A. Atillah, A. Orbi, K. Hilmi, and A. Mangin, Produits opérationnels d'océanographie spatiale pour le suivi et l'analyse du phénomène d'upwelling marocain, Geo-Observateur, vol.14, pp.49-62, 2005.

A. Bakun, Fronts and eddies as key structures in the habitat of marine fish larvae: opportunity, adaptive response and competitive advantage, Scientia Marina, vol.70, issue.S2, pp.105-122, 2006.
DOI : 10.3989/scimar.2006.70s2105

G. L. Carl, A fuzzy clustering and fuzzy merging algorithm, 1999.

Y. Chang and X. Li, Adaptive image region-growing, IEEE Transactions on Image Processing, vol.3, issue.6, pp.868-872, 1994.
DOI : 10.1109/83.336259

E. Chassot, S. Bonhommeau, G. Reygondeau, K. Nieto, J. J. Polovina et al., Satellite remote sensing for an ecosystem approach to fisheries management, ICES Journal of Marine Science, vol.68, issue.4, pp.651-666, 2011.
DOI : 10.1093/icesjms/fsq195

URL : https://hal.archives-ouvertes.fr/ird-00576217

S. Chaudhari, R. Balasubramanian, and A. Gangopadhyay, Upwelling Detection in AVHRR Sea Surface Temperature (SST) Images using Neural-Network Framework, IGARSS 2008, 2008 IEEE International Geoscience and Remote Sensing Symposium, pp.926-929, 2008.
DOI : 10.1109/IGARSS.2008.4779875

D. L. Davies and D. W. Bouldin, A cluster separation measure. Pattern Analysis and Machine Intelligence, IEEE Transactions on PAMI, vol.1, issue.2, pp.224-227, 1979.

J. C. Dunn, A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters, Journal of Cybernetics, vol.3, issue.3, pp.32-57, 1973.
DOI : 10.1080/01969727308546046

K. Fukunage, Introduction to statistical pattern recognition, pp.260-267, 1972.

B. N. Holben, Characteristics of maximum-value composite images from temporal AVHRR data, International Journal of Remote Sensing, vol.7, issue.11, pp.1417-1434, 1986.
DOI : 10.1016/0034-4257(83)90053-6

A. K. Jain and R. C. Dubes, Algorithms for Clustering Data, 1988.

S. Nascimento, P. Franco, F. Sousa, J. Dias, and F. Neves, Automated computational delimitation of SST upwelling areas using fuzzy clustering, Computers & Geosciences, vol.43, pp.207-216, 2012.
DOI : 10.1016/j.cageo.2011.10.025

K. Nieto, H. Demarcq, and S. Mcclatchie, Mesoscale frontal structures in the Canary Upwelling System: New front and filament detection algorithms applied to spatial and temporal patterns, Remote Sensing of Environment, vol.123, issue.0, pp.339-346, 2012.
DOI : 10.1016/j.rse.2012.03.028

L. Nykjaer, L. Van-camp, K. Hilmi, and A. Mangin, Interannual variability of upwelling indices along the northwest african coast, pp.176-179, 1992.

N. Otsu, A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol.9, issue.1, pp.62-66, 1979.
DOI : 10.1109/TSMC.1979.4310076

M. K. Pakhira, S. Bandyopadhyay, and U. Maulik, Validity index for crisp and fuzzy clusters, Pattern Recognition, vol.37, issue.3, pp.487-501, 2004.
DOI : 10.1016/j.patcog.2003.06.005

F. M. Sousa, S. Nascimento, H. Casimiro, and D. Boutov, Identification of upwelling areas on sea surface temperature images using fuzzy clustering, Remote Sensing of Environment, vol.112, issue.6, pp.2817-2823, 2008.
DOI : 10.1016/j.rse.2008.01.014

L. L. Stowe, P. A. Davis, and E. P. Mcclain, Scientific Basis and Initial Evaluation of the CLAVR-1 Global Clear/Cloud Classification Algorithm for the Advanced Very High Resolution Radiometer, Journal of Atmospheric and Oceanic Technology, vol.16, issue.6, p.16656, 1999.
DOI : 10.1175/1520-0426(1999)016<0656:SBAIEO>2.0.CO;2

A. Tamim, K. Minaoui, K. Daoudi, H. Yahia, A. Atillah et al., A simple and efficient approach for coarse segmentation of Moroccan coastal upwelling, Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European, pp.1-5, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00850445

W. Wang and Y. Zhang, On fuzzy cluster validity indices. Fuzzy Sets and Systems, pp.2095-2117, 2007.