A New Model to Retrieve Phytoplankton Information From Remote Sensing Signals

Abstract

Abstract The main objective of this study is to improve the retrieval of phytoplankton absorption coefficients using ocean and land color instrument (OLCI) bands (413, 443, 490, 510, 560, and 665 nm). In this study, the Raman-scattering correction was considered in an analytical forward model, and the corresponding Raman excitation OLCI band centers were calculated. The coefficients and exponents for the power law model of phytoplankton absorption were determined by a neural network classifier using a combination of sun elevation, photosynthetically active radiation, and remote sensing reflectance at OLCI bands (413, 443, 490, 510, 560, 620, 665, and 683 nm). Two optimizations were executed. The shape of the colored detrital matter (CDM) spectrum was allowed to change during the second optimization. Based on comparisons of the phytoplankton absorption coefficients at 443 nm (a Φ[443]) predicted by the improved inversion with field measurements taken from cruise surveys of the Pearl River estuary and Daya Bay and the SeaWiFS Bio-optical Archive and Storage System dataset and NASA bio-Optical Marine Algorithm Dataset, the modified inversion procedure could provide a good performance (r 2 = 0.86). The results showed that the contribution of Raman scattering to the remote sensing reflectance at 665 nm exceeded 22% in the open ocean. Moreover, the residual from the first optimization was compared with that from the second optimization, demonstrating that the variable CDM spectral slope in the analytical forward model could improve the accuracy of the forward model.