Frequent mining activities create a series of geological and environmental problems resulting in an immeasurable loss of life and property. Adopting effective technologies that monitor the surface subsidence of mining areas reliably and accurately is necessary. Targeting problems associated with conventional distributed scatterers interferometric synthetic aperture radar (DS-InSAR) technology, we propose a DS-InSAR technology integrating unmanned aerial vehicle (UAV) photogrammetry products divided into two key technical contents: generating an external reference digital elevation model (DEM) fused with UAV DEM and refining distributed scatterers candidates (DSCs) fused with an UAV digital orthophoto map (DOM). We selected two mining areas, one in Wu’an, Hebei, and the other in Inner Mongolia, with different surface cover types, mining depths, and topographies as the research area. We used Sentinel-1A SAR images covering a mine in Wu’an from 4 November 2018 to 4 March 2019 and a mining area in Inner Mongolia from 11 June 2018 to 21 October 2018 to compare and analyze the subsidence results. We also combined these results with data from their respective field observation stations to assess accuracy. We could apply DS-InSAR technology integrated with UAV photogrammetry products to the subsidence monitoring of two mining areas with different landforms and mining characteristics. Comparing with the leveling and total station, the experimental results show that the RMSE was reduced by about 2 mm in both mining areas, and accuracy for the Wu’an region improved to a higher degree than Inner Mongolia did. Furthermore, the refinement method of DS eliminated 965 and 2948 lower-quality DSCs in the two mining areas. These demonstrate that our proposed method can effectively improve the accuracy and reliability of subsidence results from two mining areas.

Constructing high-precision subsidence basins is of paramount importance for mining subsidence monitoring. Traditional unmanned aerial vehicle (UAV) photogrammetry techniques typically construct subsidence basins by directly differencing digital elevation models (DEMs) from different monitoring periods. However, this method often neglects the influence of horizontal displacement on the accuracy of the subsidence basin. Taking a mining area in Ordos, Inner Mongolia, as an example, this study employed the normalized cross-correlation (NCC) matching algorithm to extract horizontal displacement information between two epochs of a digital orthophoto map (DOM) and subsequently corrected the horizontal position of the second-epoch DEM. This ensured that the planar positions of ground feature points remained consistent in the DEM before and after subsidence. Based on this, the vertical displacement in the subsidence area (the subsidence basin) was obtained via DEM differencing, and the parameters of the post-correction subsidence basin were inverted using the probability integral method (PIM). The experimental results indicate that (1) the horizontal displacement was influenced by the gully topography, causing the displacement within the working face to be segmented on both sides of the gully; (2) the influence of the terrain on the subsidence basin was significantly reduced after correction; (3) the post-correction surface subsidence curve was smoother than the pre-correction curve, with abrupt error effects markedly diminished; (4) the accuracy of the post-correction subsidence basin increased by 43.12% compared with the total station data; and (5) comparing the measured horizontal displacement curve with that derived using the probability integral method revealed that the horizontal displacement on the side of an old goaf adjacent to the newly excavated working face shifted toward the advancing direction of the new working face as mining progressed. This study provides a novel approach and insights for using low-cost UAVs to construct high-precision subsidence basins.

With its high spatiotemporal resolution and wide-area coverage, InSAR technology has become an essential tool for monitoring mining-induced surface subsidence. However, the large-gradient deformation caused by the traditional caving method has hindered this technology’s widespread application in subsidence monitoring. With the increasing adoption of backfill mining techniques, both the magnitude and the gradient of surface deformation have been significantly reduced, creating new opportunities for applying InSAR to subsidence monitoring in mining areas. Nevertheless, current research on InSAR under backfill mining conditions remains relatively limited, particularly with respect to the applicability of time-series InSAR techniques in such settings. In this study, the Wu’an mining area, characterized by the traditional caving method, and the Fengfeng mining area, which employs overburden isolated grouting backfill mining, were selected as representative cases. By integrating Small Baseline Subset InSAR (SBAS-InSAR) time-series deformation results with ground-based leveling measurements, we comparatively analyzed the interferometric coherence characteristics and deformation monitoring performance associated with the two mining methods. We then evaluated the monitoring applicability and engineering feasibility of InSAR under overburden isolated grouting backfill mining conditions. The results indicate that, under similar surface land cover conditions, the gradient of surface deformation exerts a strong influence on interferometric coherence. Comparison with leveling measurements shows that the RMSE in the Fengfeng mining area under overburden isolated grouting backfill mining is at least 68.2% lower than that in the Wu’an mining area under caving mining. Moreover, overburden isolated grouting backfill mining can effectively mitigate mining-induced surface deformation, limiting the maximum subsidence in the Fengfeng mining area to less than 300 mm and to less than 200 mm in village areas. Using Sentinel-1 data and a conventional SBAS-InSAR processing workflow, InSAR demonstrates higher reliability and applicability for surface subsidence monitoring in mining areas under overburden isolated grouting backfilling conditions than in those under caving mining conditions. This study aims to provide a useful reference for mining subsidence monitoring based on Sentinel-1 C-band data and a conventional SBAS-InSAR processing workflow.