Landslide Monitoring And Stability Research Based On Time Series InSAR Technology

Our country has a vast territory,diverse environment and climate,and many kinds of geological disasters,among which the occurrence frequency of landslide is high and seriously endangers people's life safety.Therefore,the monitoring of landslide deformation should be strengthened.Due to the complex terrain conditions in mountainous areas,the traditional monitoring methods are limited,resulting in inaccurate data obtained by analysis.InSAR technology can monitor and obtain ground deformation information of landslide all day and all day,and the accuracy of monitoring results can reach millimeter level.In this paper,the eastern part of Toktara Prefecture was taken as the study area,and ALOS PALSAR-2 data was used as the data source.The surface deformation information of the study area was obtained by SBAS-InSAR method,and the landslide deformation points in the study area were extracted to replace the historical landslide points.Logical regression model was used to evaluate the landslide susceptibility in the study area.The main research work and conclusions are as follows:(1)SBAS-InSAR technology was used to conduct interference processing on10-scene L-band ALOS PALSAR-2 data,and the surface deformation information in the study area was extracted,and 11 deformation areas were extracted.(2)The radar line-of-sight deformation rate results were converted into slope deformation results,and under the condition that the slope deformation rate was less than 0 and the slope of the landslide occurred was greater than 10°,49133 landslide deformation points were screened.At the same time,kernel density analysis was carried out on the selected landslide deformation points.Compared with the spatial distribution of historical landslide data,82.82% of the historical landslide points were in the density division of landslide deformation points.(3)The annual deformation rate of the study area extracted by SBAS-InSAR technology was selected,and the slope,slope aspect,fluctuation degree,elevation and distance from the river system were extracted by ASTER GDEM with an accuracy of30 m to form the evaluation index of landslide susceptibility.Taking Arc GIS as the platform and SPSS as the software,the importance of the classification interval of each impact factor is analyzed by using the deterministic coefficient method,and the correlation among the factors is analyzed.(4)Logical regression model was used to evaluate the landslide stability in the study area.The stability of the landslide is analyzed based on the annual deformation rate,slope,slope aspect,fluctuation,elevation and distance from the river system.The results show that the proportion of landslide deformation points in medium,low and very low stability is 71.45%,and the proportion of historical landslide points in medium,low and very low stability is 73.62%.The area of low and very low stability area is 378.1996km2,accounting for 17.65% of the total area.Slope,slope direction,undulation,elevation and distance from the river system were used to analyze the stability of the landslide.The results show that 66.23% of the landslide deformation points are in the area with medium stability or below,and 68.71% of the historical landslide points are in the area with medium,low and very low stability.The area of low and very low prone areas is 330.4449km2,accounting for 15.42% of the total area.According to the comparative analysis,the landslide stability evaluation results with the annual deformation rate added are 5.22% higher at the landslide deformation point and 4.91% higher at the historical landslide point,respectively,and the area of low and very low stability is 47.7547km2 more,which indicates that the data obtained by InSAR technology is relatively accurate.The reliability of InSAR data used to analyze the stability of the region is proved.