A fusion framework of 3D physical model and InSAR monitoring for mining-induced deformation analysis

Underground resource extraction redistributes subsurface stress, inducing overburden movement and ground deformation. These geomechanical changes can cause ground fissures, slope failures, and collapses, resulting in resource loss, economic damage, safety risks, and environmental degradation. Therefore, accurate monitoring of surface deformation and understanding of deformation propagation mechanisms are crucial for sustainable resource extraction and geohazard mitigation. To this end, a fusion framework is proposed that integrates a three-dimensional physical model with Interferometric Synthetic Aperture Radar (InSAR) technology to monitor surface deformation and investigate deformation propagation. A mining area in China was selected as a case study. Sentinel-1A images were processed using Stacking-InSAR and Small Baseline Subset InSAR (SBAS-InSAR) techniques to derive surface deformation. InSAR-derived deformation was validated against GNSS measurements, yielding mean absolute errors (MAE) of 35.7 mm for Stacking-InSAR and 6.5 mm for SBAS-InSAR. Although SBAS-InSAR exhibits higher precision in coherent areas, it provides missing/invalid measurements in the central high-intensity deformation zone (cumulative deformation > 300 mm), indicating limited applicability under strong mining-induced disturbances. Concurrently, a large-scale three-dimensional physical model was constructed, and overburden strain and surface deformation were measured using distributed optical fiber sensing (DOFS) and digital close-range industrial photogrammetry (DCRIP). After scaling to the prototype, the physical-model surface deformation agrees well with the Stacking-InSAR measurements (mean relative error 17%–18%), confirming the reliability of the constructed physical model. Moreover, a prediction model was developed using synergistic monitoring data, achieving a root mean square error (RMSE) of 52.2 mm (i.e., 6.35% of the maximum deformation of 822.4 mm) and a standard deviation (STD) of 51.8 mm (6.30%) relative to the Stacking-InSAR results. These results demonstrate that the proposed framework effectively bridges laboratory-scale observations and field-scale satellite measurements, thereby improving the understanding of underground-to-surface deformation propagation under mining-induced disturbances. Furthermore, this integration enables high-precision estimation of mining-induced deformation and supports coupled surface and underground deformation analysis. • Developed a fusion framework integrating 3D physical modeling and InSAR techniques. • Physical modeling reveals underground deformation propagation undetectable by InSAR. • InSAR monitors surface deformation with high precision, complementing physical modeling. • Cross-validation confirmed high consistency between physical model and InSAR measurements. • Multi-scale data fusion enhances understanding of mining-induced deformation.