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 (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 730nm, and the NIR-red two-band model (with bands around 665 and 700nm) 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.
- remote sensing
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Environmental Science(all)
- Public Health, Environmental and Occupational Health