Geometric Positioning Verification of Spaceborne Photon-Counting Lidar Data Based on Terrain Feature Identification

The horizontal positioning error in spaceborne photon point clouds seriously constrains their elevation accuracy. To improve data quality for enhanced performance in scientific applications, this study proposes a photon correction method based on terrain feature identification, specifically for the photon-counting spaceborne lidar. Unlike the conventional terrain matching method, this approach accurately determines the horizontal positions of photons within a small-range area by establishing a matching relationship between the laser elevation turning points and the surface boundary lines. The feasibility of this method was verified using the satellite laser altimetry simulation platform, and the horizontal correction accuracy can reach within 0.6 m. Subsequently, the experiments were conducted to verify the geometric positioning accuracy of ICESat-2 across different areas, leveraging high-precision digital surface models. The results indicate that the average horizontal accuracy of ICESat-2 was 3.81 m, and the elevation accuracy was better than 0.5 m.