M. R. Anderberg, Cluster Analysis for Application, 1973.

H. Arefi, M. Hahn, and F. Samadzadegan, Comparison of clustering techniques applied to laser data, Geo-imagery Bridging continents xx-th ISPRS congress, 2004.

E. Backer and A. K. Jain, A clustering performance measure based on fuzzy set decomposition. Pattern Analysis and Machine Intelligence, IEEE Transactions, issue.31, pp.66-75, 1981.

C. James and . Bezdek, Pattern Recognition with Fuzzy Objective Function Algorithms, 1981.

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

J. F. Cayula and P. Cornillon, Edge Detection Algorithm for SST Images, Journal of Atmospheric and Oceanic Technology, vol.9, issue.1, pp.67-80, 1992.
DOI : 10.1175/1520-0426(1992)009<0067:EDAFSI>2.0.CO;2

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 neuralnetwork framework, IEEE International Geoscience Remote Sensing Symposium, vol.II, pp.926-929, 2008.

P. A. Devijver and J. Kittler, Pattern Recognition: A Statistical Approach, 1982.

D. Dubois and H. Prade, in fuzzy sets and possibility theory: Recent developments, r. r. yager, ed. new york: Pergamon. A unifying view of comparison indices in a fuzzy set-theoretic framework, pp.3-13, 1982.

H. Frigui and R. Krishnapuram, A robust algorithm for automatic extraction of an unknown number of clusters from noisy data, Pattern Recognition Letters, vol.17, issue.12, pp.1223-1232, 1996.
DOI : 10.1016/0167-8655(96)00080-3

P. Vicente, C. Guerrero-bote, F. Lopez-pujalte, V. De-moya-anegon, and . Herrero-solana, Comparison of neural models for document clustering, International Journal of Approximate Reasoning, vol.34, issue.23, pp.287-305, 2003.

J. A. Hartigan, Classification and Clustering, Journal of Marketing Research, vol.18, issue.4, 1975.
DOI : 10.2307/3151350

R. J. Holyer and S. H. Peckinpaugh, Edge detection applied to satellite imagery of the oceans, IEEE Transactions on Geoscience and Remote Sensing, vol.27, issue.1, pp.46-56, 1989.
DOI : 10.1109/36.20274

U. Kaymak and M. Setnes, Fuzzy clustering with volume prototypes and adaptive cluster merging. Fuzzy Systems, IEEE Transactions on, vol.10, issue.6, pp.705-712, 2002.

J. Leski, Towards a robust fuzzy clustering. Fuzzy Sets and Systems, pp.215-233, 2003.

A. Likas, N. Vlassis, J. Verbeek, ]. K. Nieto, H. Demarcq et al., The global k-means clustering algorithm (technical report) Computer Science Institute, University of Amsterdam, The Netherlands. ISA-UVA-01-02 Mesoscale frontal structures in the canary upwelling system: New front and filament detection algorithms applied to spatial and temporal patterns, Rem. Sens. Environ, vol.123, pp.339-346, 2001.

L. L. Stowe, P. A. Davis, and E. Paul-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.