Revealing Land Surface Deformation Over the Yineng Backfilling Mining Area, China, by Integrating Distributed Scatterer SAR Interferometry and a Mining Subsidence Model

Abstract

Monitoring the surface deformation of filling coal mines regularly and understanding their spatiotemporal evolution characteristics for mining management and disaster warning is greatly significant. However, there is a lack of research on extracting spatiotemporal evolution characteristics of large-scale and high-resolution surface deformation in backfill mining areas and on evaluating the filling effectiveness of subsidence restraint. In this study, we took the Yineng Coal Mine in the Shandong Province of China and the surrounding area of the coal mine as the study area. The advanced distributed scatterer interferometric synthetic aperture radar (DS InSAR) technique was adopted for time-series analysis. The probability integral method (PIM) model for backfilling mining and an arctangent time function were integrated with DS InSAR to overcome the sparsity of InSAR observation points due to the temporal decorrelation caused by vegetation coverage. The results show that the proposed integration strategy is helpful in improving the number of effective monitoring points and obtaining complete spatiotemporal information of the surface deformation of the working face. The whole study area has eight key deformation zones. All six working faces in the Yineng initial minery display different degrees of deformation during the study period. The comparison between the deformation results of backfill mining and the simulated deformation of nonbackfill mining in the CG1312 working face shows that backfilling mining technology effectively reduces the range (22.00%) and magnitude (61.50%) of surface subsidence and significantly reduces the potential threat to surface buildings.

Keywords

• Backfilling mining area
• distributed scatterer InSAR (DS InSAR)
• integrated method
• probability integral method (PIM)
• subsidence restraint
• surface deformation monitoring