Monitoring and Analysis of Surface Deformation in Lingshi County Using Dual-Orbit LuTan-1 SBAS-InSAR

Abstract

The Loess Plateau features complex geological conditions. Large-scale coal-mining activities further trigger severe and spatially heterogeneous surface deformation, which poses substantial challenges for high-precision deformation monitoring. Conventional single-orbit, medium-resolution InSAR suffers from topographic distortion and cannot support full-coverage, high-precision regional monitoring. Taking Lingshi County as the study area, this study establishes a refined full-coverage monitoring framework using ascending and descending L-band (24 cm wavelength) LuTan-1 (LT-1) time-series InSAR (Interferometric Synthetic Aperture Radar). An optimized SBAS-InSAR workflow, which combines small-baseline interferogram with the StaMPS spatial correlation-based distributed scatterer inversion, is implemented. Integrating strip mosaicking, azimuth resampling, and deformation inversion, the proposed approach processes dual-orbit LT-1 SAR data spanning July 2023 to September 2025. We extract spatiotemporal deformation evolution, exploit the geometric complementarity of dual-line-of-sight observations, and interpret mining-dominated deformation mechanisms coupled with geological hazards. L-band LuTan-1 SAR data are adopted with temporal and spatial baseline thresholds set to 96 days and 300 m for small-baseline interferogram construction. A total of 223 deformation zones covering an area of 66.64 km2 are identified, which are concentrated across three towns. The descending-orbit dataset yields a monitoring coverage of 88.69%, compared to 79.20% for ascending-orbit data. Combined dual-orbit observations increase the full-area monitoring coverage to 98.91% and eliminate layover and shadow induced blind zones. Over 90% of deformed areas are correlated with underground coal mining. Field investigations and unmanned aerial vehicle (UAV) surveys achieve a 95.96% success rate for deformation-anomaly identification (qualitative detection of deformation zones rather than quantitative velocity accuracy), which validates the reliability of the proposed workflow. This study proposes an innovative L-band SAR monitoring strategy for loess coal-mining zones and provides support for mining disturbance evaluation, ecological restoration and geological hazards detection across the Loess Plateau.