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International Journal of Digital Earth

ISSN: 1753-8947 (Print) 1753-8955 (Online) Journal homepage: http://tandfonline.com/loi/tjde20

Big Earth Data: a new challenge and opportunity for Digital Earth’s development Huadong Guo, Zhen Liu, Hao Jiang, Changlin Wang, Jie Liu & Dong Liang To cite this article: Huadong Guo, Zhen Liu, Hao Jiang, Changlin Wang, Jie Liu & Dong Liang (2017) Big Earth Data: a new challenge and opportunity for Digital Earth’s development, International Journal of Digital Earth, 10:1, 1-12, DOI: 10.1080/17538947.2016.1264490 To link to this article: http://dx.doi.org/10.1080/17538947.2016.1264490

© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 04 Dec 2016.

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Date: 23 January 2017, At: 18:23

INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2017 VOL. 10, NO. 1, 1–12 http://dx.doi.org/10.1080/17538947.2016.1264490

Big Earth Data: a new challenge and opportunity for Digital Earth’s development Huadong Guoa,b, Zhen Liua,b, Hao Jianga,b, Changlin Wanga,b, Jie Liua,b and Dong Lianga a

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, People’s Republic of China; International Society for Digital Earth

b

ABSTRACT

ARTICLE HISTORY

Digital Earth has seen great progress during the last 19 years. When it entered into the era of big data, Digital Earth developed into a new stage, namely one characterized by ‘Big Earth Data’, confronting new challenges and opportunities. In this paper we give an overview of the development of Digital Earth by summarizing research achievements and marking the milestones of Digital Earth’s development. Then, the opportunities and challenges that Big Earth Data faces are discussed. As a data-intensive scientific research approach, Big Earth Data provides a new vision and methodology to Earth sciences, and the paper identifies the advantages of Big Earth Data to scientific research, especially in knowledge discovery and global change research. We believe that Big Earth Data will advance and promote the development of Digital Earth.

Received 27 October 2016 Accepted 21 November 2016 KEYWORDS

Digital Earth; Big Earth Data; data-intensive science; knowledge discovery; global change

1. Introduction Since the outbreak of the second industrial revolution, carriers of data have practically doubled every decade. Entering into the information age, data repositories doubled every three years. In the twentyfirst century, the rapid advancement of networks and computation has enabled the emergence of ‘big’ data without spatial and temporal restrictions. Data can be ‘big’ in different ways (Lynch 2008). The International Data Corporation defines big data as ‘a new generation of technologies and architecture, designed to economically extract value from very large volumes of a wide variety of data, by enabling high-velocity capture, discovery, and/or analysis’ (http://idcdocserv.com/1142). Adrian (2011) summarized big data as a data set that ‘exceeds the reach of commonly used hardware environments and software tools to capture, manage, and process it within a tolerable elapsed time for its user population’. McKinsey Global Institute defined big data as ‘datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze’ (www.mckinsey. com/mgi/publications/big_data/pdfs/MGI_big_data_full_report.pdf). David Kellogg said that big data is simply ‘too big to be reasonably handled by current/traditional technologies’ (www.dbms2. com/2011/09/11/big-data-has-jumped-the-shark/). It has been predicted that the worldwide data volume will increase to 40 trillion gigabytes by 2020, doubling every two years (Gantz and Reinsel 2012). Studies show that about 80% of data are related to a spatial location (Densham and Goodchild 1989; Shekar and Xiong 2007; Li and Li 2014). Since CONTACT Huadong Guo [email protected] Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, International Society for Digital Earth, No. 9 DengZhuang South Road, Haidian District, Beijing 100094, People’s Republic of China © 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http:// creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

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the first Earth observation satellite was launched half a century ago, there have been more than 510 Earth observation satellites launched globally for comprehensive observation of the Earth system. Earth observation satellites have developed with much higher spatial and spectral resolutions, and the data transmission speed and storage capacity are increasing accordingly (Guo 2012; Ma et al. 2015; Chi et al. 2016). The amount of remote sensing data produced by airborne and spaceborne sensors is increasing at a rate of a terabyte per day, and a single data set can reach a gigabyte. Statistically, only the Earth Science Data and Information System of NASA archived 7.5 PB of data in 2013 (Ramapriyan et al. 2013). By 2014, for only the European Space Agency, the amount of Earth observation data exceeded 1.5 PB (He et al. 2015). In addition, Web 2.0, mobile devices, citizen participation, and crowdsourcing have become another stream in the collection of geo-related socioeconomic data with the advancement of networks (Salk et al. 2016). In situ sensor network data (e.g. OpenStreetMaps), GPS trace data from mobile devices, geo-social media data (e.g. Twitter), and crowdsourcing/volunteered geographic information data contribute to the increase in data (Howe 2006; Goodchild 2007; Ramm, Topf, and Chilton 2011; Evans et al. 2014; Lee and Kang 2015). As an example of big data in the field of Earth science, Digital Earth has proved to be a comprehensive system for organizing, analyzing, simulating, representing, and mining data from the Earth system, and creating knowledge from it. The concept of ‘Big Earth Data’, originally put forward as a new stage of Digital Earth (Guo et al. 2014), was defined further by Guo, Wang, and Liang (2016) as the big data obtained through Earth observation means (e.g. spaceborne, airborne, and ground sensors). The advent of big data has injected new impetus into the study of Digital Earth, as highlighted by the sixth Digital Earth Summit with the theme ‘Digital Earth in the Era of Big Data’. Organized by the International Society for Digital Earth (ISDE), the summit was convened in Beijing, China, in 2016. It attracted experts towards discussions on advances in technologies and applications of Digital Earth in the context of big data. It was an opportunity to review the developing progress of Digital Earth science and technology, and look ahead to new stages in the future. This paper summarizes the achievements and development milestones of Digital Earth during the past 19 years. In Section 3, the opportunities and challenges for Digital Earth in the era of big data are examined. Following that, Section 4 discusses how Big Earth Data benefits scientific research. Finally, some future thoughts for Big Earth Data are proposed.

2. Development of Digital Earth 2.1. Achievements of Digital Earth Digital Earth is a global initiative aimed at harnessing the data and information resources of Earth to quantitatively describe and represent the planet, and to monitor, measure, and forecast natural and human activities on Earth. Put forth in 1998, the vision of Digital Earth was articulated as a multiresolution and three-dimensional visual representation of Earth that would help humankind to take advantage of geo-referenced information on physical and social environments (Gore 1999). Following that, Digital Earth received greater attention in scientific and social communities (Chen 1999; Goodchild 1999, 2008; Guo, Fan, and Wang 2009; Annoni et al. 2011; Craglia et al. 2012; Goodchild et al. 2012). 2.1.1. Digital Earth research Driven by different requirements, such as Internet location information services, regional sustainable development, security, decision-making, Earth system science research, and global change, Digital Earth systems have evolved and matured with distinctive features. According to various research purposes, the Digital Earth system could be divided into three categories: (i) location-based commercial platforms; (ii) science platforms based on Earth system sciences; and (iii) public platforms oriented toward regional sustainable development and decision support. Here we briefly introduce the first two Digital Earth systems.

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Starting with the first 3D Earth geographic teaching software Atlas 2000 launched by Microsoft, Earth System was developed in 2001 integrating large-scale remote sensing images and important point data sets into a global 3D model with several terabytes of data. Then Esri launched ArcGIS 9 to visualize multi-resolution global data. In 2005, Google launched Google Earth, which integrates computer technology and 3D technology for freely browsing Earth in 3D, allowing querying, measurement, analysis, and location services based on a mass of remote sensing data (Grossner and Clarke 2007). Since then a number of virtual globes have been produced, including Skyline Globe Virtual Earth (Skyline), WorldWind (NASA), GeoGlobe (Wuhan University), and Virtual Earth and Bing Maps (Microsoft). In 2006, Nature reported on a ‘Virtual Earth’ as an entirely new way to observe and understand Earth with 3D visualization (Butler 2006). The combination of Web 2.0 and sensor networks with virtual Earth technology has produced a voluntary Digital Earth system, reflecting the needs of in-depth applications (Goodchild 2007). Along with the theoretical and technological development of Digital Earth, many scientific platforms have also been established. The Digital Earth Prototype System of the Chinese Academy of Sciences (DEPS/CAS) produced by the Key Laboratory of Digital Earth Science at the CAS Institute of Remote Sensing and Digital Earth is such a platform integrating remote sensing image receiving and processing software, graphics editing software, spatial information processing and grid computing, spatial information services, virtual reality, and a wide range of applications services (Guo, Fan, and Wang 2009). It can efficiently analyze Earth science data from remote sensing observation for applications in multiple fields, for example global climate change and earthquake disasters (Guo, Fan, and Wang 2009). Eyes on the Earth created by the Jet Propulsion Laboratory is a computer visualization software to visualize in-situ data from a number of NASA’s Earth orbiting spacecraft and those collected on Earth itself. It lets users monitor Earth’s vital signs, such as sea-level height, atmospheric carbon dioxide concentration, and Antarctic ozone, and checks the hottest and coldest locations on Earth with a global surface temperature map. It also displays the location of all of NASA’s operating Earth-observing missions in real time (NASA 2009). In addition, many other countries’ governments and institutes have produced Digital Earth platforms for certain research purposes. For example, Blue Link and Glass Earth, both explored by the Australian government, aimed to, respectively, observe and simulate the ocean and to explore the top kilometer of the Australian continent’s surface and its geological processes. The Earth Simulator, developed by three Japanese institutes, provided support in environmental change research (Yokokawa 2002). 2.1.2. International Society for Digital Earth In 1999, the first International Symposium on Digital Earth was initiated by the predecessor of the ISDE, namely the International Steering Committee of the International Symposium on Digital Earth. In response to the primary output of the symposium, the 1999 Beijing Declaration on Digital Earth, ISDE was established in Beijing in 2006. ISDE is an international scientific organization that principally promotes academic exchange, education, science and technology innovation, and international collaboration towards Digital Earth. The mission of ISDE is to benefit society by promoting the development and realization of Digital Earth. ISDE sets up collaborative mechanisms with other organizations for sharing knowledge and ideas on Digital Earth. In 2009, ISDE joined the Group on Earth Observation (GEO), which is the world’s largest inter-governmental organization on using geospatial data. ISDE also has established partnerships with the Committee on Data for Science and Technology, International Eurasian Academy of Sciences, Global Spatial Data Infrastructure Association, and African Association on Remote Sensing of the Environment. It is now widely recognized around the world as a key international organization on geospatial information science research. 2.1.3. International symposia and summits on Digital Earth To promote Digital Earth’s development, ISDE has convened many academic events for scholars in the Digital Earth community to communicate and exchange thoughts and ideas. Since the first

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International Symposium on Digital Earth in 1999, the symposium has been held biennially. So far there have been nine symposia held in seven countries worldwide. To meet the demand of the community, ISDE began to organize Digital Earth summits, which are meant to attract experts towards specialized discussions on specific, narrow themes. These summits are also held biennially in between the ISDE symposia. There have been six summits held in five countries. In addition, ISDE organizes international workshops to discuss future strategies for the promotion of Digital Earth. In 2011, a workshop on a ‘Digital Earth Vision to 2020’ was held in Beijing. Two milestone papers were produced as the outcome of that workshop, and were published in the journals PNAS and International Journal of Digital Earth (IJDE). These vision papers were a crystallization of the ideas and collective imagination of the ISDE council members. In May of 2016, another ISDE Workshop was held in Russia. These academic events served as international platforms to exchange ideas and research results, and laid a strong foundation for improving and enriching the Digital Earth concept and promoting Digital Earth applications. 2.1.4. International Journal of Digital Earth The IJDE is the academic journal of the ISDE. IJDE is the first international, peer-reviewed academic journal focusing on the fields related to Digital Earth. It is jointly published by the ISDE and the English publisher Taylor & Francis. IJDE was launched in March 2008, and was accepted for coverage by the Science Citation Index Expanded in August 2009. In 2015, IJDE had an impact factor of 3.291, ranking 4th out of 28 remote sensing journals and 7th out of 46 geography journals. IJDE has since been included in 12 large international citation databases. Currently, IJDE has become the core academic platform in the international research field of Digital Earth. It will continue to play a more important role in the disciplinary development of Digital Earth, in promoting information sharing at a global scale, and in leading the sustainable development of Digital Earth science and technology. 2.2. Milestones of Digital Earth The understanding of Digital Earth has evolved along with technological advances in terms of Earth observation, geographic information systems, global positioning systems, and the Internet. Certain development milestones of Digital Earth have demonstrated the changes in perception and research progress of this concept, stimulated by scientists, governments, and enterprises. 2.2.1. Milestone 1: the Digital Earth: understanding our planet in the twenty-first century In Al Gore’s 1998 speech ‘The Digital Earth: Understanding Our Planet in the Twenty-First Century’, he sketched a visual representation of Earth. This ‘Digital Earth’ was embedded with vast quantities of geo-referenced data and had the ability to manage and display massive geospatial information. Few of the technologies that were needed for building a Digital Earth, for example, computational science, satellite imagery, broadband networks, interoperability, and metadata, were sufficient at the time, but this was the origin of the Digital Earth vision. It was a very challenging scientific vision for research, industry, and political methods for stimulating economic progress, having much more attention given to a visual environment or computing system for global geo-referenced data and information. 2.2.2. Milestone 2: 1999 Beijing Declaration on Digital Earth An important output of the first International Symposium on Digital Earth in 1999 is the 1999 Beijing Declaration on Digital Earth was promulgated (ISDE1 1999). It gave a clear definition of the research scale for Digital Earth, from two directions, on global issues and the Earth system. It called for the importance of capacity building for technologies. As a response to Gore’s speech, it

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underlined five key technologies, though it fit in more practical objectives and specific research areas in terms of information and technology infrastructures, global systematic observation and modeling, communication networks, databases, and interoperability of geospatial data. It conferred and agreed that the action of Digital Earth should start with three priorities to tackle ‘problems in environmental protection, disaster management, and natural resource conservation’. It had the aims of raising awareness of and bringing more stakeholders into the vision of Digital Earth, so the declaration called for adequate support, close cooperation, and collaboration between governments, public and private sectors, non-governmental organizations, and international organizations and institutions. 2.2.3. Milestone 3: 2009 Beijing declaration on Digital Earth After 10 years of development of Digital Earth, along with advances in science and technology in terms of spatial information technology, communication network technology, high-performance computing, and Earth system science, a second Beijing Declaration on Digital Earth was issued in 2009 (ISDE6 2009). In this declaration, the importance of creating a Digital Earth data-sharing platform was raised. It may have resulted from the awareness of the need to provide access to diverse Earth observation data and geo-information for a broad range of users in both public and private sectors. Digital Earth shifted to a more practical system design to meet the demands for data and information sharing, and assisting the issues of closing the digital divide. The eight advanced technologies defined in this declaration, which should be integrated by Digital Earth, were more oriented toward Earth observation data and information. They were Earth observation, geo-information systems, global positioning systems, communication networks, sensor webs, electromagnetic identifiers, virtual reality, and grid computing. Regarding applications, the declaration adopted a stance that Digital Earth should expand its role in all fields related to global climate change, natural disaster prevention and response, new energy sources, agricultural and food security, and urban planning and management. It continued to recommend cooperation and collaboration among sectors and stakeholders, and, in addition, called for more investments in scientific research from planners and decision-makers. 2.2.4. Milestone 4: Digital Earth vision 2020 In 2011, 15 experts from ISDE gathered in Beijing and discussed the developing trends of Digital Earth. The seminar eventually led to two scientific papers: ‘Next-Generation Digital Earth’ published in PNAS (Goodchild et al. 2012) and ‘Digital Earth 2020: Towards the Vision for the Next Decade’ published in IJDE (Craglia et al. 2012). These papers reviewed the progress of Digital Earth since 1998 and predicted future development in light of the rapid advances of science and technology, especially in the geo-information sciences. These papers provided a new understanding of the Digital Earth concept. The paper titled ‘Next-Generation Digital Earth’ proposes that new developments in Internet, 3D, and Earth observation technologies have further accelerated the fulfillment of the Digital Earth concept and expanded the possibilities of what Digital Earth can be. It has become clear that the next generation of Digital Earth will not be a single system but, rather, multiple connected infrastructures based on open access and participation across multiple technological platforms that will address the needs of different audiences. A more dynamic view has also been proposed of Digital Earth as a digital nervous system of the globe, actively informing about events happening on (or close to) Earth’s surface by connecting to sensor networks and situation-aware systems. ‘Digital Earth 2020: Towards the Vision for the Next Decade’ identifies the main policy, scientific and societal drivers for the development of Digital Earth, and illustrates the multi-faceted nature of a new vision of Digital Earth grounding it with a few examples of potential applications. Key technologies have been developed with the evolution of Internet bandwidth and improved visualization techniques. It is equally important as social developments and the widespread adoption of social networks, which serve as a key way to communicate and turn citizens into major providers of information.

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3. Advent of Big Earth Data 3.1. Big data gains attention worldwide Big data, as a resource for exploring the world, a revolution in seeing the world, and an innovation in thinking about the world, has been seen as a ‘strategic highland’ in the new data-intensive era. It has gained attention from governments of nations around the world. Governments of different countries have made efforts to grasp the advantage brought by big data by setting up national strategies. Early in 2012, the government of the United States announced the ‘Big Data Research and Development Initiative’, aiming at improving the capability for knowledge discovery from big data (http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_ fact_sheet_final_1.pdf). In 2014, two documents were presented to the President of the United States, namely ‘Big Data: Seizing Opportunities, Preserving Values’ and ‘Big Data and Privacy: A Technological Perspective’. The European Commission released a statement on ‘Open Data: An Engine for Innovation, Growth and Transparent Governance’ in 2011. The Australian government announced ‘The Australian Public Service Big Data Strategy’ in 2013. The Chinese government announced in 2013 that big data was regarded as one of the strategic resources of social development. To respond to this initiative, several projects funded by the National Natural Science Foundation and the Ministry of Science and Technology of China were launched. In 2015, the Chinese Government released its ‘Action Plan for Promoting the Development of Big Data’. Besides nations, big data has attracted global attention from international organizations. In 2012, the UN Global Pulse published a white paper on ‘Big Data for Development: Opportunities and Challenges’, suggesting that projects/programs on big data research can be promoted as a national strategy. ‘Big Earth Observation Data for Climate Change Research’ by a research team of the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, was one of the winners of the UN Big Data Climate Challenge. It shows how big data can drive climate actions. The Organization for Economic Co-operation and Development released ‘Exploring Data-Driven Innovation as a New Source of Growth’ in 2013, exploring the potential role of data and data analytics for the creation of significant competitive advantages and for the formation of knowledge-based capital. The International Council for Science (ICSU) published its ‘Strategic Plan 2012–2017’, stressing the importance of data management and new knowledge discovery within huge amounts of data. Big data, especially Big Earth Data, provides powerful tools to understand and explain the Earth system, and to further benefit sustainable global development. In response to it, the Future Earth, a 10-year initiative jointly initiated by ICSU and the International Social Science Council was launched in 2015 to advance global sustainability science and research capacity building through effective inter-disciplinary collaboration. As an inter-governmental organization, GEO initiated a mission of building the Global Earth Observation System of Systems (GEOSS), which coordinates Earth observation data and processing systems at a global scale. Within GEOSS framework, a global partnership towards the big Earth observation data has been established.

3.2. Big Earth Data brings new impetus to earth science With the development of Earth observation technology in the field of Earth science, a huge amount of scientific big data has been generated through various aspects of Earth observation, geophysics, geochemistry, geological surveying, and ground sensor networks. These data contain rich information that is heterogeneous, multi-source, multi-temporal, multi-scale, high-dimensional, highly complex, and unstructured (Laney 2001; Fromm and Bloehdorn 2014; Nativi et al. 2015). There is great potential to promote in-depth development of Earth science research, and Big Earth Data can be seen as a new key to understanding the world. Recognizing that Earth science research has been transformed from traditional empirical data collection, theoretical science, and computational simulation to data-intensive scientific discovery, the

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research methodology has changed to exploring correlation among huge multi-disciplinary or interdisciplinary data sets (see Figure 1). With these data sets, it is possible to identify new patterns, discover new knowledge, and establish new rules hidden behind the data so as to help humankind understand the real world and to guide people toward correct decisions and efficient performance (Guo et al. 2014). With increasing attention paid to big data, it is gradually becoming clear that rapidly growing big geospatial data play an important role in enhancing the capability of humans to monitor and understand society and nature, and to react to environmental problems from spatial and temporal dimensions (Mayer-Schonberger and Cukier 2013; Chen and Yang 2014). In 2015, UN initiated 17 Goals for Sustainable Development aiming to end poverty, inequality, and climate change by 2030. Among the 17 goals, at least 8 could be realized benefiting in different ways from Big Earth Data, including clean water, affordable energy, sustainable cities, climate change, life below water, life on land, good health, and peace. As an important part of Big Earth Data, remote sensing data obtained from spaceborne and airborne sensors are characterized by high spatial and spectral resolutions, which can improve the accuracy of land classification and land use change monitoring. Meanwhile, near real-time image processing of remote sensing data provides powerful decision support to quickly respond to emergencies (e.g. earthquakes, floods, and other natural disasters). Thus, remote sensing data have the potential to promote the development of Earth science research. 3.3. Challenges to Big Earth Data technologies Technologies related to Big Earth Data comprise Earth observation, communication technology, and computers, among others. With the recognition that Big Earth Data has deepened humankind’s capability of understanding Earth, it also becomes necessary to meet the challenges brought by transmitting, storing, processing, analyzing, managing, and sharing big geospatial data. The huge amount of Earth observation data combined with real-time or near real-time acquisition rates and multiple scales especially challenge the existing technology. With numerous longer term, cheaper sensors and more time-critical requirements for sharing their data, the more complex the storage, processing,

Figure 1. The development of scientific research paradigms (according to Hey, Tansley, and Tolle 2009).

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and analysis of these data are. This data flow requires advanced technical support that is more comprehensive than that for traditional technologies. To address these challenges, scientists are making efforts to develop computing platforms, algorithms, and software systems. These technologies include high-performance platforms, mass storage technology, comprehensive automation, efficient computing, data sharing, and service systems to make Big Earth Data manageable and valuable. However, there still exist bottlenecks to overcome in a series of key technologies. 3.3.1. Effectively store and manage the huge amount of geospatial data The data collected from Earth observation satellites contain rich information with high spatial, spectral, temporal, and radiometric resolution, which provide us with the capacity of comprehensive, multi-scale, and real-time dynamic monitoring of the planet. However, with heterogeneous data formats, multiple sources and various sensors, the huge amount of geospatial data challenge the physical and logical infrastructures to store, access, and manage data (Demchenko et al. 2012; Ma et al. 2015). How to efficiently store and manage massive data, quickly and concurrently read and write these data, and realize high scalability and high availability have become the primary tasks to address. In recent years, scalable and service-on-demand distributed storage technology and management systems have matured. As for geospatial big data, distributed storage and cloud storage technologies have proved to be commendable solutions for the storage of Big Earth Data (Guo et al. 2010; Lü et al. 2011; Li, Yao, and Shao 2014). Unlike traditional relational data storage formats, which are based on parallel, fixed, and limited architectures, distributed storage technology stores data on multiple standalone devices, and allocates resources through a distributed storage system to provide services to users. This technology is lower in cost and easier to operate, but is high in resource utilization. Cloud storage has been developed based on the concept of cloud computing, with storage environments built through clustering technology mapping thousands of physical storage devices into a large storage platform through network virtualization, working together cooperatively and productively. With distributed and cloud storage, users can store and manage geospatial data in cloud storage platforms anytime and anywhere to provide service-on-demand support for geospatial data processing and analysis. 3.3.2. Efficiently perform real-time processing and analysis Real-time or near real-time satellite monitoring means a constant flow of image data will be received and further processed for any application requirements of end users. With the increasing magnitude of geospatial data, spatial-statistical analysis and processing technology are bound to advance. Spatial division, multi-dimensional data structures, static and dynamic load balancing, multiple-iteration algorithms, and many other factors should be taken into account in response to the challenges that geospatial data bring. Currently, the mainstream spatial analysis and processing technologies are based on cloud computing, using virtualization to provide massive data storage services and resources via the Internet. With the support of cloud computing, users can access spatial information resources anytime and anywhere and conduct spatial analysis on demand, which highly enhances the analytical capabilities and processing capacity of huge geospatial data and provides new solutions for the problem of insufficient computing power in spatial data analysis and geoscience simulation. To meet the demands of real-time processing and analysis, efficient artificial intelligence processing methods are needed. From the point of view of computing, the breakthrough of geospatial big data analysis may lie in the transition from traditional machine learning and data mining technology to MapReduce/ Hadoop technologies (Cosulschi, Cuzzocrea, and De Virgilio 2013; Kim et al. 2014). With effective scalability and fault tolerance, MapReduce acts as a good parallel programming model to deal with big data. It facilitates different computing architectures, including multi-core clusters, clouds, Cubieboards, and graphic processing unit architectures (Jiang et al. 2015). It can also provide end users with analytical services (Zhao et al. 2014).

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3.3.3. Promote spatial and temporal analysis of multi-scale geospatial data Big Earth Data are characterized by multiple spatial and temporal scales. This is mainly caused by the multi-grade subsystems used in Earth observation. Each subsystem has its own spatio-temporal scale, so that the obtained Earth observation data have different spatio-temporal scales and different rules and characteristics at different scales. The complexity of the task of monitoring the Earth system spans local, regional, and global scales, and the temporal scale ranges from seconds to millennia. Integrating all these data into a system or platform in itself is a tough task, even without processing and analyzing them. The framework of Digital Earth research requires such multi-scale spatial and temporal data to meet different application requirements.

4. Big Earth Data benefits scientific research Big Earth Data provides new approaches for scientific research in many ways. In this section we look into the significant advancements benefitting from Big Earth Data using the examples of knowledge discovery, global change, and Digital Earth science. 4.1. Big Earth Data promotes knowledge discovery Big Earth Data helps people understand the planet with a new approach by mining information and discovering knowledge from big geospatial data. This process is not just simple information extraction, but more focused on the mining of implicit and non-obvious patterns, rules, and knowledge behind big data. Through this process, critical information as well as the correlation of each subsystem and various biophysical variables of Earth can be explored. Meanwhile, the great volume of geospatial data has shifted the process of knowledge discovery from ‘model-driven’ to ‘data-driven’. However, it is notable that efficient data mining with Big Earth Data is still in its infancy, but it is urgent for the development of the innovative theories and discovery methods related to Big Earth Data (Guo, Wang, and Liang 2016). To deal with the huge volume of Earth observation data, technologies for transferring, storing, managing, processing, computing, and sharing big geospatial data are needed. Hence, it has become a major scientific issue in the field of Earth science to develop the theory and methodology of knowledge discovery with Big Earth Data. 4.2. Big Earth Data supports global change research Global change has been regarded as a significant threat to sustainable development worldwide. To address multi-disciplinary issues at a global scale, global change research faces the hardest challenge of obtaining various data from the interacting subsystems of Earth and dealing with them (Chen 1999; Chen and van Genderen 2008). This makes it important to collect data from various elements of the Earth system through monitoring global change’s progress in large-scale, long-term time sequences, and conduct processing, analysis, and simulation accordingly. Big Earth Data provides a wide range of long-term sequences and multiple spatio-temporal scales covering all of Earth’s spheres, such as the atmosphere, hydrosphere, lithosphere, and biosphere. This is guaranteed by a space-air-ground integrated Earth observation system and a global quasireal-time and all-weather Earth data acquisition network. Through continuous and long-term monitoring of the Earth system, scientists are able to use advanced geospatial processing technologies to simulate and analyze Earth’s dynamic surface processes and to reveal the spatio-temporal change mechanisms. This is very helpful for stakeholders to formulate scientific strategies and take actions to respond to global change for sustainable development. In this sense, Big Earth Data provides strong support to strengthen the new approaches to global change research.

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Figure 2. The shift in understanding of the concept of Digital Earth.

4.3. New stage of Digital Earth: Big Earth Data In the new era of big data, Digital Earth aims to integrate massive amounts of multi-dimensional, multi-resolution, multi-temporal geospatial data and socioeconomic data as well as analysis algorithms and models in a framework of comprehensive analysis and application systems. Digital Earth is also devoted to sewing together the huge, valuable scientific data across disciplines, covering fields of not only the atmosphere, geography, geology, environment, and ecology, but also of information science, space science, cognitive science, and ones closely related to the humanities and social sciences. It is expected to describe, analyze, model, and predict the dynamic processes of the Earth system as well as the interaction between humans and the planet through analyzing such massive data (Guo et al. 2014). To address the challenges of Big Earth Data, Digital Earth systems should stick to synthesis and systematic observation of Earth, as well as data-intensive methods for studying Earth system models, thereby leading to increased knowledge discovery. Relying on national spatial infrastructures and high-speed Internet, Digital Earth systems can connect multiple satellites and geographical information centers to complete the acquisition, transmission, storage, processing, analysis, and distribution of spatial data. Big Earth Data will further generate more Digital Earth products, services, and applications. In this context, big geospatial data constitutes the basis and core of Digital Earth research. With new methods, technologies, and applications emerging, Digital Earth has evolved into a new connotation from the concept of ‘Putting Earth into the computer’ to ‘Big Earth Data’, a perspective influenced by big data (Figure 2). It could be proposed that, serving as a typical data-intensive research methodology and system in Earth science, Digital Earth was driven to advance to the new stage of Big Earth Data.

5. Conclusions With around 19 years of development, Digital Earth has evolved from the very original vision of representing the planet with several key technologies to a new stage in the context of big data. Digital Earth has proven to be a useful tool in assisting us to better understand the planet we live on, and to further help stakeholders take relevant actions to respond to the problems we face. Digital Earth provides a new vision and new methodology with prominent advantages for scientists to study the Earth system, especially in the era of big data.

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Although there are still many challenges to overcome in terms of relevant technologies, we are happy to see that Big Earth Data, as a data-intensive scientific approach, has raised worldwide attention and become a new opportunity and impetus to knowledge discovery in Earth science. Big Earth Data makes it possible to explore the correlations among multi-disciplinary data, and further discover new models, new rules, and new knowledge. The long sequence of multiple spatial and temporal scales of Earth observation data, the accurate, continuous ground station observations and experimental data, the scientific basis and theoretical speculations as well as relevant processing and analysis technologies will contribute to the advancement of Earth science research. We believe that as a successful example of big data in Earth science, Digital Earth will provide brand-new ideas for solving problems in Earth science research in the context of big data.

Disclosure statement No potential conflict of interest was reported by the authors.

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