西藏色拉滑坡时序InSAR二维形变反演与预测  

Two-Dimensional Deformation Inversion with Time-Series InSAR and Prediction of Sela Landslide in Tibet

作　　者：刘媛媛[1,2] 陈人杰 陈能辉 LIU Yuanyuan;CHEN Renjie;CHEN Nenghui(School of Surveying and Geoinformation Engineering,East China University of Technology,Nanchang,Jiangxi 330013,China;Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources,East China University of Technology,Nanchang,Jiangxi 330013,China;Jiangxi Provincial Architectural Design and Research Institute Group Co.,Ltd.,Nanchang,Jiangxi 330000,China)

机构地区：[1]东华理工大学测绘与空间信息工程学院,江西南昌330013 [2]东华理工大学自然资源部环鄱阳湖区域矿山环境监测与治理重点实验室,江西南昌330013 [3]江西省建筑设计研究总院集团有限公司,江西南昌330000

出　　处：《北京理工大学学报》2023年第11期1115-1124,共10页Transactions of Beijing Institute of Technology

基　　金：国家自然科学基金资助项目(42104030,41929001,42161064);江西省自然科学基金资助项目(20202BABL212016);自然资源部环鄱阳湖区域矿山环境监测与治理重点实验室开放基金资助项目(MEMM1-2021-2022-23);东华理工大学博士科研启动基金资助项目(DHBK2018004);江西省自然资源厅重点科技项目(ZRKJ20232424)。

摘　　要：针对西藏贡觉县色拉滑坡,采用小基线集技术获取滑坡一维视线向形变结果,通过多维小基线集技术计算滑坡二维东西向与垂直向形变速率与时间序列形变,结果表明色拉滑坡以东西向形变为主且滑坡前缘特征点累积位移超过100 mm;并将特征点累积形变与地区降雨量进行对比分析,发现每年6月-9月期间滑坡前缘受强降雨影响形变速率加快从而牵引滑坡中后部分加速形变.采用长短期记忆网络模型对滑坡特征点时间序列进行预测分析,预测结果显示周期性和缓慢形变可获得恰当的预测结果,对于剧烈形变的特征点符合其运动趋势.所得结果可为金沙江流域类似滑坡灾害预警提供参考.The Jinsha river is the upstream section of the Yangtze river located in the mountainous region of western China.Due to complex topography and frequent disasters,it often endangers people's lives and proper-ties as well as cause serious damage to infrastructure,Timely identification of the feature and patterns of land-slide deformation is conducive to the prevention and early warning of landslide disasters.Firstly,the one-dimen-sional line-of-sight deformation results were obtained based on the small baseline subsets(SBAS)technique for the Sela landslide in Gongjue county,Tibet,and then,the deformation rates and time series deformation of the two-dimensional deformation in the east-west direction and vertical direction were calculated with the multidi-mensional small baseline subsets(MSBAS)technique.The results show that the Sela landslide mainly produces in east-west deformation and the cumulative deformation of the feature point on landslide front edge can exceed 100 mm.Comparing and analyzing the time series deformation and regional rainfall,the deformation rate of the landslide front edge was found to be accelerated due to heavy rainfall from June to September each year,pulling the middle and rear parts of the landslide accelerated deformation.Finally,a long short-term memory(LSTM)model was used to predict and analyze the time series deformation of landslide,providing the appropriate predic-tion results with both periodic and slow-moving deformation case,and the points in the severe deformation and also in accordance with their motion trends.The obtained results can provide a reference for the early warning of similar landslide disasters in the valley of Jinsha River.

关 键 词：色拉滑坡 合成孔径雷达干涉测量 多维小基线集技术 二维形变 长短期记忆网络模型 

分 类 号：P237[天文地球—摄影测量与遥感] P642.22[天文地球—测绘科学与技术]