A Novel Atmospheric Correction for Turbid Water Remote Sensing - Dian Wang; Xiangyu Xiang; Ronghua Ma; Yongqin Guo; Wangyuan Zhu; Zhihao Wu (Remote Sensing, 2023)
For the remote sensing of turbid waters, the atmospheric correction (AC) is a key issue. The “black pixel” assumption helps to solve the AC for turbid waters. It has proved to be inaccurate to regard all water pixels in the SWIR (Short Wave Infrared) band as black pixels. It is necessary to perform atmospheric correction in the visible bands after removing the radiation contributions of water in the SWIR band. Here, the modified ACZI (m-ACZI) algorithm was developed. The m-ACZI assumes the spatial homogeneity of aerosol types and employs the BPI (Black Pixel Index) and PIFs (Pseudo-Invariant Features) to identify the “black pixel”. Then, the radiation contributions of waters in the SWIR band are removed to complete the atmospheric correction for turbid waters. The results showed that the m-ACZI had better performance than the SeaDAS (SeaWiFS Data Analysis System) -SWIR and the EXP (exponential extrapolation) algorithm in the visible band (sMAPE < 30.71%, RMSE < 0.0111 sr−1) and is similar to the DSF (Dark Spectrum Fitting) algorithm in floating algae waters. The m-ACZI algorithm is suitable for turbid inland waters.