Author(s): Palanisamy Shanmugam, YuHwan Ahn
There exists a large demand for an accurate atmospheric correction of satellite ocean colour data over highly turbid coastal waters, where the standard atmospheric correction (SAC) algorithms designed for open ocean water turn out to be unsuccessful because of eventual interference of elevated radiance from suspended materials and perhaps the shallow bottom with the corrections based on the two near-infrared bands at 765 and 865 nm in which the water-leaving radiances are discarded (or modelled) in order to estimate aerosol radiative properties and extrapolate these into the visible spectrum in the atmospheric correction of the imagery. Furthermore, in the presence of strongly absorbing aerosols (e.g. Asian dust and Sahara dust) the SAC algorithms often underestimate water-leaving radiance values in the violet and blue spectrum or completely fail to deliver the desired biogeochemical products for coastal regions. To make the satellite ocean colour data offer unrivaled utility in monitoring and quantifying the components of ecologically important coastal waters, this study presents a more realistic and cost-effective image-based atmospheric correction method to accurately retrieve water-leaving radiances and chlorophyll concentrations from SeaWiFS imagery in the presence of strongly absorbing aerosols over highly turbid Northwest Pacific coastal waters. This method is a modified version of the spectral shape matching method (SSMM) previously developed by Ahn and Shanmugam (2004 Korean J. Remote Sens. 20 289–305), re-treating the assumption of spatial homogeneity of the atmosphere using simple models for assessing the contributions of aerosol and molecular scattering. Because of the difficulties in making atmospheric measurements concurrently with each overpass of SeaWiFS the atmospheric diffuse transmittance values are dependent on a standard method with the SAC scheme designed for processing SeaWiFS ocean colour data. The new method is extensively tested under the presence of various atmospheric conditions using SeaWiFS imagery and the results are compared with in situ (ship-borne) measurements in highly turbid coastal waters of the Korean Southwest Sea (KSWS). Such comparison demonstrates the efficiency of SSMM in terms of removing the effects of strongly absorbing aerosols (Asian dust) and improving the accuracy of water-leaving radiance retrieval with an RMSE deviation of 0.076, in contrast with 0.326 for the SAC algorithm which masked most of the sediment-laden and aerosol-dominated coastal areas. Further comparison in the Yellow Sea waters representing a massive phytoplankton bloom on 27 March 2002 revealed that the SAC algorithm caused an excessive correction for the visible bands, with the 412 nm band being affected the most, leading to severe overestimation of chlorophyll concentrations in the bloom-contained waters. In contrast, the SSMM remained very effective in terms of reducing errors of both water-leaving radiance and chlorophyll concentration estimates.