Paper
5 January 2001 Temporal and spatial variability of chlorophyll a, suspended solids, and yellow substance in the Yellow Sea and East China Sea using ocean color sensor
Motoaki Kishino, Akihiko Tanaka, Tomohiko Oishi, Roland Doerffer, Helmut Schiller
Author Affiliations +
Proceedings Volume 4154, Hyperspectral Remote Sensing of the Ocean; (2001) https://doi.org/10.1117/12.411673
Event: Second International Asia-Pacific Symposium on Remote Sensing of the Atmosphere, Environment, and Space, 2000, Sendai, Japan
Abstract
An inverse modeling has a possibility to retrieve the concentration of water constituents, such as chlorophyll (alpha) (Chl-(alpha) ), suspended matter (SS) and yellow substance (CDOM), in case 2 water from remotely sensed data. It turned out to be useful for mass processing of satellite data. Standard approach for inversion of radiative transfer needs long computation time, because iteration procedure is essential. On the other hand, Neural Network (NN) method is able to overcome this problem since it is consider to be a kind of non-linear multiple regression method, so that it is possible to retrieve the concentration of multiple water constituents by NN. The NN Method was applied to OCTS (Ocean Color and Temperature Scanner) data in the Yellow Sea and East China Sea to retrieve of chlorophyll a concentration, in organic suspended solids and yellow substances. The large mount of suspended Solids the Yellow Sea and the East China Sea were supplied from the Yellow River (Wei He) and the Yangtze River (Chang Jiang). The temporal and spatial distributions of chlorophyll (alpha) , inorganic mineral suspension and yellow substance were analyzed.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Motoaki Kishino, Akihiko Tanaka, Tomohiko Oishi, Roland Doerffer, and Helmut Schiller "Temporal and spatial variability of chlorophyll a, suspended solids, and yellow substance in the Yellow Sea and East China Sea using ocean color sensor", Proc. SPIE 4154, Hyperspectral Remote Sensing of the Ocean, (5 January 2001); https://doi.org/10.1117/12.411673
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Cited by 2 scholarly publications.
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KEYWORDS
Atmospheric modeling

Data modeling

Atmospheric optics

Optical coherence tomography

Solids

Ocean optics

Radiative transfer

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