Abstract

A neural network is developed to retrieve chlorophyll a concentration from marine reflectance by use of the five visible spectral bands of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The network, dedicated to the western equatorial Pacific Ocean, is calibrated with synthetic data that vary in terms of atmospheric content, solar zenith angle, and secondary pigments. Pigment variability is based on in situ data collected in the study region and is introduced through nonlinear modeling of phytoplankton absorption as a function of chlorophyll a, b, and c and photosynthetic and photoprotectant carotenoids. Tests performed on simulated yet realistic data show that chlorophyll a retrievals are substantially improved by use of the neural network instead of classical algorithms, which are sensitive to spectrally uncorrelated effects. The methodology is general, i.e., is applicable to regions other than the western equatorial Pacific Ocean.

© 2004 Optical Society of America

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