Atmospheric correction based on the optimal solution of aerosol mix ratio: A case study for Pearl River Estuary

Abstract

Abstract In ocean color remote sensing, the presence of absorbing aerosols and turbid waters will lead to increased errors in atmospheric correction (AC) for coastal regions. In order to reduce these errors, an alternative AC algorithm has been proposed based on the in situ measurements of the Pearl River Estuary (PRE) and the candidate aerosol models including continental, maritime, and absorbing urban aerosols. The new AC algorithm optimally solved the equation set which is constructed by the multi-spectral relationships of remote sensing reflectance (Rrs ) and the aerosol reflectance of each aerosol model. The performances of the new AC were evaluated using the simulated dataset and the in situ Rrs . The results indicated that this algorithm can effectively reduce the overestimation of aerosol reflectance caused by absorbing aerosols, and can retrieve reasonable Rrs values in PRE.