Articles | Volume 16, issue 2
Ocean Sci., 16, 513–533, 2020
https://doi.org/10.5194/os-16-513-2020
Ocean Sci., 16, 513–533, 2020
https://doi.org/10.5194/os-16-513-2020

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.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Anna Mirena Feist-Polner on behalf of the Authors (09 Jan 2020)  Author's response
ED: Referee Nomination & Report Request started (23 Jan 2020) by Oliver Zielinski
RR by Anonymous Referee #2 (28 Jan 2020)
RR by Yangyang Liu (05 Feb 2020)
ED: Publish subject to technical corrections (18 Feb 2020) by Oliver Zielinski
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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.