On Detectability of Moroccan Coastal Upwelling in Sea Surface Temperature Satellite Images

Ayoub Tamim 1, * Khalid Minaoui 2 Khalid Daoudi 3 Abderrahman Atillah 4 Driss Aboutajdine 5
* Auteur correspondant
1 LRIT
LRIT - Laboratoire de Recherche Informatique et Télécommunications
2 LRIT Associated Unit to the CNRST-URAC n◦ 29
LRIT - Laboratoire de Recherche Informatique et Télécommunications
3 GeoStat - Geometry and Statistics in acquisition data
Inria Bordeaux - Sud-Ouest
4 CRTS - Centre Royal de Télédétection Spatiale
5 GSCM-LRIT - Laboratoire de Recherche en Informatique et Télécommunications [Rabat]
Abstract : This work aims at automatically identify the upwelling areas in coastal ocean of Morocco using the Sea Surface Temperature (SST) satellite images. This has been done by using the fuzzy clustering technique. The proposed approach is started with the application of Gustafson-Kessel clustering algorithm in order to detect groups in each SST image with homogenous and non-overlapping temper-ature, resulting in a c-partitioned labeled image. Cluster validity indices are used to select the c-partition that best reproduces the shape of upwelling areas. An area opening technique is developed that is used to filter out the residuals noise and fine structures in offshore waters not belonging to the upwelling regions. The de-veloped algorithm is applied and adjusted over a database of 70 SST images from years 2007 and 2008, covering the southern part of Moroccan atlantic coast. The system was evaluated by an oceanographer and provided acceptable results for a wide variety of oceanographic conditions.
Keywords : Upwelling sea surface temperature fuzzy clustering Gustafson-Kessel clustering algorithm validity indices area opening
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Communication dans un congrès
10th International Symposium on Visual Computing, Dec 2014, Las Vegas, United States. Springer, LNCS, 〈http://www.isvc.net〉
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Ayoub Tamim, Khalid Minaoui, Khalid Daoudi, Abderrahman Atillah, Driss Aboutajdine. On Detectability of Moroccan Coastal Upwelling in Sea Surface Temperature Satellite Images. 10th International Symposium on Visual Computing, Dec 2014, Las Vegas, United States. Springer, LNCS, 〈http://www.isvc.net〉. 〈hal-01078678〉

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