地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (12): 2425-2435.doi: 10.12082/dqxxkx.2020.190741

• 遥感科学与应用技术 • 上一篇    下一篇

联合DInSAR与Offset-tracking技术监测高强度采区开采沉陷的方法

徐小波1,*(), 马超2,3, 单新建4, 连达军1, 屈春燕4, 白俊武1   

  1. 1.苏州科技大学环境科学与工程学院,苏州 215009
    2.河南理工大学测绘与国土信息工程学院, 焦作 454003
    3.河南理工大学 自然资源部矿山时空信息与生态修复重点实验室,焦作 454003
    4.中国地震局地质研究所 地震动力学国家重点实验室,北京 100029
  • 收稿日期:2019-12-02 修回日期:2020-04-13 出版日期:2020-12-25 发布日期:2021-02-25
  • 通讯作者: 徐小波 E-mail:Tim-xxb@163.com
  • 作者简介:徐小波(1988— ),男,江西上饶人,讲师,博士,主要从事InSAR监测地表形变研究。E-mail: Tim-xxb@163.com
  • 基金资助:
    国家自然科学基金项目(41701515);国家自然科学基金委员会与神华集团有限责任公司联合基金项目(U1261106);国家自然科学基金委员会与神华集团有限责任公司联合基金项目(U1261206);地震动力学国家重点实验室开放基金(LED2018B04);江苏省自然科学基金(BK20170379)

Monitoring Ground Subsidence in High-intensity Mining Area by Integrating DInSAR and Offset-tracking Technology

XU Xiaobo1,*(), MA Chao2,3, SHAN Xinjian4, LIAN Dajun1, QU Chunyan4, BAI Junwu1   

  1. 1. School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
    2. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China
    3. Key Laboratory of Spatio-temporal Information and Ecological Restoration of Mines(MNR), Henan Polytechnic University, Jiaozuo 454003, China
    4. State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing 100029, China
  • Received:2019-12-02 Revised:2020-04-13 Online:2020-12-25 Published:2021-02-25
  • Contact: XU Xiaobo E-mail:Tim-xxb@163.com
  • Supported by:
    National Natural Science Foundation of China(41701515);National Natural Science Foundation of China and the Shenhua Coal Industry Group Company Limited(U1261106);National Natural Science Foundation of China and the Shenhua Coal Industry Group Company Limited(U1261206);State Key Laboratory of Earthquake Dynamics(LED2018B04);National Natural Science Foundation of Jiangsu Province(BK20170379)

摘要:

高强度煤炭开采产生巨大的地表形变,形变相位梯度过大导致干涉测量解缠错误,单一采用常规DInSAR及其衍生技术都无法获得地表沉陷主值。本文提出一种新的解决方案,即联合利用DInSAR与偏移量追踪技术(Offset-tracking)各自的技术优势,实现开采区大变形的准确提取,并基于GAUSS函数模型拟合恢复沉陷区剖面形态。基于2012年2月13日和2012年11月27日两景高分辨率SAR数据(RADARSAT-2,5 m精细波束模式(MF5))为数据源,以神东矿区布尔台矿、寸草塔一矿、二矿为研究区,采用常规DInSAR技术获得亚厘米级沉陷区边界,边界沉陷值处于-0.01~ -0.02 m;利用偏移量追踪方法获取米级地表沉陷中心主值,中心沉陷值集中在-1.0~ -4.0 m。将2种方法监测到沉陷信息分段融合,最后采用GAUSS函数模型重构矿区开采沉陷下沉特征曲线。结果表明,偏移量追踪方法可弥补DInSAR技术监测大量级形变信息的不足,联合技术可完整获取高强度采区的大形变沉陷。

关键词: 布尔台矿, 高强度采区, 大形变沉陷, DInSAR, 偏移量追踪, GAUSS拟合, 沉陷特征, Radarsat

Abstract:

High-intensity underground mining leads to huge surface deformation, and excessive deformation phase gradients could lead to interference unwrapping errors. Currently, the characteristics of surface subsidence cannot be obtained well by conventional DInSAR and its derivative technologies. In this paper, we propose a new method, which combines DInSAR and Offset-tracking technology to extract large-scale deformation accurately, and further restore settlement field shape using the GAUSS function model. We take Bu'ertai Mine, and Cuncaota No.1 and No.2 Mine in Shendong Mining Area as research areas and use the high-resolution RADARSAT-2 data with 5 m fine beam model (MF5) on February 13, 2012 and November 27, 2012 to obtain the mine subsidence boundaries at sub-centimeter level using DInSAR technology and the mine subsidence center at meter level using Offset-tracking method. The boundary subsidence value is -0.01~ -0.02 m and the central subsidence value is -1.0~ -4.0 m. The whole subsidence field is then retrieved by integrating above two results. Finally, the GAUSS function model is used to fit the mining subsidence boundary and central, and to reconstruct the characteristic curve of mining subsidence. Our results demonstrate that the Offset-tracking method could compensate the deficiency of DInSAR in large deformation extraction, and the combination of these two techniques could effectively and accurately extract large-scale subsidence field in mining areas.

Key words: Bu'ertai mine, high-intensity mining, large scale subsidence, DInSAR, Offset-tracking, GAUSS_fitting, subsidence characteristics, Radarsat