Terrain slope adaptive registration and positioning accuracy improvement based on spaceborne photon point clouds and images

doi:10.13474/j.cnki.11-2246.2026.0713

Abstract

Abstract: [Purposes] Spaceborne photon-counting LiDAR systems,exemplified by ICESat-2,can directly acquire high-precision 3D information about the Earth's surface.This data serves as a novel type of control information for enhancing the 3D geolocation accuracy of satellite imagery.This study proposes a large-area block adjustment method based on topographic slope adaptive generalized iterative closest point (TSA-GICP)registration. [Methods] A strategy is designed involving global coarse registration followed by local TSA-GICP fine registration between linearly distributed spaceborne photon point clouds and digital surface models (DSMs)generated from satellite imagery.A 3D feature detection algorithm is employed to extract common feature points from the two types of heterogeneous point cloud data,enabling the automatic screening and generation of photon control points (PCPs)that are uniformly distributed,moderate in quantity,and reliable in quality.A joint block adjustment scheme incorporating an additional parameter-based rational function model (RFM)is implemented. [Findings] Compared to uncontrolled positioning and positioning assisted by Google imagery and SRTM DEM,the planimetric accuracy of ZY-3 imagery improved from 10.445 and 3.695 m to 3.058 m,and the vertical accuracy improved from 9.916 and 2.796 m to 1.821 m.Compared to Google imagery and SRTM DEM-assisted positioning,the planimetric and vertical accuracies improved by 17.24% and 34.87%,respectively.For BJ-3 imagery,planimetric accuracy improved from 6.477 and 3.879 m to 2.703 m,and vertical accuracy improved from 5.714 and 2.226 m to 0.793 m.Compared to Google imagery and SRTM DEM-assisted positioning,the planimetric and vertical accuracies improved by 30.32%and 64.38%,respectively. [Conclusions] The proposed method effectively enhances the 3D geolocation accuracy of satellite imagery,providing a feasible technical reference for improving global mapping accuracy.

Key words: spaceborne photon control point, satellite stereo imagery, topographic slope adaptation, generalized iterative closest point registration, automatic screening

CLC Number:

P237

Wang Fan, Fang Yong. Terrain slope adaptive registration and positioning accuracy improvement based on spaceborne photon point clouds and images[J]. Bulletin of Surveying and Mapping, 2026, 0(7): 88-95,117.

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URL: http://tb.chinasmp.com/EN/10.13474/j.cnki.11-2246.2026.0713

http://tb.chinasmp.com/EN/Y2026/V0/I7/88

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