The objective of this work is to estimate chlorophyll-a (chl-a) concentration in the Pearl River estuary in China. To test the performance of algorithms for the estimation of the chl-a concentration in these productive turbid waters, the maximum band ratio (MBR) and near-infrared–red (NIR–red) models are used in this study. Specific focus is placed on (a) comparing the ability of the models to estimate chl-a in the range 1–12 mg m − 3 , which is typical for coastal and estuarine waters, and (b) assessing the potential of the Moderate Resolution Imaging Spectrometer (MODIS) and Medium Resolution Imaging Spectrometer (MERIS) to estimate chl-a concentrations. Reflectance spectra and water samples were collected at 13 stations with chl-a ranging from 0.83 to 11.8 mg m − 3 and total suspended matter from 9.9 to 21.5 g m − 3 . A close relationship was found between chl-a concentration and total suspended matter concentration with the determining coefficient ( R 2 ) above 0.89. The MBR calculated in the spectral bands of MODIS proved to be a good proxy for chl-a concentration ( R 2 > 0.93). On the other hand, both the NIR–red three-band model, with wavebands around 665, 700, and 730 nm, and the NIR–red two-band model (with bands around 665 and 700 nm) explained more than 95% of the chl-a variation, and we were able to estimate chl-a concentrations with a root mean square error below 1 mg m − 3 . The two- and three-band NIR–red models with MERIS spectral bands accounted for 93% of the chl-a variation. These findings imply that the extensive database of MODIS and MERIS images could be used to quantitatively monitor chl-a in the Pearl River estuary.
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Zhang et al. (2011) studied this question.
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