基于时序InSAR的矿区沉降监测及动态预计研究
Time-series InSAR-based Subsidence Monitoring and Dynamic Prediction in Mining Areas
奚小军 1李晋波2
作者信息
- 1. 沈阳市勘察测绘研究院有限公司,辽宁 沈阳 110004;沈阳市自然资源卫星应用技术中心,辽宁 沈阳 110004;辽宁省城市资源监测重点实验室,辽宁 沈阳 110004
- 2. 山西长平煤业有限责任公司,山西 晋城 048000
- 折叠
摘要
矿区沉降监测和预测对于防范地质灾害、恢复生态环境具有重要意义.矿山开采地表移动变形动态预计是采空区塌陷研究中的关键问题.InSAR对大变形区域进行沉降监测能得到高分辨率和高精度的时序沉降监测结果.本文将时序InSAR地表形变技术与幂指数Knothe模型相结合,研究矿区地表沉降的动态变化过程.首先研究了SBAS-InSAR地表形变监测技术,矿区动态沉降模型,以及InSAR侧视成像与矿区地表之间的几何关系式确定沉陷位移值计算方法.通过提取地表沉陷盆地边界点形变时间序列,反演幂指数Knothe时间函数建立动态预计模型.通过山西某矿区2019—2021年27景哨兵影像,数据处理得到地表形变影像图提取边界点沉降时间序列,利用遗传算法反演Knothe模型参数,并与GPS-RTK观测数据相对比分析.根据选取某个具有代表性的下沉特征点验证结果,一致性良好,可以为矿区开采沉陷模型建立提供理论依据.
Abstract
The monitoring and prediction of subsidence in mining areas is of great significance for the prevention of geological disasters and the restoration of ecological environment. The dynamic prediction of surface movement deformation in mining is a key issue in the study of subsidence in mining areas. InSAR subsidence monitoring of large deformation areas can obtain high resolution and high accuracy time-series subsidence monitoring results. In this paper,the time-series InSAR surface deformation technique is combined with the power exponential Knothe model to study the dynamic process of surface subsidence in mining areas. This paper first investigates the SBAS-InSAR surface de-formation monitoring technique,the dynamic subsidence model of the mine area,and the geometric equation between InSAR side-view imaging and the mine surface to determine the calculation method of subsidence displacement values. The dynamic prediction model is established by extracting the time series of surface subsidence basin boundary point deformation and inverting the power exponential Knothe time function. Finally,through the 27-view sentinel image of Changping mine area from 2019-2021,the surface deformation image map is obtained by using data processing to extract the boundary point subsidence time series,invert the Knothe model parameters by using genetic algorithm,and ana-lyse them in comparison with GPS-RTK observation data. Based on the validation results of a selected representative subsidence feature point,the time-series InSAR monitoring values agree well with the GPS-RTK values and have practical application value. It can provide a theoreti-cal basis for the establishment of mining subsidence models.
关键词
时序InSAR/沉降监测/knothe函数/动态预计Key words
time-series InSAR/subsidence monitoring/Knothte function/dynamic prediction引用本文复制引用
基金项目
自然资源部重点实验室开放基金(ZRZYBWD202110)
辽宁省企业技术创新重点项目计划(167785620219)
出版年
2024
NETL
NSTL
万方数据