摘要
地表形变引发的地质灾害给自然环境和社会带来了巨大威胁,小基线集合成孔径雷达干涉测量(SBAS-InSAR)技术以其监测精度高、监测范围大和非接触等优势,成为地表形变监测的重要手段,为预防地质灾害发生、降低灾害损失,实现地表形变有效监测具有重要意义。利用SBASInSAR技术对青海省西宁市2018年1月7日至11月27日27景Sentinel-1A数据进行处理,得到西宁市地表平均形变速率分布图。与同期8个西宁南山GPS地面观测点比较,除一个点误差较大外,其余7个点均方根误差都在3 mm以内,证明了SBAS-InSAR监测结果的可靠性。SBASInSAR监测结果表明:山体滑坡是西宁市地表形变的主要形式,特别是沿互助北山和G6京藏高速公路一带滑坡运动尤为明显。实验首次获取了西宁市火车站东北滑坡灾害点定量形变数据,为分析该灾害点状况、保障西宁火车站安全运行提供有价值的参考。
Geological disasters caused by surface deformation pose a great threat to the natural environment and society.SBAS-InSAR technology has become an important means of surface deformation monitoring with its ad⁃vantages of high monitoring accuracy,large monitoring range and non-contact,to prevent geological disaster and reducing disaster losses,achieve the surface deformation monitoring is importmant.In this paper,the SBAS-InSAR technology was used to process sentinel-1A data acquired during January 7,2018 and Novem⁃ber 27,2018 in Xining city,Qinghai province.The average surface deformation velocity distribution map was obtained.The deformations obtained by SBAS-InSAR were compared with those obtained by 8 GPS observa⁃tion stations which were installed to monitor the deformation of NanShan in Xining.Except for one GPS sta⁃tions,the RMS errors on the other 7 GPS stations are within 3 mm,which proves the reliability of SBAS-In⁃SAR.Based on the SBAS-InSAR monitoring results,it is pointed out that the landslide is the main form of ground deformation in Xining city,especially along the Mutual aid beishan and G6 highway.The quantitative deformation data on a landslide which is in northeast of Xining railway station were obtained for the first time.The quantitative deformation data are important to the deformation analysis of the landslide and the safe opera⁃tion of Xining railway station.
作者
安炳琪
罗海滨
丁海勇
张志山
王伟
史潇
柯福阳
王明明
An Bingqi;Luo Haibing;Ding Haiyong;Zhang Zhishan;Wang Wei;Shi Xiao;Ke Fuyang;Wang Mingming(School of Remote Sensing&Geomatics Engineering,NUIST,Nanjing 210044,China;Xining Surveying and Mapping Institute,Xining 810008,China;Xining Land Surveying and Planning Research Institute,Xining 810008,China;Jiangsu Meteorological Service Center,Nanjing 210008,China;Jiangsu Kebo Space Information Technology Co.,Ltd.,Nanjing 210044,China)
出处
《遥感技术与应用》
CSCD
北大核心
2021年第4期838-846,共9页
Remote Sensing Technology and Application
基金
国家自然科学基金项目(41571350)
西宁市科技计划项目(2019⁃Y⁃12)
江苏省自然资源厅科技项目(KJXM2019035)。