Abstract:

We present here results supporting the use of Medium Resolution Imaging Spectrometer (MERIS)-based Near Infrared-Red algorithms for estimating chlorophyll-a (chl-a) concentration in complex coastal waters. The objective of the study was to test the potential of universal applicability of NIR-Red algorithms, calibrated with (a) radiometric measurements and in situ data from inland waters in Nebraska, (b) MERIS data, acquired over Azov Sea in Russia, and (c) data synthetically generated using a radiative transfer model, to estimate chl-α concentration in the Hudson/Raritan Estuary of New York/New Jersey. We used a set of in situ reflectance and water samples collected in the Hudson/Raritan Estuary of New York/New Jersey for this validation. The NIR-Red algorithms produced consistently accurate estimates of chl-α concentration, ranging from 3.9 mg m^-3 to 26.3 mg m³, with the root mean square error (RMSE) below 2 mg m^-3. The algorithms do not need re-parameterization and it presents a strong case for the use of NIR-Red algorithms for real-time quantitative monitoring of Hudson/Raritan Estuary, and potentially other inland and coastal waters.