A New Strategy for Extracting 3D Deformation of Mining Areas from a Single-Geometry Synthetic Aperture Radar Dataset

This paper presents a strategy for extracting three-dimensional (3D) mining deformation from a single-geometry synthetic aperture radar (SAR) dataset. In light of the directionality of horizontal displacement caused by underground mining, we first re-model the proportional relationship between horizontal displacement and horizontal gradient of subsidence. Afterward, to improve the stability of the re-model, a solution strategy is proposed by setting different solution starting points and directions. The proposed method allows hiring of arbitrary single-geometry SAR data (e.g., air-borne, space-borne, and ground-borne SAR data) to reconstruct 3D displacements of mining areas. The proposed method has been validated through simulation and in-site data. The simulation data monitoring results indicate that the root mean square errors (RMSE) of the 3D displacements extracted by the proposed strategy are 0.45, 0.5, and 2.98 mm for the vertical subsidence, east-west, and north-south horizontal displacements, respectively. The in-site data monitoring results indicate that the RMSE of vertical subsidence compared with the leveling data are 7.3 mm. Furthermore, the MSBAS method was employed to further validate the reliability of the proposed method, the results show that the proposed method is effective to obtain the 3D deformation of the mining area, which greatly improves the applicability of SAR interferometry in the 3D deformation monitoring of the mining areas.

Automated summary

This paper presents a strategy for extracting three-dimensional mining deformation using single-geometry SAR data. The methodology includes modeling the relationship between horizontal displacement and subsidence gradient and proposing a solution strategy to improve stability. The proposed method allows for the reconstruction of 3D displacements in mining areas using various types of SAR data. The effectiveness of the method is validated through simulation and in-site data, showcasing its applicability in mining deformation monitoring.