基于SBAS-InSAR技术的黄河上游库坝群段滑坡识别及监测分析
Identification and Monitoring Analysis of Landslides in the Upper Yellow River Reservoir Area Based on SBAS-InSAR Technology
李泉林 1李秀珍 2龚俊豪 1赵晨澄1
作者信息
- 1. 中国科学院大学,北京 100049;中国科学院、水利部成都山地灾害与环境研究所,四川 成都 610041
- 2. 中国科学院、水利部成都山地灾害与环境研究所,四川 成都 610041
- 折叠
摘要
黄河上游库坝群段地质条件复杂,发育多处大型滑坡.该研究以黄河上游龙羊峡—盐锅峡段为研究区,基于地质条件调查、历史滑坡数据及遥感资料,选取2018-2021年80余景SENTTINEL-1A卫星数据,通过SBAS-InSAR监测雷达视线方向的地表形变速率,并将其转为沿斜坡方向形变速率.据此识别出57处缓慢变形的大型滑坡,并通过对变形速率的核密度分析,确定了形变集中区域.ROC曲线显示,这些区域与历史滑坡分布高度一致.在此基础上,以龙羊峡库区白刺滩典型滑坡为例,选取典型剖面及形变点,分析了时序形变与降雨量和水库水位变化相关关系.结果表明,白刺滩滑坡受到降雨和库水位变化影响显著,尤其是滑坡前缘形变序列与降雨量及库水位变化具有较强相关性.
Abstract
The geological conditions in the reservoir dam group section of the upper reaches of the Yellow River are complex,with the development of many large landslides.Focusing on the Longyangxia-Yangogorge section in the upper reaches of the Yellow River and based on the investigation of geological conditions and historical landslides in the area and remote sensing interpretation,more than 80 scenes of SENTINEL-1A data from 2018 to 2021 are selected.Using the SBAS-InSAR technique,the deformation rates in the radar line of sight are obtained and converted to deformation rates along the slope direction.Based on this,57 large landslides with slow deformation are identified,and deformation con-centration areas are obtained based on kernel density analysis of deformation rates.The ROC curve indicates a good consis-tency between the concentration areas and historical landslide distributions,with dense historical landslide distributions in deformation concentration areas.On this basis,the Baicitan landslide in the Longyangxia reservoir area is selected as a typical landslide.Typical profiles and deformation points are chosen to analyze the relationship between time-series defor-mation and rainfall and reservoir water level changes.The results show that the Baicitan landslide is affected by rainfall and reservoir water level changes,with a strong correlation between the deformation sequence at the front edge and changes in rainfall and reservoir water level.
关键词
滑坡识别及监测/SBAS-InSAR技术/时序分析/核密度分析/黄河上游库坝群段Key words
landslide identification and monitoring/SBAS-InSAR technology/time-series analysis/kernel den-sity analysis/upper Yellow River Reservoir-Dam cluster segment引用本文复制引用
出版年
2025
国家科技期刊平台
NSTL
万方数据