Tao Qiuxiang, Liu Ruixiang, Li Xuepeng, Gao Tengfei, Chen Yang, Xiao Yixin, He Huzhen, Wei Yunguang
College of Geodesy and Geomatics, Shandong University of Science and Technology, 579 Qianwangang Road, Qingdao, 266590, China.
Demonstration Center for Experimental Surveying and Mapping Education (Shandong University of Science and Technology), 579 Qianwangang Road, Qingdao, 266590, China.
Sci Rep. 2025 Jan 22;15(1):2853. doi: 10.1038/s41598-025-87087-4.
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.
在矿产资源开采过程中，监测地表变形对于确保工程和地面基础设施的安全至关重要。监测完整的三维地表变形尤为重要。传统的合成孔径雷达（InSAR）技术仅提供沿视线（LOS）方向的变形分量，并且在植被覆盖的矿区和开采沉陷中心往往缺乏足够的有效数据。为了解决这一问题，本研究提出了一种将SBAS-InSAR与概率积分法（PIM）相结合的方法（SBAS-PIM）。该方法利用矿区的高相干点和植被覆盖区域的GNSS数据来反演PIM所需的参数，从而获得三维地表变形结果。所提出的方法能够用较少的InSAR点和GNSS数据获取三维变形数据，显著降低了劳动力成本，并解决了InSAR在植被茂密地区三维地表变形监测方面的空白。此外，它还考虑了多个相邻工作面的相互影响。最后，通过在中国菏泽某矿区的应用，得到垂直、东西和南北方向的最大位移分别为-2011、-418和-281mm。垂直方向与东西方向和GNSS数据之间的相关系数均大于或等于0.9，表明该方法能够有效地监测矿区的三维地表变形。
