Shandong Province Sanhekou Mining Industry Co., Ltd.
School of Surveying and Geo-Informatics, Shandong Jianzhu University

针对煤矿持续开采引起的地表沉降问题,联合SBAS-InSAR技术和概率积分法实现矿区全盆地精细化沉降监测,利用SBAS-InSAR技术获取矿区累积沉降量并提取沉降盆地边缘特征点,进一步联合实测水准数据,基于遗传算法求解概率积分法参数,获取矿区地表沉降监测,依据InSAR最大形变梯度理论,通过计算干涉图平均相干性,并以此为阈值将SBAS-InSAR沉降结果和概率积分法的结果进行融合,获取矿区精细化地表沉降信息。以山东省三河口煤矿为研究区,采用2022年11月2日到2023年8月29日期间覆盖研究区的26景Sentinel-1A数据,对该方法的精度进行验证。结果表明,该方法的监测精度优于单独使用SBAS-InSAR技术和概率积分法,可以获取矿区全盆地精细化沉降信息。

In response to the problem of surface subsidence caused by continuous coal mining, SBAS-InSAR technology and probability integration method are combined to achieve refined subsidence monitoring of the whole basin of the mining area. SBAS-InSAR technology is used to obtain the cumulative subsidence amount of the mining area and extract the characteristic points of the subsidence basin edge. Further, the actual measured leveling data is combined, and the probability integration method parameters are solved based on genetic algorithm to obtain surface subsidence monitoring of the mining area. According to InSAR maximum shape change gradient theory, by calculating the average coherence of the interferogram, and taking it as a threshold value to fuse the SBAS-InSAR subsidence results and probability integration method to obtain refined surface subsidence information of the mining area. Taking Sanhekou Coal Mine in Shandong Province as the research area, the accuracy of this method is validated using 26 scenes Sentinel-1A data of covered research areas from November 2, 2022 to August 29, 2023. The results indicate that the monitoring accuracy of this method is superior to using SBAS-InSAR technology and probability integration method alone, and can obtain refined subsidence information of the whole basin of the mining area.