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

Abstract

A multi-spectral classification and quantification technique is developed for estimating chlorophyll a concentrations, Chl, in shallow oceanic waters where light reflected by the bottom can contribute significantly to the above-water remote-sensing reflectance spectra, R rs( λ). Classification criteria for determining bottom reflectance contributions for shipboard R rs( λ) 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 nm, [ R rs(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 log10) 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 log10 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.