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 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 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 three key landslides in Jichang Town, Yujiaying and Fana, 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.

中文翻译：

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贵州省滑坡InSAR与光学遥感早期识别与监测

我国贵州省地形地貌复杂，加上强降水的气候条件，使贵州省滑坡灾害频繁发生。为避免灾害对人民生命和经济财产造成损害，迫切需要一种可靠的滑坡早期识别方法和滑坡监测方法。传统的滑坡识别和监测方法存在局限性。InSAR技术在大尺度滑坡识别和监测方面具有独特优势，但基于单一变形值的滑坡识别结果是片面的。所以，本文利用Sentinel-1A雷达卫星影像数据，利用InSAR技术和光学遥感技术，在贵州省六盘水市、铜仁市、贵阳市等地区开展大面积地表变形监测识别危险变形区。结合基于时间序列归一化植被指数和滑坡发育环境要素的潜在滑坡识别方法，对研究区滑坡隐患进行调查。本文采用时间序列InSAR技术对冀昌镇、于家营、法那三个重点滑坡进行监测，及时掌握滑坡运动状态。