Estimating chlorophyll a concentrations from remote-sensing reflectance in optically shallow waters

A multi-spectral classification and quantification technique is developed for estimating chlorophyll a concentrations, Chi, in shallow oceanic waters where light reflected by the bottom can contribute significantly to the above-water remote-sensing reflectance spectra, R, A Classification criteria for determining bottom reflectance contributions for shipboard R,().) data from the west Florida shelf and Bahamian waters (1998-2001; n=451) were established using the relationship between R-rs(412)/R-rs(670) and the spectral curvature about 555 run, [R,(412)*R-rs(670)]/R-rs(555)(2). Chlorophyll concentrations for data classified as optically deep and optically shallow were derived separately using best-fit cubic polynomial functions developed from the band-ratios R-rs(490)/R-rs(555) and R-rs(412)/R-rs(670), respectively. Concentrations for transitional data were calculated from weighted averages of the two derived values. The root-mean-square error (RMSE(log)10) calculated for the entire data set using the new technique was 14% lower than the lowest error derived using the best individual band-ratio. The standard blue-to-green, band-ratio algorithm yields a 26% higher RMSE(log)10 than that calculated using the new method. This study demonstrates the potential of quantifying chlorophyll a concentrations more accurately from multi-spectral satellite ocean color data in oceanic regions containing optically shallow waters. (c) 2006 Elsevier Inc. All rights reserved.