Landslide Identification and Deformation Monitoring Analysis in Xining City Based on the Time Series InSAR of Sentinel-1A with Ascending and Descending Orbits

Abstract

Landslide disasters occur frequently in the Loess Plateau of China, which seriously threatens the economic development and the safety of life and property. Using time-series Interferometric synthetic aperture radar (InSAR) to identify potential active landslides and monitor their deformation is conducive to prevent and reduce the harm caused by disasters. This paper takes Xining City as the research area, using the sentinel-1A radar images ascending orbit and descending orbit, the ground surface deformation rate and time series variables in the study area were obtained by using two time series InSAR technologies of small baseline subset (SBAS) and permanent scatterer (PS).Through the cross inspection of the deformation results detected by SBAS and PS technology, it is found that the deformation characteristics detected by SBAS technology are richer in space, the cumulative deformation variables are more robust, and have more advantages in the identification of active landslides. Compared with GNSS monitoring data, the cumulative deformation of landslide detected by PS technology has better fitting degree and higher accuracy. The experimental results show that time-series InSAR technology can effectively identify and monitor loess landslides, which provides a scientific basis for regional disaster prevention and control.