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Soppa, Mariana A.; Hirata, Takafumi; Silva, Brenner; Dinter, Tilman; Peeken, Ilka; Wiegmann, Sonja; Bracher, Astrid. |
Diatoms are the major marine primary producers on the global scale and, recently, several methods have been developed to retrieve their abundance or dominance from satellite remote sensing data. In this work, we highlight the importance of the Southern Ocean (SO) in developing a global algorithm for diatom using an Abundance Based Approach (ABA). A large global in situ data set of phytoplankton pigments was compiled, particularly with more samples collected in the SO. We revised the ABA to take account of the information on the penetration depth (Z(pd)) and to improve the relationship between diatoms and total chlorophyll-a (TChla). The results showed that there is a distinct relationship between diatoms and TChla in the SO, and a new global model... |
Tipo: Text |
Palavras-chave: Ocean colour; Phytoplankton functional types; Diatom; Remote sensing; Chlorophyll-a. |
Ano: 2014 |
URL: https://archimer.ifremer.fr/doc/00290/40075/39289.pdf |
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Navarro, Gabriel; Almaraz, Pablo; Caballero, Isabel; Vazquez, Agueda; Huertas, Isabel E.. |
During the last two decades, several satellite algorithms have been proposed to retrieve information about phytoplankton groups using ocean color data. One of these algorithms, the so-called PHYSAT-Med, was developed specifically for the Mediterranean Sea due to the optical peculiarities of this basin. The method allows the detection from ocean color images of the dominant Mediterranean phytoplankton groups, namely nanoeukaryotes, Prochlorococcus. Synechococcus, diatoms, coccolithophorids, and Phaeocystis-like phytoplankton. Here, we present a new version of PHYSAT-Med applied to the Ocean Colour Climate Change Initiative (OC-CCI) database. The OC-CCI database consists of a multi-sensor, global ocean-color product that merges observations from four... |
Tipo: Text |
Palavras-chave: PHYSAT-Med algorithm; OC-CCI database; Phytoplankton functional types; Mediterranean Sea; Wavelet analysis. |
Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00589/70148/68133.pdf |
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