Remote Sensing, Vol. 16, Pages 2752: Construction of High-Precision and Complete Images of a Subsidence Basin in Sand Dune Mining Areas by InSAR-UAV-LiDAR Heterogeneous Data Integration

Remote Sensing, Vol. 16, Pages 2752: Construction of High-Precision and Complete Images of a Subsidence Basin in Sand Dune Mining Areas by InSAR-UAV-LiDAR Heterogeneous Data Integration

Remote Sensing doi: 10.3390/rs16152752

Authors: Rui Wang Shiqiao Huang Yibo He Kan Wu Yuanyuan Gu Qimin He Huineng Yan Jing Yang

Affected by geological factors, the scale of surface deformation in a hilly semi-desertification mining area varies. Meanwhile, there is certain dense vegetation on the ground, so it is difficult to construct a high-precision and complete image of a subsidence basin by using a single monitoring method, and hence the laws of the deformation and inversion of mining parameters cannot be known. Therefore, we firstly propose conducting collaborative monitoring by using InSAR (Interferometric Synthetic Aperture Radar), UAV (unmanned aerial vehicle), and 3DTLS (three-dimensional terrestrial laser scanning). The time-series complete surface subsidence basin is constructed by fusing heterogeneous data. In this paper, SBAS-InSAR (Small Baseline Subset) technology, which has the characteristics of reducing the time and space discorrelation, is used to obtain the small-scale deformation of the subsidence basin, oblique photogrammetry and 3D-TLS with strong penetrating power are used to obtain the anomaly and large-scale deformation, and the local polynomial interpolation based on the weight of heterogeneous data is used to construct a complete and high-precision subsidence basin. Compared with GNSS (Global Navigation Satellite System) monitoring data, the mean square errors of 1.442 m, 0.090 m, 0.072 m are obtained. The root mean square error of the high-precision image of the subsidence basin data is 0.040 m, accounting for 1.4% of the maximum subsidence value. The high-precision image of complete subsidence basin data can provide reliable support for the study of surface subsidence law and mining parameter inversion.