monitoring of pacific islands' environment from the

MONITORING OF PACIFIC ISLANDS' ENVIRONMENT FROM THE MOUNTAIN TO THE CORAL REEFS UNDER MINING CONSTRAINTS : CASE STUDY OF THE GREAT SOUTH OF NEW CALEDONIA WITH PLEIADES VHR DATA Andreoli Rémi1, Marchand Cyril2, Nazha Folcher-Selmaoui3, Yesou Hervé4, Tinel Claire5, Fontannaz Delphine6 1

Bluecham SAS, 101 Promenade Roger Laroque, 98800 Nouméa, New Caledonia 2 IRD, 101 Promenade Roger Laroque, 98848, Nouméa, New Caledonia 3 PPME EA3325, Université de la Nouvelle-Calédonie, Nouméa, New Caledonia 4 SERTIT, Université de Strasbourg, 300 Bld Sébastien Brant BP10413 67412 IllkirchGraffenstaden, France 5 CNES, 18 Avenue Edouard Belin, 31 401 toulouse Cedex 9, France 1. INTRODUCTION New Caledonia is an archipelago in the south-west of the Pacific Ocean. It concentrates the main particularities of Pacific Island countries: islands surrounded by a lagoon closed by coral reefs and covered by typical vegetation; and they are exposed to littoral risk (hurricane, tsunami) as well as climate change and sea level rise [1]. In this way, New Caledonia lagoon and coral reef is a UNESCO world heritage since 2008; mangroves of the archipelago cover more than 30000 ha and are one of the first resources to local population. As the third producer of Nickel in the world, New Caledonia’s decision makers are facing the challenge to manage their natural resources (coral reefs, lagoon, mangroves and vegetation) under the constraints of Nickel mining. 2. MONITORING OF PACIFIC ISLANDS'ENVIRONMENT Remote sensing data from earth observation satellites constitutes one of the major sources of environmental information. During the last 40 years, the quality, precision, coverage and repetitiveness of the remote sensing data have been constantly improved. The Pleiade constellation offers since 2012 the ability to collect tri-stereoscopy mutlispectral data at 70 cm resolution. In the meantime, data analysis procedures and algorithms took the advantage of high resolution remote sensing data to provide new value added product. In this way, very high resolution remote sensing data make possible the recognition and mapping of the mangroves’s species [2], [3] and

[4]. Very high resolution remote sensing data are also used to set up coral reef resilience models [5]. And data mining procedure provide methodologies to analyse this amount of remote sensing data such as for erosion monitoring under mining constraints [6].

Figure 1 : Pleiade data acquired the 13th of July 2012. From west to east : mining harbor, factory and exploitation sites, coastal settlements and tribes, mangroves, UNESCO heritage lagoon. © CNES 2012, Distribution Astrium Services / Spot Image S.A., France, All rights reserved. Commercial use prohibited.

The potential of Pleiade data to provide valuable information to decision makers in New Caledonia is assess concerning the mangroves monitoring, soil erosion mapping and hurricane and tsunami vulnerability evaluation. In this way, a Pleiade tristereoscopic coverage were acquire the 13th of July 2012 (figure 1) and a second acquisition is scheduled over the cyclonic season 2012-2013. Combination of DSM, vegetation species maps, soils degradation monitoring, erosion processing, coral reef changes was performed exploiting Pleiade data over the Great South of New Caledonia. These information are currently analyzed performing data mining techniques and spatial cross comparison with exogenous data (figure 2 and figure 3).

Figure 2: DTM derived from om Pleiade Tri-stereoscopic Tri data [7].. Contains © CNES 2012, Distribution Astrium Services / Spot Image S.A., France, All rights reserved. Commercial use prohibited.

Figure 3: STL-maps maps from data mining methods develop to highlight highligh soil degradation processes according to time and location [6]. [6] this illustration shows ows the mining activities impacts on soils (1 to 6) and changes in the mangroves area and the lagoon.

3. ANALITYCS IN THE CLOUD Then, the key challenge is therefore to provide decision makers with the right information at the right time and in a user-friendly manner. Cloud computing technology allows the development of web based platforms which are able to connect to scattered databases to exploit data, perform scientifically-based data analysis and modeling processes. The QëhnelöTM platform, based on the environmental geospatial cloud computing concept, allows the combination of remote sensing data and spatial analysis with any other remote database to assess the environment under social and industrial constraints and monitor the risks in an all-in-one package for effective decisionmaking by non-specialists. 4. REFERENCES [1] N. Mimoura, "Vulnerability of island countries in the South Pacific to sea level rise and climate change", Clim Res Vol 12, pp137-143, 1999 [2] C. Marchand, T. Quiniou, R. Andreoli, "Dispositif de suivi de la mangrove en contexte minier, télédétection optique et radar et mesures in situ", CNRT Nickel et son environnement Final Report, 140p, Dec. 2012. [3] L. Wang, W.P. Sousa, P. Gong, "Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery". International Journal of Remote Sensing 25:5655-5668, 2004. [4] L. Wang, W.P. Sousa, P. Gong, G.S. Biging, "Comparison of IKONOS and QuickBird images for mapping mangroves species on the Caribbean coast of Panama". Remote sensing of environment 91:432440, 2004. [5] J. Scopélitis,, S. Andrefouët, and C. Largouët, "Modelling coral reef habitat trajectories: Evaluation of an integrated timed automata and remote sensing approach". Ecological Modelling 205, 59–80, 2007. [6] N. Méger, C. Rigotti, L. Guerguen, F. Lodge, C. Pothier, R. Andreoli, M. Datcu, "Normalized mutual information-based ranking of spatio-temporal localization maps", ESA-EUSC-JRC 2012 Image Information Mining conference, 2012. [7] A. Durand, R. Andreoli, C. Tinel, H. Yesou, "Multi-strip DSM generation with PleiadesHR data over a coastal and mountainous mining landscape", EARSeL Symposium 3-6 June 2013, Matera, Italy, 2013