Airborne LiDAR Strip Error Correction and Deformation Monitoring

Airborne light detection and ranging (LiDAR) is a fast ground observation technology that can obtain point cloud data with centimeter precision in height and centimeter resolution in spatial domain, which has been widely applied to construct digital element model (DEM). However, there are still limitations in deformation monitoring, especially in large-scale and high-precision surface deformation monitoring. Namely, when the deformation magnitude is close to the LiDAR monitoring accuracy, the difference results contain obvious strip errors. To solve this problem, a strip error correction method based on the differential results is proposed for airborne LiDAR deformation monitoring including three main steps: quasi-stable adjustment on elevation correction, fixed-axis iterative closest point (ICP), and affine ICP algorithm to correct the strip errors. Experiments show that the proposed method can correct the strip error, and the RMSE of the two-phase point clouds for one flight track was decreased from the original 6.2 and 5.3 cm to 3.5 and 3.3 cm. Deformation patterns and rates are consistent as verified by external results with the small baseline subset InSAR (SBAS-InSAR) of Sentinel-1 SAR data. An internal comparison with the classical ICP algorithm shows this method is more accurate. The effectiveness of the proposed method in monitoring surface deformation is verified.