关键词: 大量级沉陷, SBAS-InSAR, UAV-LiDAR, 克里金插值, 煤矿沉降监测

Abstract: [Purposes]Surface subsidence induced by mining activities in mining areas is characterized by rapid deformation rates,significant damage severity,and extensive spatial coverage.To address the challenge that interferometric synthetic aperture radar (InSAR) struggles to capture complete basin information during large-scale subsidence monitoring due to spatiotemporal decoherence.[Methods]This paper proposes an InSAR-based large-scale subsidence monitoring method that integrates unmanned aerial vehicle laser radar (UAV-LiDAR)data.This method first acquires cumulative subsidence basins from both time-series InSAR and UAV-LiDAR data within the mining area.Reliable regions for both datasets are delineated based on deformation threshold segmentation.Kriging interpolation is then applied to spatially fuse transitional zones,enabling comprehensive reconstruction of the mining subsidence basin.[Findings]Verification conducted at the S1306 working face of Shanxi Lu'an Gucheng Coal Mine demonstrates that InSAR effectively monitors non-central subsidence zones,while UAV-LiDAR compensates for its accuracy limitations in large-scale subsidence areas.The fused results yield continuous and complete subsidence basins with well-preserved fine-scale features.[Conclusions]Compared with leveling survey data,the root mean square error (RMSE),mean absolute error (MAE),and mean squared error (MSE)of the fusion results were 81.6,63.0,and 6.7 mm,respectively.This validates the effectiveness of this method in obtaining complete and accurate subsidence information in mining areas under complex mining conditions.

Key words: large-scale subsidence, SBAS-InSAR, UAV-LiDAR, Kriging interpolation, coal mine subsidence monitoring