Journal
REMOTE SENSING
Volume 10, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/rs10040498
Keywords
phytoplankton functional types (PFT); ocean color; modified PHYSAT method; empirical orthogonal functions (EOF); coastal upwelling waters
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Funding
- National Fund for Scientific and Technological Development of Chile (FONDECYT projects) [11130463, 1151299]
- IMO-Chile
- Coastal and Marine Research Institute (INVEMAR) of Colombia [COLCIENCIAS-INVEMAR FP44842-499-2014]
- Administrative Department of Science, Technology and Innovation (COLCIENCIAS) of Colombia [COLCIENCIAS-INVEMAR FP44842-499-2014]
- Fondo Nacional de Financiamiento para la Ciencia, la Tecnologia y la Innovacion Francisco Jose de Caldas
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An approach that improves the spectral-based PHYSAT method for identifying phytoplankton functional types (PFT) in satellite ocean-color imagery is developed and applied to one study case. This new approach, called PHYSTWO, relies on the assumption that the dominant effect of chlorophyll-a (Chl-a) in the normalized water-leaving radiance (nLw) spectrum can be effectively isolated from the signal of accessory pigment biomarkers of different PFT by using Empirical Orthogonal Function (EOF) decomposition. PHYSTWO operates in the dimensionless plane composed by the first two EOF modes generated through the decomposition of a space-nLw matrix at seven wavelengths (412, 443, 469, 488, 531, 547, and 555 nm). PFT determination is performed using orthogonal models derived from the acceptable ranges of anomalies proposed by PHYSAT but adjusted with the available regional and global data. In applying PHYSTWO to study phytoplankton community structures in the coastal upwelling system off central Chile, we find that this method increases the accuracy of PFT identification, extends the application of this tool to waters with high Chl-a concentration, and significantly decreases (-60%) the undetermined retrievals when compared with PHYSAT. The improved accuracy of PHYSTWO and its applicability for the identification of new PFT are discussed.
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