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姬宗皓,薄怀志,王东平,高彦生,宋炳忠.基于D—InSAR的济宁市采煤沉陷监测与分析[J].山东国土资源,2019,35(2):
基于D—InSAR的济宁市采煤沉陷监测与分析
Monitoring and Analysis of Coal Mining Subsidence in Ji'ning Based on D-InSAR
  
DOI:10.12128/j.issn.1672-6979.2019.02.006
中文关键词:  采煤沉陷区监测  DInSAR  RADARSAT2
英文关键词:Monitoring of coal mining subsidence  D-InSAR, RADARSAT-2
基金项目:
作者单位
姬宗皓 济宁市采煤塌陷地治理中心自然资源部采煤沉陷区综合治理与生态修复工程技术创新中心 
薄怀志 自然资源部采煤沉陷区综合治理与生态修复工程技术创新中心山东省鲁南地质工程勘察院山东省地矿局采煤塌陷地综合治理工程技术研究中心 
王东平 济宁市采煤塌陷地治理中心 
高彦生 济宁市采煤塌陷地治理中心 
宋炳忠 自然资源部采煤沉陷区综合治理与生态修复工程技术创新中心山东省鲁南地质工程勘察院山东省地矿局采煤塌陷地综合治理工程技术研究中心 
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中文摘要:
      对地下采煤造成的地表沉陷进行及时、精确的监测监管是一个亟待解决的课题。该文以济宁市为例,介绍了DInSAR技术在大范围采煤沉陷区监测及其时序变化特征分析中的应用。介绍了使用DInSAR技术对采煤沉陷进行监测的基本原理;以5cm下沉线作为采煤沉陷区边界线,选取15期RADARSAT2 Wide模式数据,采用多基线累积叠加方法分别提取各期采煤沉陷区边界并使用岩移观测数据对监测结果进行了检核。以花园煤矿为例,分析D-InSAR监测采煤沉陷范围及程度的时序变化特征,随着开采的持续进行,沉陷范围及沉陷量逐步增加,受临近工作面开采影响,沉陷中心的沉陷量呈周期性增加。结果表明,DInSAR可以精确有效地对采煤沉陷区范围及其时序变形过程进行监测,可以应用于大尺度采煤沉陷区的动态监测。
英文摘要:
      The timely and precise monitoring and management of surface subsidence caused by underground coal mining is an urgent problem. Taking Ji'ning city as an example, the application of D-InSAR technology in the monitoring of large scale coal mining subsidence area and characteristics analysis of its time series change have been introduced in this paper. Basic principle for monitoring coal mining subsidence by using D-InSAR technology has been introduced at first. Then, the 5cm subsidence lines are taken as the boundary of the coal mining subsidence area, and the 15 periods of RADARSAT-2 wide model data are selected. The method of multi-baseline cumulative superposition is used to extract the boundary of the coal mining subsidence area of each period, and the results are checked by using the data of leveling observation. Finally, by using each period of coal mining subsidence area obtained by D-InSAR technology, the temporal and spatial changing characteristics of mining subsidence area in Ji'ning city have been analyzed. The results show that D-InSAR could be used to monitor the coal mining subsidence area and its time series deformation process accurately and effectively. It can be applied in dynamic observation of large scale coal mining subsidence area.
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