Retrieval of gelbstoff absorption coefficient in pearl river estuary using remotely-sensed ocean color data

Abstract

Gelbstoff is the main absorber in natural waters of UV and visible light, and has an increasing absorption with decreasing wavelength in the range between 700 and 350 nm. Gelbstoff is often an important source of interference in the determination of plant pigments (e.g., Chlorophyll a) in coastal waters using remotely- sensed ocean color data. The existence of gelbstoff will affect the transfer of radiance in the water column, and then affect the depth of euphotic layer and photosynthesis. Many biogeochemical processes in the ocean, including trace metal complexation, are influenced by the presence of gelbstoff. Accurate estimates of gelbstoff concentrations in the ocean are critical not only to sea-land interaction studies, but also to biogeochemical and ecological studies. In this study in-situ data of the absorption coefficient of gelbstoff (Ag) and remote sensing reflectance (Rrs) in the Pearl River estuary were collected at 36 stations from 2 cruises conducted in 25-26 January 2003 and 5-6 January 2004 respectively. The Pearl River Estuary is the largest estuarine system in the South China Sea (SCS) region with eight discharge mouths of the river system and dynamic water mixing processes. The in-situ remote sensing reflectance data were calculated into 6 bands responding to the wavelength ranges of SeaWiFS band 1 to band 6 (412 to 670 nm). The relationships of the measured Ag to 240 band combinations to measured Rrs were analyzed, and the band combination with highest correlation coefficients with Ag was used for algorithm development. A local algorithm for retrieval of gelbstoff absorption coefficient was developed and applied to estimate gelbstoff absorption coefficient from atmospheric corrected SeaWiFS data. The accuracy of remotely-sensed retrieval of gelbstoff was evaluated by comparison to the measured data. The spatial distribution of gelbstoff absorption coefficient in the Pearl River estuary waters was revealed by thematic images retrieved from SeaWiFS data. © 2005 IEEE.