NDLI: Remote estimation of chlorophyll concentration in productive waters : Principals , algorithm development and validation

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Remote estimation of chlorophyll concentration in productive waters : Principals , algorithm development and validation

Content Provider	Semantic Scholar
Author	Gitelson, Anatoly A. Yacobi, Yosef Z. Rundquist, Donald C. Stark, Rainer Han, Long-Xi Etzion, Dror
Copyright Year	2000
Abstract	Most of the information pertaining to remote sensing of phytoplankton was developed for oligotrophic waters, where detritus and inorganic particles are scarce or their concentrations correlate with phytoplankton density. In our study we concentrated on inland and productive coastal waters, with the initial work done in Lake Kinneret, Israel. The primary objectives were: (1) to study the spectral features of reflectance of different water bodies during different seasons of the year, in order to find spectral features which are closely related to phytoplankton density; and, (2) to devise and validate algorithms for chlorophyll estimation using reflectance data as the measured variables. We found that the information gained from several spectral bands in the red and near-infra-red ranges of the spectrum were sufficient for the construction of algorithms for phytoplankton density estimation. These algorithms were validated in Lake Kinneret, as well as in other environments, with slight modification of the coefficients: the polluted water of Haifa Bay (Mediterranean Sea), fish ponds and wastewater reservoirs in Israel, and lakes with diverse trophic status in northwestern Iowa and eastern Nebraska (USA). Within the context of information essential for the estimation of chlorophyll concentration by remotely operated instruments, we discuss the requirements for satellite sensors to make them expedient tools for monitoring quality of productive aquatic ecosystems.
File Format	PDF HTM / HTML
Alternate Webpage(s)	https://acwi.gov/monitoring/nwqmc.org/2000proceeding/papers/pap_gitelson.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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