253 / 2023-09-30 05:42:22

Comparative Study of Surface Deformation Monitoring Methods in Mining Areas Using Active and Passive Remote Sensing Technologies

mining area; unmanned monitoring; D-InSAR; UAV; SBAS

Coal mining induces surface subsidence, rendering the swift and precise monitoring of deformation within mining regions a matter of global significance. In light of the prevailing international inclination towards unmanned monitoring of mining-induced subsidence, this research focuses on the working face 110801 situated in Banji, Bozhou City, within the Anhui Province. To capture comprehensive data, we harnessed cutting-edge active remote sensing technologies, specifically Differential Interferometric Synthetic Aperture Radar (D-InSAR) and Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR). Leveraging these methods, we meticulously processed a dataset consisting of 38 observations from the Sentinel-1A satellite spanning the period from April 10, 2021, to June 28, 2022. These endeavors yielded valuable insights into ground subsidence phenomena within the specified area. A series of two time-phased digital surface model (DSM) datasets were acquired utilizing a passive remote sensing method through an Unmanned Aerial Vehicle (UAV). These datasets were subsequently processed to derive ground subsidence information spanning the period from April 10, 2021, to June 28, 2022. The monitoring outcomes obtained through the aforementioned three methodologies were subjected to analyses. Furthermore, the precision of these methods was ascertained through the validation process employing leveling data. The study has determined that all three methodologies are capable of detecting the subsidence basin. Within the periphery of the subsidence basin, both D-InSAR and SBAS-InSAR exhibited closer alignment with the leveling results, with SBAS-InSAR demonstrating superior precision in monitoring minor deformations. Conversely, the UAV-based monitoring results exhibited a greater divergence from the leveling data. In the central segment of the sedimentary basin, the findings from Unmanned Aerial Vehicle (UAV) monitoring exhibit a lesser disparity when compared to the leveling data. Conversely, both Differential Interferometric Synthetic Aperture Radar (D-InSAR) and Small Baseline Subset (SBAS-InSAR) analyses demonstrate a more pronounced variance when juxtaposed with the leveling data, it is noteworthy that D-InSAR outperforms SBAS-InSAR in terms of monitoring accuracy. These findings constitute a crucial foundation for the integration of multi-source remote sensing data in future endeavors. This integration will allow for the optimal utilization of the distinct advantages inherent in various remote sensing technologies for the purpose of monitoring mining subsidence. Additionally, it will facilitate the rapid and precise construction of comprehensive subsidence basins while enabling the unmanned monitoring of mining regions on a global scale.