A sliding window-based coastal bathymetric method for ICESat-2 photon-counting LiDAR data with variable photon density

Abstract

Coastal bathymetry is of great significance to the development and protection of islands and reefs. Traditional ship-based sonar bathymetry and airborne LiDAR (Light Detection and Ranging) bathymetry make it difficult to efficiently map the water depth of remote islands and reefs. Notably, the photon-counting LiDAR on board ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) has the capability of shallow water bathymetry. However, the photon data acquired by this instrument is contaminated with substantial noise of varying density. In this study, a sliding window-based coastal bathymetric method (SWCBM-Ph) is proposed for photon data with variable density. Experiments are carried out on six island coasts as an example, and the results show that the method is effective in extracting underwater terrain photons for bathymetry, with RMSE (Root Mean Square Error) of 0.60 m and 0.53 m on low- and high-density photon datasets separately within water depth of 30 m. Compared with existing bathymetry methods, the SWCBM-Ph is less affected by noise signals, and adapts to variations in photon density, including diversities between different datasets and within the same dataset. Therefore, the proposed method helps to improve the stability of spaceborne photon bathymetry for complex situations in coastal waters.