Integrating ICESat-2 and Sentinel-3 Data for Comprehensive Klidar Retrieval: Case-I Water

The continuous demand for coastal zone resource exploitation and marine ecosystem protection challenges satellite remote sensing observation of shallow sea apparent optical properties. The existing satellite retrieval method of the light detection and ranging (LiDAR) attenuation coefficient ( $K_{\mathrm {lidar}}$ ) relies on water column photons, so it cannot achieve accurate water quality measurements in shallow water depths. In this study, the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) data were innovatively fused with Sentinel-3 image to retrieve comprehensive $K_{\mathrm {lidar}}$ . First, $K_{\mathrm {lidar}}$ is calculated in offshore areas using ICESat-2 water column photons and in nearshore areas using seafloor photons. ICESat-2-derived $K_{\mathrm {lidar}}$ was then integrated with Sentinel-3 image, employing Bayesian-optimized CatBoost (BO-CatBoost) to invert the spatial distribution of both offshore and nearshore areas. Finally, the retrieval results’ weights were assigned based on Sentinel-3’s band ratio, yielding comprehensive $K_{\mathrm {lidar}}$ results for the shallow seas. The proposed method successfully obtained an accurate spatial distribution of $K_{\mathrm {lidar}}$ in Passu Keah, Culebra, and Marquesas Keys. The results show that the coefficient of determination ( $R^{2}$ ), mean relative error (MRE), and mean absolute error (MAE) for the three study areas range from 0.7402 to 0.8557, 0.0405 to $0.0885~\mathrm {m}^{-1}$ , and 0.0033 to $0.0055~\mathrm {m}^{-1}$ , respectively. The root mean square error (RMSE) ranges from 0.0043 to $0.0077~\mathrm {m}^{-1}$ . It has higher reliability than Sentinel-3’s $K_{d}{(}532{)}$ . As satellite remote sensing improves, the method will efficiently map the LiDAR attenuation coefficient across vast areas, offering reliable data for resource development, water quality, and ecosystem conservation.