Articles | Volume 16, issue 2
Ocean Sci., 16, 513–533, 2020
Ocean Sci., 16, 513–533, 2020

Research article 24 Apr 2020

Research article | 24 Apr 2020

Estimation of phytoplankton pigments from ocean-color satellite observations in the Senegalo–Mauritanian region by using an advanced neural classifier

Khalil Yala et al.

Data sets

Retrieving aerosol characteristics and sea-surface chlorophyll from satellite ocean color multi-spectral sensors using a neural-variational method D. Diouf, A. Niang, J. Brajard, M. Crepon, and S. Thiria

Short summary
The paper is a contribution to the study of phytoplankton pigment climatology from satellite ocean-color observations in the Senegalo–Mauritanian upwelling, which is a very productive region where in situ observations are lacking. We processed the satellite data with an efficient new neural network classifier. We were able to provide the climatological cycle of diatoms. This study may have an economic impact on fisheries thanks to better knowledge of phytoplankton dynamics.