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利用InSAR识别与监测黑方台黄土滑坡
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  • 英文篇名:Identification and monitoring of Heifangtai loess landslide with InSAR
  • 作者:朱文峰 ; 赵超英 ; 张勤 ; 康亚
  • 英文作者:ZHU Wenfeng;ZHAO Chaoying;ZHANG Qin;KANG Ya;School of Geology Engineering and Geomatics,Chang'an University;National Administration of Surveying,Mapping and Geoinformation, Engineering Research Center of National Geographic Conditions Monitoring;Key Laboratory of Western Mineral Resources and Geological Engineering,Ministry of Education;
  • 关键词:黑方台 ; 合成孔径雷达干涉测量 ; 黄土滑坡 ; 滑坡调查 ; 监测
  • 英文关键词:Heifangtai;;InSAR;;loess landslide;;landslide investigation;;monitoring
  • 中文刊名:CHKD
  • 英文刊名:Science of Surveying and Mapping
  • 机构:长安大学地质工程与测绘学院;地理国情监测国家测绘地理信息局工程技术研究中心;西部矿产资源与地质工程教育部重点实验室;
  • 出版日期:2019-01-24 17:02
  • 出版单位:测绘科学
  • 年:2019
  • 期:v.44;No.251
  • 基金:国家自然科学基金项目(41731066,41628401);; 长安大学创新团队项目(310826173101)
  • 语种:中文;
  • 页:CHKD201905012
  • 页数:7
  • CN:05
  • ISSN:11-4415/P
  • 分类号:73-79
摘要
针对甘肃永靖县的黑方台地区滑坡不断对当地居民人身及财产安全构成重大威胁的现状,该文选取高分辨率的升降轨TerraSAR数据、3m分辨率的DEM数据和30m分辨率的SRTM DEM数据,利用InSAR技术对该地区的地表形变进行监测,主要结果如下:用Stacking技术获取了黑方台的形变速率图,识别出14处不稳定滑坡体;用SBAS-InSAR技术对典型滑坡体进行时间序列监测,将InSAR结果投影到滑坡方向与已有的GPS结果进行比较,最大较差为6mm,最大中误差为3mm。结果表明,InSAR技术用来识别与监测黄土滑坡方便可靠,并且精度较高。
        Landslide in the Heifangtai area of Yongjing County,Gansu Province,had been posed a serious threat to the safety of the people and property of local residents,TerraSAR data,two resolution DEM data including three-meter UAV DEM and thirty-meter SRTM DEM were chosen to analyze the surface deformation in Heifangtai area,finally 14 unstable landslides were identified from stacking InSAR and time-series deformation results over one typical landslide were retrieved by using SBAS-InSAR technology based on ascending and descending TerraSAR data.The results from InSAR were projected to the landslide direction and compared with the existing GPS results.the maximum difference was 6 mm,and the maximum root mean square error(RM_SE)was 3 mm.The conclusion showed that InSAR technology was convenient and reliable for identifying and monitoring loess landslides,and had high precision.
引文
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