Remote Estimation of Chlorophyll-a in Inland Waters by a NIR-Red-Based Algorithm: Validation in Asian LakesReport as inadecuate




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1

Key Laboratory of Algal Biology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, Hubei, China

2

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China

3

Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki 305-8572, Japan





*

Author to whom correspondence should be addressed.



Abstract Satellite remote sensing is a highly useful tool for monitoring chlorophyll-a concentration Chl-a in water bodies. Remote sensing algorithms based on near-infrared-red NIR-red wavelengths have demonstrated great potential for retrieving Chl-a in inland waters. This study tested the performance of a recently developed NIR-red based algorithm, SAMO-LUT Semi-Analytical Model Optimizing and Look-Up Tables, using an extensive dataset collected from five Asian lakes. Results demonstrated that Chl-a retrieved by the SAMO-LUT algorithm was strongly correlated with measured Chl-a R2 = 0.94, and the root-mean-square error RMSE and normalized root-mean-square error NRMS were 8.9 mg∙m−3 and 72.6%, respectively. However, the SAMO-LUT algorithm yielded large errors for sites where Chl-a was less than 10 mg∙m−3 RMSE = 1.8 mg∙m−3 and NRMS = 217.9%. This was because differences in water-leaving radiances at the NIR-red wavelengths i.e., 665 nm, 705 nm and 754 nm used in the SAMO-LUT were too small due to low concentrations of water constituents. Using a blue-green algorithm OC4E instead of the SAMO-LUT for the waters with low constituent concentrations would have reduced the RMSE and NRMS to 1.0 mg∙m−3 and 16.0%, respectively. This indicates 1 the NIR-red algorithm does not work well when water constituent concentrations are relatively low; 2 different algorithms should be used in light of water constituent concentration; and thus 3 it is necessary to develop a classification method for selecting the appropriate algorithm. View Full-Text

Keywords: chlorophyll-a concentration; NIR-red algorithms; blue-green algorithms; Asian lakes; accuracy assessment chlorophyll-a concentration; NIR-red algorithms; blue-green algorithms; Asian lakes; accuracy assessment





Author: Gongliang Yu 1,3, Wei Yang 2,* , Bunkei Matsushita 3, Renhui Li 1, Yoichi Oyama 3 and Takehiko Fukushima 3

Source: http://mdpi.com/



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