The differences between the design and as-built have been indicated. As a result, information on the suitability of the flying measurement set for the purposes of this article has been obtained. Key words: geoportal, UAV, dron, GIS, road engineering Introduction Development of mobile technologies (HONKAVAARA et al., 2013; BOCCARDO et al., 2015; DANDOIS et al., 2015; JANOWSKI et al., 2014), GIS systems (LIU et al., 2017; CHOJKA, 2015, JANOWSKI et al., 2014) and data integration systems (WĘGLICKI et al., 2017) lets BIM (Building Information Modeling) allows for the wide use of BIM technology. In this technology, paper and digital data, measurement and design documentation can be represented as the same model. In the case of a single building, the case does not seem too complicated. The construction of linear facilities (railway and road) is a bigger challenge. A very large number of vector and raster data, the extent of objects as well as a large number of people managing the work make it difficult to manage the construction with the use of BIM technology. In this aspect, one of the modern and useful solutions is to obtain visual information using sensors attached to unmanned aerial platforms (UAV). According to (HAN, GOLPARVAR-FARD, 2017), during the documentation of the progress of works, hundreds of photos and videos are collected, which over time become useless without proper archiving. This issue is partly described in the article (WĘGLICKI et al., 2017). Three aspects are crucial: eliability, relevance, and speed (HAN, GOLPARVAR-FARD, 2017). These three aspects can be successfully done using UAV. The goal of the article is to present examples of combining data collected by UAV and a visual analysis of the possibilities of their use in linear construction. Presented case studies confirm the usefulness of UAV technology in practice. Needs and possibilities The investment process for the construction of a linear facility (roads, railways) requires the participation of the surveyor at each stage of its implementation. Due to the surface complexity of these facilities, the main thing is the constant contact of the road contractor with geodetic support and construction supervision. The internet platform - www.geoportal.pro - can be used for efficient information exchange. This portal was created to collect, archive, visualize and share information from the construction site for individual executive and management sections (WĘGLICKI et al., 2017). The main goal of the system is to integrate various data in various formats. These data include orthophoto maps, sketches and orthophoto plans that are made as photogrammetric measurements using UAV.
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Fig. 1 shows UAV construction examples (left - wing, right - multicopter).
Fig. 1. UAV construction examples (left - wing, right - multicopter). Source: Own elaboration.
An important aspect of this technology is the possibility of using various measuring sensors as well as cameras with different spatial resolution. Fig. 2 shows an example of the development of images made using UAV with different details and size of the analyzed area.
Fig. 2. An example of using UAV for photos with various details. Source: Own elaboration.
Such UAV capabilities and results are expected during the process of a road investment. The potential of using UAV can be defined in the following engineering areas: • development of a design situational plan for the investment, • inventory of the construction site, determination of the progress of works, monitoring of investment progress, • precise volume calculations of the material piles, earth masses lying on the construction site, • development of investment visualization for the needs of social consultations, • definition of profiles and sections of terrain, slope exposition, • definition of the direction of water runoff and flooding areas, • definition of the logging area and determining its size, • definition of visibility zones on road curves, • analysis of surface condition and road markings, • as-built visualization. Data and control object The data for the article were obtained using UAV during the investment process of the S7 express road implemented in Poland, in the vicinity of the city of Gdansk. The data was distributed via the www platform.
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Distribution of the data via www platform – geoportal.pro - provides: on-line access from anywhere in the world, access via login and password - to the assigned object, depending on the permissions defined by project management, • access via a computer, smartphone or tablet - all you have to do is to remember your login and password. As a test field, several sections of the expressway were selected, to show the widest usefulness of measurements performed with UAV in linear engineering. • •
Fig. 3. Test/control object. Source: Own elaboration based on www.geoportal.pro.
Visual quality assessment together with a case study The possibilities of using UAV in linear engineering were based on predefined ranges. Three criteria were assessed: investment need, resolution (accuracy, precision), user. Fig. 4 indicates the possibility of identifying with hybrid data the crossing of the road border during the implementation of the road investment. This is the basis for claims by the owners of adjacent land not occupied as intended. Here, the accuracy of the study is at the level of 30cm.
Fig. 4. Crossing the road border. Source: Own elaboration.
Another important aspect of using UAV is to provide information before construction starts. At this stage, the development plan of the investment project is carried out (Fig 5).
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Fig. 5. Development of a design situational plan for the investment. Source: Own elaboration.
The orthophotomap allows not only to visualize the terrain, but also to control the compliance of the land development plan with the map for design purposes and the design documentation (Fig. 6). The accuracy of the study in this case should be at least 10 cm.
Fig. 6. Checking the compliance of the land development plan with the map for design purposes and the construction design documentation. Source: Own elaboration.
High-resolution pictures are required for situational and altitude map control with the actual terrain (Fig. 7). Here, the numerical map (KOWALCZK, KOWALCZYK, 2008) and the orthophotomap are the data to integration. Such high precision with simultaneous clarity of details is ensured by the high-resolution camera and a stable UAV flight. Figs. 8 and Fig. 9 show the use of an orthophotomap developed from UAV data for building site inventory, determination of progress of works, monitoring of investment progress. This solution allows for quick assessment of the progress of works by construction supervision and construction management. In this case, the resolution and accuracy of the study may be varied. During the investment, huge amounts of material are transported to the site, f.ex. crushed aggregate. It is stored on construction sites (Fig. 10) located along the construction sections. Knowledge about the amount of cubic meters stored and available to buit-in is useful for section managers. In this case, the expected accuracy is within 30cm to 50cm.
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Fig. 7. Control of the situational and altitude map with the actual terrain. Source: Own elaboration.
Fig. 8. Inventory of progress of compaction of soil foundation. Source: Own elaboration.
Fig. 9. Monitoring of earthworks. Source: Own elaboration.
Fig. 10. Piles and earth masses stored inside the building site. Source: Own elaboration.
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Even if the investment is done, it is required to do permanent quality control, including deformation and technical condition. Such objects, in particular, are bridges (fig 11) and viaducts exposed to continuous vibrations of different frequencies and environmental factors. UAV has the ability to hang in the air and get very close to the controlled object, especially to places that are difficult to reach for the engineer. Figures 12 and 13 show the possibilities of UAV in assessing the technical condition of the bridge elements that are part of the road infrastructure.
Fig 11. Suspension bridge located in Gdansk. Source: Own elaboration.
Fig. 12. photographic inventory of inaccessible places - example A. Source: Own elaboration.
Such inventory helps the engineers in making decisions about allowing the facility to be used as well as establishing the date and necessity to repair the elements. Road investments, in addition to the construction of new roads, include also works related to the repair or reconstruction of existing damaged road sections. A quick way to get complete information about the condition of a road or its parts is to use an orthophotomap from high resolution images got from UAV (Fig. 14). The clients are companies and institutions managing the road as well as local government authorities. A similar possibility is shown in Fig. 15, where changes have been identified in time: since the implementation of the previous investment and now for the purpose of preparing the tender documentation. In this case, the quality of the photos as well as the orthophotomap should allow for the best preparation of the tender documentation by the investor. At the stage of settlement the completed investment, photogrammetric measurements and data allow to speed up settlements as well as verify the information contained in the documentation. The main customer of such a product is an investor. One way of accounting is to carry out a work balance (Fig. 16) and a list of items to settle (Fig. 17), which were based on UAV measurments.
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Fig. 13. photographic inventory of inaccessible places - example B. Source: Own elaboration.
Fig. 14. analysis of surface condition and road markings. Source: Own elaboration.
Fig. 15. Integration of analog maps with land borders and actual orotofotomaps. Source: own elaboration.
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Fig. 16. Work balance - items to be settled. Source: Own elaboration. List of elements Sum kerbstone K1 K2 K3 K4 K5 K6 K7 K8 K9 K10 K11 K12 K13 K14
3463,27 length [m] 27,8 61,92 171,17 28,43 12,06 155,2 17,04 124,46 2635,1 144,66 5,99 5,76 29,61 44,07
Sum
860,72
rim O1 O2 O3 O4 O5 O6 O7 O8 O9 O10
length [m] 29,78 10,67 33,12 15,51 98,94 152,08 129,08 2,04 244,62 144,88
Sum sewage systems at e kerbstone S1 S2
366,24
Sum
2248,41
length [m] 141,99 224,25
paving P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14
area [m^2] 59,32 50,24 122,8 296,29 16,03 58,84 33,69 26,42 59,35 97,32 182,81 394,22 585,51 265,57
Fig. 17 List of items to be settled. Source: Own elaboration.
Conclusion Linear investment (roads, railways) is a big logistical and technological challenge. Information that can be obtained in almost real time, speeds up execution of works and causes less complications during its implementation. The above article shows the possibilities of using products obtained using UAV, defined the need for its use and the expected quality and accuracy of photogrammetric data. The potential recipients for the developed products were also indicated. The BIM technology, mentioned at the beginning, can successfully use the capabilities of unmanned aircraft at the concept stage, implementation project and during the monitoring as well. In summary, it can be pointed out, that the article does not exhaust all possibilities of using UAV. You can, among other things, add a visualization of the investment for the needs of social consultations, definition of profiles and cross-sections, exposing the slopes, definition the direction of water runoff and flooding areas, denifinition the area of forest clearing and determining its size, definition of the visibility zones on the road arches. Table 1 summarizes the potential of UAV photogrammetric measurements for the needs of road investment. As it can be seen in Table 1, photogrammetric and photographic products developed on the basis of data collected using UAV are applicable at every stage of the linear investment project. From the moment of concept, design documentations, physical implementation, as well as further monitoring of the already completed investment. All the above-mentioned applications and usage of final results would not have been possible, if not the experience of the performers – surveyors, UAV pilots, data developers, expert software for the processing of photographs and integrating different types of data. In this particular case, the data integrator capabilities of geoportal.pro were used (www.geoportal.pro).
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Table1. Summary of the UAV photo measurements for the implementation of a road investment. investment need
resolution (accuracy, precision)
data / product recipient
Identification of the investment border
Identification of crossing the border of the road, compensation, elimination of crossing the border
Accuracy of measurement and development – 10-15cm in relation to the geodetic control network
Landowners, Government, Investor, Contractor
Situational plan of the investment for design purposes
Development of situational plan of the investment for design purposes
Accuracy of measurement and development - 5cm in relation to the geodetic control network
Designer, Investor, Contractor
Control the compliance of official documents, maps and construction design documentation.
Control the compliance of existing situation with design documentation, investment development plan and geodetic maps.
Accuracy of measurement and development - 5cm in relation to the geodetic control network
Designer, Investor, Contractor State and local administration
Checking the situational and altitude maps with the existing area.
Project control, construction economics.
High resolution pictures, sharp details, Accuracy of measurement and development - 5cm in relation to the geodetic control network
Surveyor, Designer, Contractor
Inventory of the construction site
Inventory of progress of road foundation works, monitoring of earthworks, piles and earth masses stored on the construction site, calculating the volume of the material, determining the progress of works, monitoring investment progress
High-resolution pictures, sharp details, accuracy of measurement and development – 10-15cm in relation to the geodetic control network
Site manager, Construction logistics department, Construction supervision
Control of deformations and technical condition
Photographic inventories of inaccessible places
High resolution pictures, sharp detail
Investor, Contractor, Owner of the object
Analysis of road surface condition and road markings
Making decisions to repair or rebuild old destroyed sections
High-resolution photos, sharp details, a few centimeters accuracy
The owner of the object
Preparation of tender documentation
Integration of analog maps with borders and ortophotomap
Accuracy at the presentation level
Investor, Owner of the object, Tenderers
Element of investment stages
The balance of works in relation to the final settlement, List of settlement elements, asbuilt control and visualization
High-resolution photos, sharp details, a few centimeters accuracy
Investor, Contractor
property manager
Source: Own elaboration.
References BOCCARDO, P., CHIABRANDO, F., DUTTO, F., TONOLO, F. G., LINGUA, A. 2015. UAV deployment exercise for mapping purposes: Evaluation of emergency response applications. Sensors, 15(7): 15717-15737. CHOJKA, A. 2015. GML - Does it really work in practice? In 15th International Multidisciplinary Scientific Geoconference (SGEM), Albena, Bulgaria, Date: 18-24 June, 2015. DANDOIS, J. P., OLANO, M., & ELLIS, E. C. 2015. Optimal altitude, overlap, and weather conditions for computer vision UAV estimates of forest structure. Remote Sensing, 7(10): 13895-13920. HAN, K. K., & GOLPARVAR-FARD, M. 2017. Potential of big visual data and building information modeling for construction performance analytics: An exploratory study. Automation in Construction, 73, 184-198. HONKAVAARA, E., SAARI, H., KAIVOSOJA, J., PÖLÖNEN, I., HAKALA, T., LITKEY, P., PESONEN, L. 2013. Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture. Remote Sensing, 5(10): 5006-5039. JANOWSKI, A., NOWAK, A., PRZYBORSKI, M., SZULWIC, J. 2014. Mobile indicators in GIS and GPS positioning accuracy in cities. In International Conference on Rough Sets and Intelligent Systems Paradigms, Springer, Cham, p. 309-318. KOWALCZYK, K., KOWALCZYK, A., 2008. Selected issues concerning map drawing. 7th International Conference „Environmental Engineering”, Vilnius, Lithuania, 22-23 May 2008, Vol. 3, p. 1359-1365.
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LIU, X., WANG, X., WRIGHT, G., CHENG, JC, LI, X. I LIU, R. 2017. Najnowocześniejszy przegląd integracji modeli informacji o budynku (BIM) i systemu informacji geograficznej (GIS). ISPRS International Journal of Geo-Information, 6 (2): 53. WĘGLICKI, R., KOWALCZYK, K., OGÓREK, T. 2017. The integration of numerical and raster data for engineering tasks. In Geographic Information Systems Conference and Exhibition “GIS ODYSSEY 2017”, Italia, Trento.
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PERFORMANCE THRESHOLD OF THE INTERACTIVE RASTER MAP PRESENTATION – AS ILLUSTRATED WITH THE EXAMPLE OF THE JQUERY JAVA SCRIPT COMPONENT Karol Król, Ph.D.
Department of Land Management and Landscape Architecture University of Agriculture in Krakow Krakow, Poland e-mail:
[email protected] – contact person Abstract The purpose of the present work was to determine at what size of the raster file the effective performance threshold of the map application will be exceeded, which will cause difficulties in browsing the map, resulting from, for instance, a prolonged loading time of the screen in the browser window, or from the lessthan-smooth running of the application. Five model versions of the web application, differing in the size of the raster maps, were tested for performance. Applications were created using the Mapbox component: Zoomable jQuery Map. The performance of the application composed of all the raster maps, superimposed one upon another, has been assumed as the benchmark for measurements. The soil and agricultural map, created using the QGIS software, served as the raster base. Performance tests were conducted in an informal manner, using selected web applications. The values of performance indicators – Yslow and PageSpeed Score – were analysed, along with the loading time of the application in the browser window. In conclusion, it was shown that the loading time of the application in the browser window must not be equated with its general performance. Key words: web application performance, performance tests, web mapping, raster maps, mashup Introduction In recent years, the number of generally available components expanding the functionality of websites – the so-called “plug-ins” – has significantly increased. The main advantage is their modularity – they can be used in many projects at the same time, as well as “switched” on and off at the user’s request. Among the wide range of various components extending the functionality of websites, there are those that are responsible for the presentation of spatial data. Interactive cartographic publications made available online have many advantages. Maps are a clear and intuitive way of data presentation – whereas a combination of thematic maps often allows you to see and to show the hidden relationships in numbers. Furthermore, information provided in the form of an interactive map is attractive to the recipient, who finds it easier to remember (BROVELLI et al., 2015). Online maps are published using various techniques and designing tools. They may be made available in the form of dynamic web applications (independent map services, geoportals) or components of other, hybrid websites (mashups). The criteria that can be decisive when selecting a given component typically include its functionality and efficient performance, often resulting from the working principle of the component itself (DANIEL et al., 2011). Websites and web applications have increased their volume over tenfold during the last decade (ZHU, REDDI, 2013). Extensive, multimedia-based, functional websites are the result of technological advances, coupled with the expectations of the users, who are not interested in the infrastructure through which the content is delivered, only in the efficient performance with which that content can be viewed, modified, and downloaded (DICKINGER, STANGL, 2013). This generates a demand for high-performance computer systems and mobile devices that will ensure the comfort of browsing the websites, which provide increasingly complex functionalities. It also requires new design solutions that will ensure high performance (KRÓL et al., 2016). Browsers of raster maps are intended for the publication of “ad-hoc” maps by municipalities and public administration, when there is no economic justification for creating extensive map services, and there is a need to quickly publish the map, for instance, in the case of changing the ordinal numbering of buildings (KRÓL, 2016). These solutions are usually based on raster maps. Limitations to the usability of the presentations thus made available result mainly from the size of the screen that often loads in the browser window in its entirety, which may be inefficient. The purpose of the present work was to determine at what
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size of the raster file the efficient performance threshold would be exceeded, causing difficulties in browsing the map. Online maps as website components Online maps being a component of a website (extending its functionality) are most often elicited in a browser window via a “floating frame” (iframe) or implemented using the API programming interface (BOWIE et al., 2014, PETERSON, 2015). The emergence of application programming interfaces (APIs), i.e. sets of procedures, protocols and tools for creating web applications, has contributed to the creation of numerous and increasingly accomplished mashup and hybrid applications (WOOD et al., 2007, YU et al., 2008). They combine selected thematic content with master maps from geodata providers. APIs facilitate programming of mapping services, which may include a website component, among others (SMITH, 2016). Map components can also be created using the public jQuery JavaScript library (KRÓL, SZOMOROVA, 2015). The advantage of such solutions is the small volume of the application itself, whereas its disadvantage is the dependence of the application’s performance (usability) on the size of the raster, when the component’s operation is based on its presentation. The size of the raster can therefore determine the effective performance of the component, and translate into the performance (usability) of the entire site. Performance matters Effectiveness of websites is considered in many aspects, but most often those relating to technology, and to sales, and it is expressed by numerous parameters. One of those parameters is performance, often equated with the speed of loading the site in the browser window. The website’s performance is largely due to the design solutions adopted, including the techniques and components that had been used to create it (WU, WANG, 2010). Currently, one of the shortcomings of websites (responsive, multimedia-based, interactive, and created on the basis of extensive content management systems – CMS) is their efficiency. Optimization of the latter can be crucial for user comfort. From the user’s point of view, performance is a measure of usability. It is a parameter that determines the comfort of browsing the website, which may have a bearing on conversion goals (SANDERS, GALLOWAY, 2013). Website performance is considered from the perspective of server performance on which it is maintained (server-side performance, where data server is subjected to performance tests) and from the perspective of the website’s performance (client-side performance). Websites are subjected to “on input” performance tests (total load time in the browser window, and the time of reading the content shown on the display) or in the “continuous monitoring” model (when using the application under variable load, simulated or in natural conditions, i.e. during regular use). One of the most important performance parameters is the perceived time of loading the site in the browser window – considering that around 39% of Internet users claim that the speed of the website is more important than its functionality (AKAMAI, 2017). Website performance has a significant impact on its effectiveness. Research has shown that delaying your website’s loading time in a browser window by 100 milliseconds (0.1 seconds) can lower your conversion rate by 7%. A website rendered within 10 seconds gains 46% fewer page views, and its bounce rate is 135% higher. About 53% of mobile site visitors leave it if that site loads for more than three seconds (CROSMAN, 2010). Website performance is also perceived through the lens of the Internet-specific “sense of time”. Studies have shown that, for an average user, the perceived waiting time for a website appears about 15% longer than it actually is. According to research by Google, fast-loading websites generate lower maintenance costs, they are more readily viewed, and visitors spend more time there, while even a half-second delay affects visitor statistics (SINGHAL, CUTTS, 2010). At all stages of creating a website, but also at any time after its publication, it is useful to apply tools that automatically measure selected aspects of its technical and functional quality. The results of automated tests are usually presented in a descriptive form and synthetic point scores – expressed in the letters of alphabet or graphic symbols. A synthetic final score facilitates making a comparison between many similar projects. It also allows you to compare the measurement results obtained using various tools. This fits in with the concept of cross-measurement, consisting in testing selected parameters of the website using at least two different testing tools. Selected testing applications also present lists of critical points that need to be optimized, along with a list of post-testing recommendations. Material and methods Five model, twin versions of the web application were subjected to performance tests of the “clientside performance” type (Fig. 1). Each of them was created out of two raster maps (in PNG format) – the master map, identical in each version of the application, presented by default after eliciting the application in the browser window; and a base map, intended for exploration, i.e. elicited at the user’s request (Table
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1). The performance of the application created from all five base maps superimposed one on top of the other (Fig. 2) was assumed as the benchmark for measurements. The soil and agricultural map of the Proszowice Municipality created using the QGIS software served as the raster basis. Proszowice Municipality is located in the northern part of the Małopolska Province (Poland) in Płaskowyż Proszowicki (the Proszowice Plateau). Table1. Description of selected attributes of raster maps in the form of web applications. No.
Raster size grade (dpi)
Size of the raster in pixels
Size of the raster (MB)
Total size of the application (MB)
1
72
841x595
0.33
0.66
2
150
1753x1240
0.89
1.19
3
300
3507x2480
1.99
2.32
4
450
5261x3720
3.16
3.49
5
600
7015x4960
4.34
4.67
6
Reference application
from 841x595 to 7015x4960*
10.7
10.8
Key: *raster maps elicited incrementally as a result of user activity. Source: Own study.
Fig. 1. View of the application allowing the browsing of a raster map. Source: Own study using the Mapbox component .
Performance tests were performed in an informal manner, using selected online applications (Table 2). The tests were carried out for both mobile devices (in mobile mode) and desktop computers (in desktop mode). Table 2. Online applications used in performance testing. Testing application
Measurement unit
PageSpeed Insights (Google Developers)
PSI D, PSI M attributes
GTmetrix
PageSpeed Score, YSlow
Pingdom Website Speed Test
Google PageSpeed Performance grade, load time, page size
Dareboost: Website Speed Test (DaM)
Performance grade, Speed Index
Website Speed Test – Image Analysis Results
Page Image Score, Total Image Weight (TIW), Potential Compressed Weight (PCW)
Source: Own study.
Page Speed Insights measures site performance on mobile devices (PSI M) and desktop computers (PSI D). The application downloads the resources available at the URL twice – through a mobile client, and through a desktop client – it then measures the time of loading the part of the page visible on the screen, and the time in which the page loads fully. PageSpeed Insights checks whether a site can be generated on a mobile device in less than one second. In the “mobile” test, the time of generating a fragment of the site
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visible on the screen (Above The Fold – ATF) is significant. The result of the measurement is a score between 0 and 100 percentage points (PageSpeed Score). A rating of at least 85 points means that the page performance is relatively good, but its selected parameters can be optimized. The GTmetrix application measures the website’s performance, its loading time in the browser window, and the sizes of its components. The result of the performance measurement is presented using the PageSpeed Score and YSlow indices. The YSlow index is an alternative to the Google PageSpeed Score, created and shared by Yahoo! The YSlow attribute is expressed with a synthetic point score, ranging between 0 and 100 percentage points.
Fig. 2. Schematic arrangement of raster maps, superimposed one upon another, and subsequently elicited using Mapbox. Source: Own study.
The Pingdom Website Speed Test application, like GTmetrix, provides information about the website’s performance, its loading time in the browser window, and the sizes of its components. Dareboost (DaM) provides a module for testing the applications in the mobile mode. The result of the measurements is presented in the form of a synthetic point score and the Mobile Speed Index. The faster the rendering (that is, the better the performance), the lower the index value, with Google recommending that it does not exceed 1000 units. The Website Speed Test Image Analysis Tool application, on the other hand, analyses the graphic files that make up the website being tested. The result of the “degree of image compression” test is expressed by a synthetic indicator, the Page Image Score. The application’s algorithm identifies graphic files that make up the site, measures their volumes, and provides information about the possibilities of their compression. Model applications were created using HTML, CSS and the Mapbox component: Zoomable jQuery Map Plugin (MIT License) (MOHLER, 2018). The jQuery Mapbox Plugin facilitates the presentation of raster graphics. The applications served as raster browsers (Image Viewer) and were developed to consume minimal server resources, as well as to not overburden the Internet connection. The applications were extended by adding a graphical user interface (GUI), which facilitates viewing the map using the navigation icons. Among other things, Mapbox allows horizontal viewing of raster graphics (grab and drag the map area). Also, it simulates the effect of zooming the map view, by overlapping appropriately prearranged vertical rasters. Zooming in the map view consists in the presentation of previously developed rasters. The rasters are entered into the structure of the hypertext document, and displayed in the browser window one under the other. As a result of user activity, individual variations of the raster are elicited, which constitutes a kind of simulation of zooming in on the map view. Mapbox component: Zoomable jQuery Map Plugin was chosen due to its low hardware requirements and lack of restrictions as to the size of the presented raster graphics. Outcome of the study The performance of individual versions of the application on desktop devices gradually decreased with the increase in the size of the master map raster (Table 3), which was correlated with the loading time of the application’s components (Fig. 3). An increase in the raster size caused difficulties in browsing the map. With the raster size equal to 150dpi, “step loading” of individual rasters was noticeable, and with the size exceeding 300dpi, the application lost its smooth operation. Thus, the measurements demonstrated
324
that with a 150dpi grid, the effective performance threshold, at which relatively comfortable use of the application is possible, had been exceeded. 45 40 35 30 25
20
Pingdom
15
Gtmetrix
10
Dareboost
5 0
Fig. 3. Loading time of the application in the browser window depending on the raster size. Source: Own study.
The performance results obtained in the PSI M test are puzzling. They suggest that the performance of applications on mobile devices improves with the increase of the raster size. It should be noted here that the PSI M performance measurement is carried out without full rendering, i.e. not all of the resources constituting the tested application are loaded during the process. However, this does not explain the increase in the PSI M performance index, despite the increase in the raster size. In turn, the results obtained using the Dareboost application show a drop in the application performance on mobile devices with the increase of the raster size. Admittedly, these are not big drops. Everything seems to indicate that application architecture (i.e. the way it was created) is significant for performance. Performance is measured only for those components that are visible to the user when loading the application in the browser window. Other resources, in this case those with the most impact on performance, are elicited when using the application. Then, there may also be a decrease in the application’s performance (that will not be seen in the state of “application rest”). This is indicated by the value of the Dareboost Mobile Speed Index. Its value remains at a similar level regardless of the size of the base raster (Table 3). The tests showed that the size of the YSlow index does not depend on the size of the application’s components that are “waiting to be elicited” (measurement without full rendering). The application was created in such a way that the base map raster (72dpi) would be read in the browser window first, while the master map raster (150-600dpi) would remain “available” to the user, that is, eliciting it in the browser window would occur only as a result of user activity. The base for each version of the tested application was therefore the same; it was the master map rasters that were different. This may translate to the identical size of the YSlow parameter; also when measuring the performance using the Pingdom Website Speed Test application. Table 3. Measurement results for selected performance indices. Testing application PSI GTmetrix
Raster size (dpi)
Reference application
72
150
300
450
600
M
D
M
D
M
D
M
D
M
D
M
D
83
23
67
83
70
74
75
59
75
51
77
43
P
Y
P
Y
P
Y
P
Y
P
Y
P
Y
24
77
83
77
74
77
59
77
51
77
45
77
Pingdom
88
88
88
88
88
88
Dareboost Mobile
58
61
58
54
54
55
4297
2419
2379
2410
2389
2410
Dareboost Mobile Speed Index
Key: M – mobile; D – desktop; P – PageSpeed Score; Y – YSlow. Source: Own study.
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The loading time of the developed applications is not satisfactory. The application presenting the 72dpi raster loaded in the browser window in just over 3 seconds (according to Pingdom and Dareboost), while the loading of the 600dpi map took up to 7 times longer on mobile devices (Table 4). The loading time of an application presenting 300dpi and larger rasters exceeded 10 seconds. It was therefore below users’ expectations. Such presentation does not meet performance standards. Furthermore, the measurements showed that the loading time of the application must not be equated with its general performance (efficiency). The latter remained at a similar level, while the loading time of parts of the application extended with the increase in the size of the raster. Table 4. Loading time of the application in the browser window depending on the size of the raster map. Testing application Pingdom Desktop
Raster size (dpi)
Reference application
72
150
300
450
600
L
S
L
S
L
S
L
S
L
S
L
S
10.01
10.8
3.32
0.55
3.88
1.1
3.62
2.2
4.09
3.4
4.57
4.6
GTmetrix Desktop
6.2
10.8
1.9
0.55
2.8
1.1
2.5
2.2
2.8
3.38
3.2
4.56
Dareboost Mobile
40.86
11.07
3.42
0.56
5.72
1.13
10.66
2.32
15.56
3.54
20.54
4.78
Key: L – loading time, S – total page size. Source: Own study.
The Website Speed Test application has a programmed limit (protection against excessive server load), which users are not informed about. The measurement results were only available for the application presenting the master map raster in a size not exceeding 300dpi (Table 5). This was demonstrated by the reference application test, which consisted of five rasters in the size from 841x595 (72dpi) to 7015x4960px (600dpi). In the test results, it was noted that only those rasters whose size did not exceed 300dpi had been verified. The remaining rasters had been omitted. In the case of tests that were performed in full, in each case the application indicated the possibility of raster compression by about 30%. Table 5. Website Speed Test – Image Analysis Results. Index Page Image Score (PIS) Image Weight Comparison (IWC)
72
150
300
B (good)
B (good)
B (good)
450; 600; Reference no data
TIW
PCW
TIW
PCW
TIW
PCW
TIW
PCW
0.507
0.157/30.9
1.1
0.3/27.8
2.3
0.616/27.2
no data
no data
Key: TIW – Total Image Weight (MB), PCW – Potential Compressed Weight (MB/%). Source: Own study.
Conclusions The tests have shown that the division into raster graphics (maps) prepared for online publication (72dpi) and those intended for printed publications (from 300dpi upwards) is justified. The dynamics of loading raster graphics decreases along with their size. The effective performance threshold, also understood as the threshold of map viewing comfort, or the flexibility threshold, depends on the device on which the map is displayed. The application’s architecture should be different for mobile devices than for desktop devices. Therefore, the way in which the map presentation will be programmed is of great importance. An example of the image viewer that was developed for the presentation of large raster files is Zoomify Viewer. Presentation of the raster in the application window, however, follows the division of the raster into smaller fragments, which are then elicited one by one. This significantly increases the flexibility of the application and determines its usability. The dynamics of the application may also be dependent on the software, including the system platform and the web browser operated by the user. When there is a need to publish a large raster in its entirety – the size of which reduces the efficiency of the application – it should be equipped with graphics presenting the progress of loading the raster map, the so-called “progress bar”. It will focus the user’s attention and reduce the sense of discomfort resulting from long waiting. It is difficult to set one generally accepted performance threshold, characteristic for all web applications presenting raster maps, at which it is displayed in a dynamic (i.e. efficient) way. These applications are executed in various ways, using various programming tools and techniques. Therefore, it is possible to influence application performance not only by reducing the size of the raster (compression),
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although it may translate into a reduction in its adaptability, but also by changing the technique of its presentation (programming changes). Improving the performance of the application requires multiple measurements performed according to the A/B test scenario. This will lead to rejecting design concepts that would reduce application performance. In addition, automated (algorithmic) tests can be supplemented by a performance assessment by the users. Performance tests demonstrated that the first time the application is loaded in the browser window, it runs relatively smoothly. Therefore, the measurement of application performance should be carried out during its use (in monitoring mode), using various testing tools, because it is then that the most problems with its performance may occur – during raster elicitation and browsing or during “raster switching” during which the rasters are elicited by the user when trying to zoom in on the map view. Therefore, the biggest fluctuations in performance may occur during the use of the application, and not during the first loading of the application in the browser window. Delays and lack of smoothness in the raster presentation during its browsing may be decisive for the user in terms of discontinuing to use the application. It is therefore important to equip the application with mechanisms that provide feedback in the form of graphical information about the loading progress (status) of the application. References AKAMAI, 2017. Akamai Online Retail Performance Report: Milliseconds Are Critical. State of Online Retail Performance report, https://goo.gl/72fpyT (access: 24.01.2018). BOWIE, G.D., MILLWARD, A.A., BHAGAT, N.N. 2014. Interactive mapping of urban tree benefits using Google Fusion Tables and API technologies. Urban Forestry & Urban Greening, 13(4): 742-755. BROVELLI, M.A., ZAMBONI, G., MUNOZ, C. A. 2015. From paper maps to the Digital Earth and the Internet of Places. Rendiconti Lincei, 26(1): 97-103. CROSMAN, P. 2010. Online Banking Customers Expect Fast Website Performance, Survey Finds. InformationWeek: Connecting The Business Technology Community, https://goo.gl/FdWDyH (access: 24.01.2018) DANIEL, F., MATERA, M., WEISS, M. 2011. Next in mashup development: User-created apps on the web. IT Professional, 13(5): 22-29. DICKINGER, A., STANGL, B. 2013. Website performance and behavioral consequences: A formative measurement approach. Journal of Business Research, 66(6): 771-777. KRÓL, K. 2016. Data presentation on the map in Google Charts and jQuery JavaScript technologies. Geomatics, Landmanagement and Landscape, 2: 91-106. KRÓL, K., SZOMOROVA, L. 2015. The possibilities of using chosen jQuery JavaScript components in creating interactive maps. Geomatics, Landmanagement and Landscape, 2: 45-54. KRÓL, K., SZEWCZYK, B., PAWŁOWSKA, B. 2016. Interaktywna prezentacja zagadnień środowiskowych za pomocą Google Fusion Tables na przykładzie zdjęć fitosocjologicznych wybranych okolic Tenczynka (Interactive presentation of environmental issues using Google Fusion Tables on the example of phytosociological images of selected Tenczynek areas). Acta Sci. Pol., Formatio Circumiectus, 15(4): 253-264. MOHLER, A. 2018. Mapbox: Zoomable jQuery Map Plugin, https://goo.gl/2WIKh (access: 20.01.2018). PETERSON, M.P. 2015. Evaluating mapping APIs. In: J. Brus, A. Vondrakova, V. Vozenilek (Editors). Modern Trends in Cartography. Springer, Cham., 183-197. SANDERS, J., GALLOWAY, L. 2013. Rural small firms' website quality in transition and market economies. Journal of Small Business and Enterprise Development, no. 20(4): 788-806. SINGHAL A., CUTTS, M. 2010. Using site speed in web search ranking. Google Webmaster Central Blog, https://goo.gl/sVusvY (access: 24.05.2017). SMITH, D. A. 2016. Online interactive thematic mapping: Applications and techniques for socio-economic research. Computers, Environment and Urban Systems, 57: 106-117. WOOD, J., DYKES, J., SLINGSBY, A., CLARKE, K. 2007. Interactive visual exploration of a large spatiotemporal dataset: reflections on a geovisualization mashup. IEEE Transactions on Visualization and Computer Graphics, 13(6): 1176-1183. WU, Q., WANG, Y. 2010. Performance testing and optimization of J2EE-based web applications, In: Second International Workshop on Education Technology and Computer Science, ETCS, 2: 681–683. YU, J., BENATALLAH, B., CASATI, F., DANIEL, F., 2008. Understanding mashup development. Internet Computing, IEEE Internet Computing, 12(5): 44-52. ZHU, Y., REDDI, V.J. 2013. High-performance and energy-efficient mobile web browsing on big/little systems. In International Symposium on High Performance Computer Architecture (HPCA), 13–24.
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DESIGN AND IMPLEMENTATION OF THE SPATIAL DATABASE FOR THE ANALYSIS OF RESIDENTIAL ESTATE MARKET Prof. Janusz Kwiecień, Ph.D. Department Geomatics and Spatial Economy UTP University of Science and Technology Bydgoszcz, Poland e-mail:
[email protected]– contact person
Małgorzata Krajewska, Ph.D. Department Geomatics and Spatial Economy UTP University of Science and Technology Bydgoszcz, Poland e-mail:
[email protected]
Kinga Szopińska, Ph.D. Department Geomatics and Spatial Economy UTP University of Science and Technology Bydgoszcz, Poland e-mail:
[email protected] Abstract In order to effectively manage the database on the real estate market, advanced IT technologies are necessary to provide mechanisms for entering, collecting, analysing and storing cadastral data. Solutions for the real estate market modelling should be treated as an important element for the development of the spatial economy. The main goal of this article is to present the spatial modelling technology of GIS databases for residential real estate using the UML. Key words: spatial database, GIS, Unified Modelling Language (UML), real estate market, Poland Introduction The appraiser needs quick access to relevant information to effectively do his job. Each participant in the real estate market collects data on real estate that were subject to market transactions. Depending on the type of real estate surveyed, data may include transactions regarding the record plot, building or premises (residential premises and premises designed for other purposes). When assessing the value, the appraiser, in addition to analyse the descriptive data, should be able to locate the specific real estate in space in order to identify them spatially and obtain information about the real estate environment in order to select similar properties. The use of GIS technology (LONGLEY, 2005; PARZYCH, CICHOCIŃSKI, 2006; BYDŁOSZ, 2015; SZOPIŃSKA, 2017) seems to be an ideal solution for the appraiser, that provide mechanisms for entering, collecting, analysing and storing real estate data. In Poland, property appraisers in their work use various tools to build the database on the real estate market, including, among others (BIELIŃSKI, 2015): • Walor (http://www.pronet.com.pl) – version with the Partner program and without this program, • Pricebook, (http://www.pricebook.pl), • Maciej Solarz Internet Database (http://www.msrm.pl), • The program of Research Centre of Real Estate Market Sp. z o.o. (http://www.ebaza.obrn.pl), • The program of the Lower Silesian Real Estate Price Database, • Krzempek-Pospieszałowski Transaction Analysis Systems (http://www.analizysat.pl). A comparison of some possibilities of these individual programs tools is presented in the Table 1. It shows that the spatial presentation of the analysed data contained in these programs is based on the global system of Google Maps, which makes detailed spatial analysis difficult, for example: underground utilities, detailed topography. This article presents a different proposal for the collection, description and spatial presentation of real estate data, which is based on the spatial modelling technology of GIS databases for residential real estate using the UML.
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Table1. Basic information about programs. BASIC DATA ABOUT THE PROGRAM PROGRAM NAME
Walor
Pricebook
internet database
PRODUCER
Pronet
Widelane
Maciej Solarz
WEB PAGE
www.pronet.com.pl
www.pricebook.pl
www.msm.pl
BASIC FUNCTION
database with a user-friendly interface for searching and presenting data
database with a user-friendly interface for searching and presenting data
database with a modest interface equipped with basic functions that enables searching and downloading data on own computer
BUILDING A DATABASE
Database available only for authorized persons
Database available only for authorized persons
Database divided into a free part (non-standard properties) available to all appraisers and paid (other transactions) available to authorized persons
TYPES OF TRANSACTIONS IN THE DATABASE
Buildings, land, premises, rents, transmission easement
Premises, buildings, undeveloped, rents
Unusual properties, premises, buildings, undeveloped, rents
WAY OF DEFINING LOCATION
Database fields: province, county, commune, city, address
Database fields: province, county, commune, city, address
Database fields: province, county, commune and An additional field for manual entering address
INTEGRATION WITH GOOGLE MAPS
yes
yes
planned
PRINCIPLE OF OPERATION
Source: Own study.
The database model At the moment, the most popular database design tool is Computer Aided Software Engineering (CASE). Using relevant CASE tools allows increasing effectiveness of database development. The logical model of the database which can be recorded using object modelling language – Unified Modelling Language (UML) can be used for automatic generation of the database schema that complies to the specification (DATABASE…). Spatial database can be designed in 3 steps: conceptual model, logical model and physical model. Building a conceptual model involves a range of thought processes and ideas regarding the project. The designer should imagine the problem and its solutions methodology. The main task in the conceptual process of building a data model is precise definition of objects of interest and identification of relationships between them. At this stage, the way of writing descriptive attributes is determined and spatial properties of objects and relations between them. As a standard, UML is used, which is a record of expressing object models. UML is a graphic modelling language that enables graphic imaging and documenting of the real world in terms of objects. It is supported by the largest software and database vendors to assist with the documentation of the design tool (CASE), e.g. Sparx Enterprise Architect (DESIGNING…). The great advantage of UML is the ability to freely and repeatedly modify the diagrams described in it. UML has been accepted as a formal language for representing conceptual schemas in the ISO 19100 series (ISO 19101-1:2014). Based on the application schema, a physical model (implementation) of database is built. The Conceptual Model The outlines of the first version of the conceptual model that arises as a result of conceptual modelling are always born in the modelling person's head. It starts with the selection of a fragment of the world that will be modelled (Fig. 1). It is necessary to limit the world around us territorially and substantively. Territorial restriction means subtracting the decision about what area we will model: cities, commune, country, etc. (universe of discourse in Fig. 1). Substantial limitation means choosing the types of objects, ideas, facts, processes that should be in the model (universe of discourse). We decide to build a model for a spatial data system or some other. From all elements (objects and not only) located in a given area and related to a given subject, we choose the ones described in the model and then in the system. In the next step, we begin to think about what information of objects properties we want to collect. Therefore, a conceptual model is created. If we construct a model that will describe more than one object, then there is the need to save our ideas, not to forget them, be able to show and discuss with
329
someone, then something to follow etc. In other words, we put our formalism on our model in the form of conceptual schema language, e.g. UML. Then we get a conceptual schema, which for a specific field is called the application schema.
Fig. 1. From the real world to the conceptual schema. Source: Own study on the basis of ISO 19101-1:2014.
The database schema Designing ArcGIS geodatabase with Enterprise Architect 2017 was used for the spatial database of residential real estate. This environment provides the UML profile for modelling ArcGIS concepts and the ability to generate ArcGIS schemas as XML (DESIGNING…). Visualization of the diagram of relationships between classes of diagrams “Buildings”, “Streets”, “Districts”,Traffic_str" for spatial database of residential real estate
is shown in Figure 2.
Fig. 2. Diagram of relationships between classes of diagrams “Buildings”, “Streets”, “Districts”,Traffic_str" for spatial database of residential real estate. Source: Own elaboration based on Enterprise Architect.
330
The source of spatial information for the property valuation system is cadastral parcels and buildings. Residential premises are characterized by a clear difference in relation to the aforementioned types of real estate. In the case of many apartments in one building, a flat in the database model is associated with the feature class: Buildings, thanks to which it can be located spatially. Traffic is defined as the table (Traffic_str), not as the feature class, in which objects have spatial attributes. Information about the size of noise acting on the building (flat) due to road traffic will be possible via a specific relationship between the table named Traffic_str and the feature class: Buildings. In the database model, there are also feature classes named: Streets and Districts with mutual relations. This allows for complex spatial analyses regarding the impact of noise on housing prices. At the end of the database design description, it is worth saying that this project defined the most basic attributes for the analysis of the impact of noise on housing prices. However, the proposed scope of the information described is not final, as it is possible to re-use the UML model schema for further objects and attributes modification. The example of implementation of gis database for residential estate with road noise factor After the design phase, it is advisable to repeatedly check the model semantic, to prevent any errors propagating to the implementation of the schema. Enterprise Architect provides a built-in model checker specifically for the ArcGIS Workspace models. After completing the model, Enterprise Architect can generate the appropriate ArcGIS schema as a XML Workspace document. The next step is to automatically generate an empty geodatabase in ArcGIS Catalogue folder and import to it a XML Document Workspace. The geodatabase preparation for use by property appraisers includes the import of spatial data for districts, buildings and streets to the system. ArcGIS allows us to import data from many formats, such as: * .shp, * .dgn, * .dwg and * .dxf. A database for real estates in GIS is an ideal source of spatial information for property value appraiser who needs a piece of information for appraisal. Every software belonging to the group described as desktop GIS has tools for finding, sorting and analysing the descriptive and geographic information in the geodatabase (ArcGIS Desktop Help). How we can use ArcGIS system for spatial analysis is described below. ArcGIS allows you to search for data, and then select records in the database according to built SQL expressions. We can use comparison operators, such as: equal (=), not equal (), greater than (>), smaller than ( =), less than or equal ( 65 AND Noise
