Reconstruction of Coal Mining Subsidence Field by Fusion of SAR and UAV LiDAR Deformation Data

Author:

Yang Bin1ORCID,Du Weibing12ORCID,Zou Youfeng1,Zhang Hebing1,Chai Huabin1,Wang Wei3,Song Xiangyang1ORCID,Zhang Wenzhi1

Affiliation:

1. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China

2. Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains, Zhengzhou 450000, China

3. Shendong Coal Branch, China Shenhua Energy Co., Ltd., Yulin 719000, China

Abstract

The geological environment damage caused by coal mining subsidence has become an important factor affecting the sustainable development of mining areas. Reconstruction of the Coal Mining Subsidence Field (CMSF) is the key to preventing geological disasters, and the needs of CMSF reconstruction cannot be met by solely relying on a single remote sensing technology. The combination of Unmanned Aerial Vehicle (UAV) and Synthetic Aperture Radar (SAR) has complementary advantages; however, the data fusion strategy by refining the SAR deformation field through UAV still needs to be updated constantly. This paper proposed a Prior Weighting (PW) method based on Satellite Aerial (SA) heterogeneous remote sensing. The method can be used to fuse SAR and UAV Light Detection and Ranging (LiDAR) data for ground subsidence parameter inversion. Firstly, the subsidence boundary of Differential Interferometric SAR (DInSAR) combined with the large gradient subsidence of Pixel Offset Tracking (POT) was developed to initialize the SAR preliminary CMSF. Secondly, the SAR preliminary CMSF was refined by UAV LiDAR data; the weights of SAR and UAV LiDAR data are 0.4 and 0.6 iteratively. After the data fusion, the subsidence field was reconstructed. The results showed that the overall CMSF accuracy improved from ±144 mm to ±51 mm. The relative errors of the surface subsidence factor and main influence angle tangent calculated by the physical model and in situ measured data are 1.3% and 1.7%. It shows that the proposed SAR/UAV fusion method has significant advantages in the reconstruction of CMSF, and the PW method contributes to the prevention and control of mining subsidence.

Funder

National Natural Science Foundation of China

PI project of Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains Grant

Publisher

MDPI AG

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