Remote-sensing estimation of water quality in estuarine and coastal waters: A case study


In this study, we applied the in-situ and remote-sensing data to the Pearl River estuarine and coastal waters in the north of South China Sea. 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 (R2) above 0.89. The MBR calculated in the spectral bands of MODIS proved to be a good proxy for chl-a concentration (R2 > 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. We also applied Landsat-8 OLI data to estimate suspended matter in the same area. These findings imply that the extensive database of MODIS, MERIS, and Landsat images could be used to quantitatively monitor chl-a and suspended matter in estuarine and coastal waters.