IEEE - Institute of Electrical and Electronics Engineers
Abstract
International audienceAn unsupervised classification method is developed for the coarse segmentation of Moroccan coastal upwelling using the Sea Surface Temperature (SST) satellite images. The algorithm is started with the generation of c-partitioned labeled image using Otsu's method for the purpose of finding regions of homogenous temperatures. Then two well-known validity indices are used to select the c-partition which best reproduce the shape of upwelling area. A region-growing algorithm is developed that is used to remove the noisy structures in the offshore waters not belonging to the upwelling area. The algorithm is used to provide a seasonal variability of upwelling activity in the southern Moroccan Atlantic coast using 70 SST images of the years 2007 and 2008. The performance of the proposed methodology has been validated by an oceanographer, showing its effectiveness for automatic delimitation of Moroccan upwelling region