Role of Visible Spectroscopy in Bio-Optical Characterization of Coastal Waters

Ocean color remote sensing deals with the modulation of incident light by bio-optically active constituents present in the water column through the process of absorption and backscattering. The challenging task is to find out different approaches for exploiting water-leaving radiance measured from ocean color sensors to infer the absorption, scattering properties, and thereby concentrations of the bio-optical constituents present in different water types. In last few decades, these studies were carried out based on multispectral bands from different ocean color sensors in open ocean waters. Initially, the derived concentrations of chlorophyll-a (chl-a) were primarily based on the formulation of empirical approaches using large database of in situ measured values. Further advancement involved the use of bio-optical models such as quasi-analytical (Lee-Morel) and Garver-Seigel-Maritorena (GSM), which showed marginal improvements over the empirical approaches in deriving chl-a concentrations for optically complex Case-2 waters. A major drawback in these bio-optical models was the use of a constant value for the slope of colored dissolved and detrital organic matter absorption (a
_cdm
). In this study, a semianalytical bio-optical model (ABOM) is presented to derive concentration of chl-a in optically complex waters using hyperspectral data. Herein, we show that by modeling the variability in the a
_cdm
slope, the large errors associated with chlorophyll estimation in optically complex waters can be reduced significantly. The model was tested on a data set collected from an optically complex Chilika lagoon situated in the northeastern region of India. Results of the analysis indicate a significant change in the estimation of chl-a (mg/m
³
) with an mean absolute percentage difference (MAPD) of 58% as compared to GSM (175%) and Lee-Morel (189%) bio-optical model when compared with the in situ measurements. This study reveals that the bio-optical models developed for global oceans needs to be regionally parametrized for optical constituents in complex water bodies to estimate chlorophyll concentration with reduced uncertainty.