首页|基于联合时序InSAR技术的矿区沉降隐患区识别

基于联合时序InSAR技术的矿区沉降隐患区识别

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针对目前单一InSAR解译技术方法在复杂地表形变解译中精度及可靠性有限的难点,提出了利用PS-InSAR(persist scatterers InSAR)、SBAS-InSAR(small base-line subsets InSAR)这 2 种时序InSAR技术联合进行山地矿区地面沉降隐患区圈划的方法.以湖北省宜都市松宜矿区为例,基于大样本理论,利用矿区内高精度的PS点形变结果,校正具有高空间覆盖率的SBAS-InSAR处理结果,从而进一步提高地表形变监测精度并增加形变靶区范围圈划的准确度.通过对比使用单一PS-InSAR技术和经过PS-SBAS联合方法处理后得到的典型形变点时序曲线及野外实地调查,验证了解译结果的可靠性.研究表明:联合时序InSAR技术可以提高地表沉降监测精度并增加地表变形靶区范围圈划的准确度,为类似山地矿区的地面沉降隐患监测与分析提供新的技术思路.
Identification of mining subsidence hazard areas based on joint time series InSAR technology
A methodology is proposed to address the limitations in accuracy and reliability of the current single InSAR techniques for complex ground deformation analysis.By combining two time series InSAR techniques,PS-InSAR(persist scatterers InSAR)and SBAS-InSAR(small base-line subsets InSAR),a comprehensive delineation of potential subsidence hazard areas in mountainous mining regions is achieved.Taking the Songyi mining area in Yidu,Hubei Province as an example,the high-precision PS point deformation results within the mining area are utilized to calibrate the SBAS-InSAR processing outcomes,which possess high spatial coverage.This approach improves the accuracy of ground deformation monitoring and enhances the precision of area delineation.The reliability of the interpretation results is validated by comparing the time-series curves of typical deformation points obtained using the single PS-InSAR technology and the joint PS-SBAS method,as well as the on-site field investigations.This research shows that the joint time series InSAR technology can elevate the monitoring accuracy of ground subsidence and enhance the precision of area delineation,and offer new technological insights for monitoring and analyzing ground subsidence hazards in similar mountainous mining regions.

mountainous areas in western Hubeiground subsidence in mining areadeformation monitoringjoint time series InSAR technology

彭一桂、艾东、曾斌、刘诗雅

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中国地质大学(武汉)环境学院,湖北 武汉 430078

湖北省地质局第七地质大队,湖北 宜昌 443100

鄂西山地 矿区地面沉降 形变监测 联合时间序列InSAR技术

湖北省地质局科技基金项目湖北省地质局第七地质大队科技基金项目

KJ2022-24DQKJ2022-1

2024

自然灾害学报
中国地震局工程力学所 中国灾害防御协会

自然灾害学报

CSTPCD北大核心
影响因子:0.862
ISSN:1004-4574
年,卷(期):2024.33(3)