Polarimetric Time-Series InSAR for Surface Deformation Monitoring in Mining Area Using Dual-Polarization Data

Timely and reliable surface deformation monitoring is critical for hazard prevention and resource management in mining areas. However, traditional Time-Series Interferometric (TSI) Synthetic Aperture Radar techniques often suffer from low coherent point density in mining environments, limiting their effectiveness. To overcome this limitation, we propose an adaptive Polarimetric TSI (PolTSI) method that exploits dual-polarization Sentinel-1 data to achieve more reliable deformation monitoring in complex mining terrains. The method employs a dual-strategy optimization: amplitude dispersion-based optimization for Permanent Scatterer (PS) pixels and minimum mean square error (MMSE)-based polarimetric filtering followed by coherence maximization for Distributed Scatterer (DS) pixels. Experimental results from an open-pit mining area demonstrate that the proposed approach significantly improves phase quality and spatial coverage. In particular, the number of coherent monitoring points increased from 31,183 with conventional TSI to 465,328 using the proposed approach, corresponding to a 1392% improvement. This substantial enhancement confirms the method's robustness in extracting deformation signals from low-coherence, heterogeneous mining surfaces. As one of the few studies to apply Polarimetric InSAR (Pol-InSAR) in active mining regions, our work demonstrates the underexplored potential of dual-pol SAR data for improving both the spatial density and reliability of time-series deformation mapping. The results provide a solid technical foundation for large-scale, high-precision surface monitoring in complex mining environments.