摘要
针对天水市大型或严重破坏的黄土滑坡调查与分析较少,潜在活动蠕变型滑坡的空间分布与未来发展趋势不明的问题,该文基于InSAR遥感技术对天水市活动性滑坡进行了解译识别、成因分析与调查核实,利用SBAS-InSAR计算的时序形变信息判断滑坡未来的发展趋势。研究区内发现了103处活动性灾害,其中69处为黄土滑坡、34处地面沉降区。结合地质条件和地貌特征分析表明,地质条件、人类活动、河流沟谷以及降雨是诱发滑坡产生的主要因素,而且滑坡的分布与斜坡坡度、坡向以及坡体与水系距离有很强的相关性。实验结果证明,InSAR技术可以有效地识别和监测黄土滑坡,可为区域灾害防治提供科学依据。
The investigation and analysis of large or seriously damaged loess landslides in Tianshui city are few and the spatial distribution and future development trend of potential active creep landslides are unknown.In this paper,based on InSAR remote sensing technology,the active landslides in Tianshui city were identified,analyzed and verified,and the future development trend of landslides were judged by using the time series deformation calculated by SBAS-InSAR technology.Total 103 active disasters were found in the study area,including 69 loess landslides and 34 land subsidence areas.The analysis of geological conditions and geomorphic features shows that geological conditions,human activities,rivers and rainfall are the main factors inducing landslides,and the distribution of landslides has a strong correlation with slope,aspect and the distance between slope and river.The experimental results show that InSAR technology can effectively identify and monitor loess landslides,and provide scientific basis for regional disaster prevention and control.
作者
姚佳明
姚鑫
刘星洪
姚闯闯
李凌婧
YAO Jiaming;YAO Xin;LIU Xinghong;YAO Chuangchuang;LI Lingjing(Key Laboratory of Active Tectonics and Geological Safety,Ministry of Natural Resources,Institute of Geomechanics,Chinese Academy of Geological Sciences,Beijing 100081,China;State Key Laboratory of Resources and Environment Information System,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《测绘科学》
CSCD
北大核心
2022年第1期121-132,共12页
Science of Surveying and Mapping
基金
中国地质调查局工作项目(DD20190717)
国家重点研发计划课题项目(2018YFC1505002)
三峡集团公司项目(YMJ(XLD)(19)110)
国家自然科学基金项目(41672359)。