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Automatic detection of Moroccan coastal upwelling from chlorophyll-a concentration images using the Expectation-Maximization method

Domaine:

environment and energygeospatial

Type de record:

paper
Créateur:
BelElaMin
Éditeur:
Uni
Éditeur:
CCSDIEEE
Hôte:avatar
International audience The inshore water along the Atlantic coast of Morocco is part of one of the four major upwelling systems in the world. This region is characterized by the presence of upwelling activity almost all years around. In this work, we propose an unsupervised algorithm for identifying and extracting automatically this vital zone using the satellite observation of chlorophyll-a concentration (CHL-a). In fact, the approach is started with the application of Expectation-Maximisation algorithm for detecting the nutrient-rich region over CHL-a image. Then, a regiongrowing algorithm is applied to remove the noisy structures appeared in the offshore waters not belonging to the upwelling region. The proposed methodology is tested over a database of 230 weekly CHL-a images spanning the period from the years 2016 to 2020. The results show that the proposed method seems to be applicable for any other ecosystem.

Visit

hal.science

Tags

chlorophyll-a indexMoroccan upwellingChlorophyll-a concentrationRegion-growingExpectation-MaximisationExpectation-Maximisation Region-growing Chlorophyll-a concentration Moroccan upwelling chlorophyll-a index[INFO]Computer Science [cs]

Licenses

https://about.hal.science/hal-authorisation-v1/info:eu-repo/semantics/OpenAccess

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