Multi-dimensional Time-series InSAR Applied To Landslide Identification And Monitoring In Liupanshui Of GuiZhou

China has the largest contiguous exposed karst area in the world.Among the widely distributed karst areas,the southwest karst region is full of mountains and valleys,has a fragile geological environment,developed river system and strong human engineering activities and many potential hazards.Large landslides are frequent in this region and have serious consequences.Landslides are a serious threat to the lives and property of people living in karst mountain areas.However,the current conventional landslide hazard monitoring methods: laser point cloud monitoring,CNSS monitoring and optical remote sensing monitoring all have their shortcomings.In SAR technology,as an emerging active remote sensing technology,has the advantages of being unaffected by clouds and rain and collecting data around the clock.In recent years,it has developed rapidly and has been widely used in geological hazard identification and monitoring.At the same time,it offers the possibility of deciphering landslide mechanisms and instability patterns based on deformation results.However,due to the special climatic and geological environment of the study area,spatial and temporal decoherence and atmospheric disturbances caused by vegetation and rainfall are still the pain points of long time series karst mountain surface deformation monitoring.In this paper,Liupanshui City,Guizhou Province,is selected as the research object for wide-area hazard identification,and the existing In SAR data processing methods are reasonably used to obtain the distribution of hazards in Liupanshui City and analyze the distribution and causes of landslide hazards.The landslide mechanism and instability pattern of the Pingdi landslide in the Shuicheng District of Liupanshui City and the settlement deformation process of the Yanbiankou Plateau in Zhongshan District are analyzed in detail in conjunction with the In SAR deformation results.The specific research results of this paper are as follows:(1)The principle of surface deformation monitoring by synthetic aperture radar(SAR)is introduced,and the DS-In SAR technique and the atmospheric error correction technique based on quadratic tree image segmentation are elaborated.The application of the In SAR technique towards the monitoring and identification of karst landslides in southwest China was summarized.(2)The Sentinel-1A ascending and descending orbit data covering Liupanshui city were used for disaster identification using Interferogram Stacking technology and quadtree image segmentation atmospheric error correction technology.The surface deformation maps,high resolution optical remote sensing images,geological and topographic information and visual analysis result maps were used for earlier identification and classification of disaster,and analyze the characteristics of landslide disaster.(3)The collected ALOS-2 data and Sentinel-1A ascending and descending data of Shuicheng District were used to identify the landslide in Shuicheng District,landslides in the Shuicheng District were identified and compared with the historical landslide catalogue map to obtain a current landslide catalogue map.(4)Multi-dimensional long time series deformation monitoring was derived for Pingdi landslide in Shuicheng District,Liupanshui City based on DS-In SAR and MSBAS techniques.Combined daily precipitation and geological data,the temporal and spatial evolution characteristics and instability model of landslide were analyzed,and the deformation model of Pingdi landslide induced by mining and driven by rainfall was revealed.(5)Multi-dimensional long time series deformation monitoring was derived for the Yanbiankou subsidencel.First,the basic situation of the Yanbiankou subsidence was introduced.Then,the temporal and spatial characteristics of deformation and the development process of deformation were analyzed.Finally,the triggering factors of the deformation were analyzed.The results showed that the subsidence near the slope would affect the stability of the front and the upper part of the slope,and rainfall was the one triggering factor of deformation.