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Ocean Science An interactive open-access journal of the European Geosciences Union
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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 20 Mar 2019

Submitted as: research article | 20 Mar 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Ocean Science (OS).

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

Khalil Yala1, Ndeye Niang2, Julien Brajard1, Carlos Mejia1, Mory Ouattara2, Roy El Hourany1, Michel Crépon1, and Sylvie Thiria1,3 Khalil Yala et al.
  • 1IPSL/LOCEAN, Sorbonne Université (Université Paris6, CNRS, IRD, MNHN), 4 Place Jussieu, 75005 Paris, France
  • 2CEDRIC, CNAM, 292 rue Saint Martin, 75003 Paris, France
  • 3UVSQ, F-78035, Versailles, France

Abstract. We processed daily ocean-color satellite observations to construct a monthly climatology of phytoplankton pigment concentrations in the Senegalo-Mauritanian region. Thanks to the difficulty of the problem, we proposed a new method. It primarily consists in associating, in well-identified clusters, similar pixels in terms of ocean-color parameters and in situ pigment concentrations taken from a global ocean database. The association is carried using a new Self Organized Map (2S-SOM). Its major advantage is to allow taking into account the specificity of the optical properties of the water by adding specific weights to the different ocean color parameters and the in situ measurements. In the retrieval phase, the pigment concentration of a pixel is estimated by taking the pigment concentration values associated with the 2S-SOM cluster presenting the ocean-color satellite spectral measurements, which are the closest to those of the pixel under study according to some distance. The method was validated by using a cross-validation procedure. We focused our study on the fucoxanthin concentration, which is related to the abundance of diatoms. We showed that the fucoxanthin starts to develop in December, presents its maximum intensity in March when the upwelling intensity is maximum, extends up to the coast of Guinea in April and begins to decrease in May. The results are in agreement with previous observations and recent in situ measurements. The method is very general and can be applied in every oceanic region.

Khalil Yala et al.
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Khalil Yala et al.
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Short summary
We retrieved the major pigment concentrations of phytoplankton from satellite ocean color multi-spectral sensors in the Senegalo-Mauritanian upwelling, which is one of the most productive upwelling system with strong economic impacts on fisheries in Senegal and Mauritania. We processed the satellite data with a neural network classifier. This research was done through a fruitful cooperation between statisticians, specialists of neural Networks and oceanographers.
We retrieved the major pigment concentrations of phytoplankton from satellite ocean color...