In the process of mineral resource extraction, monitoring surface deformation is crucial for ensuring the safety of engineering and ground infrastructure. Monitoring complete three-dimensional surface deformation is particularly significant. Traditional synthetic aperture radar (InSAR) technology provides deformation components only along the line of sight (LOS) and often lacks sufficient effective data in vegetation-covered mining areas and mining subsidence centers. To address this, this study proposes a method (SBAS-PIM) that combines SBAS-InSAR with the probabilistic integral method (PIM). This method leverages high-coherence points in mining areas and GNSS data from vegetation-covered regions to invert the parameters required by PIM, thus obtaining three-dimensional surface deformation results. The proposed method allows for the acquisition of three-dimensional deformation data with fewer InSAR points and GNSS data, significantly reducing labor costs and addressing the gap in InSAR monitoring of three-dimensional surface deformation in densely vegetated areas. Additionally, it accounts for the mutual influence of multiple adjacent working faces. Finally, through the application to a mining area in Heze, China, the maximum displacements in the vertical, east-west, and north-south directions were obtained as -2011, -418, and - 281 mm, respectively. The correlation coefficients between the vertical and east-west directions and GNSS data were both greater than or equal to 0.9, indicating that this method can effectively monitor the three-dimensional surface deformation of the mining area.
Keywords: 3D displacement; Adjacent multiple working faces; Probability integral method; SBAS-InSAR; Vegetation-covered mining areas.
© 2025. The Author(s).