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Phytoplankton Diversity in the Mediterranean Sea From Satellite Data Using Self-Organizing Maps ArchiMer
El Hourany, Roy; Abboud-abi Saab, Marie; Faour, Ghaleb; Mejia, Carlos; Crepon, Michel; Thiria, Sylvie.
We present a new method to identify phytoplankton functional types (PFTs) in the Mediterranean Sea from ocean color data (GlobColour data in the present study) and AVHRR sea surface temperature. The principle of the method is constituted by two very fine clustering algorithms, one mapping the relationship between the satellite data and the pigments and the other between the pigments and the PFTs. The clustering algorithms are constituted of two efficient self-organizing maps, which are neural network classifiers. We were able to identify and estimate the percentage of six PFTs: haptophytes, chlorophytes, cryptophytes, Synechococcus, Prochlorococcus, and diatoms. We found that these PFTs present a peculiar variability due to the complex physical and...
Tipo: Text Palavras-chave: Phytoplankton; Secondary phytoplankton pigments; Self-organizing maps; Classification; Mediterranean Sea; Remote sensing.
Ano: 2019 URL:
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