Abstract: The topography and landforms of Guizhou province in China are complicated, and the climatic conditions of heavy precipitation make landslide disasters in Guizhou province occur frequently. To avoid damage bringing to people's lives and economic property caused by disasters, a reliable early landslide identification method and landslide monitoring method are urgently needed. Traditional landslide identification and monitoring methods have limitations. InSAR technology has unique advantages in large-scale landslide identification and monitoring, but landslide identification results based on a single deformation value are one-sided. Therefore, this paper uses Sentinel-1A Radar satellite image data and uses InSAR technology and optical remote sensing technology togather to carry out large-scale surface deformation monitoring and identification of dangerous deformation areas in Liupanshui city, Tongren city, Guiyang city and other regions in Guizhou province. The potential landslide identification methods based on the time series normalized difference vegetation index and landslide development environment elements are combined to investigate hidden landslide hazards in the study area. In this paper, time series InSAR technology is used to monitor key landslides in Yujiaying, to grasp the movement status of the landslide in time. The method of landslide identification and monitoring in this paper is of great significance for disaster prevention and management in Guizhou province.

Key words: Guizhou province, landslide identification and monitoring, optical remote sensing, InSAR, SBAS