## 1 Introduction  
Since the neotectonic movement, geological disasters occur frequently. As a kind of geological disaster, landslides represent a great threat to people's life and property safety. The deformation and destruction of landslides are closely related to tectonic activities, and the active period of tectonic movement is usually the high incidence period of landslides. The structural framework in the region dominates the spatial distribution of landslides. The extension orientation of faults, the areas of strong crustal uplift, the areas of strong undercutting of rivers, and the transition areas of crustal uplift and subsidence are all favorable areas for the development of landslides [1]. The complex topography and geomorphology of China lead to the frequent occurrence of geological disasters, the frequency of extreme weather and climate events is relatively high in many areas, and the uncertain factors of rainstorm in medium- and small-scale weather systems are increased. Rainfall will reduce the soil base force and shear strength, thus destroying the stability of the soil [2, 3]. On 24 June 2017, a landslide occurred in Xinmo Village, Maoxian County, Sichuan Province, resulting in 10 deaths and 73 missing. On 23 July 2019, under the influence of heavy rainfall, a massive landslide occurred in Pingdi Village, Jichang Town, Shuicheng County, Liupanshui City, Guizhou Province, killing 43 people and leaving 9 missing. Mountain landslides are highly hidden, and post-disaster investigations show that more than 70% of the landslides that have occurred have not been classified as hidden danger points [4]. Therefore, it is necessary to identify and monitor the hidden danger of landslide in the early stage. The traditional monitoring methods of landslide deformation include geometric leveling and the Global Navigation Satellite System (GNSS). Although the accuracy is high, the monitoring points are sparse, which is not conducive to the large-scale geological hazard survey [5,6]. Synthetic Aperture Radar Interferometry (InSAR) technology uses the phase information of repeatedly observed images to obtain small surface deformation, which plays an important role in the early identification and detection of landslides [7, 8, 9]. In 2014, the ESA Sentinel-1 satellite was successfully launched, and its radar data set is open to the world free of charge, which effectively promotes the application of InSAR in various fields and provides favorable data support for landslide deformation monitoring. In recent years, many scholars have carried out related landslide investigation using Insar technology. [PERSON] et al. (2016) obtained the post-disaster deformation evolution characteristics of a large area of landslide in Dashuchang town by using ground-based InSAR data [10]. [PERSON] et al. used laser radar, synthetic aperture radar interferometry, and other methods to extract and analyze the displacement of landslides in Sirobagarh area, Uttarakhand state, India [11]. [PERSON] and [PERSON] used interferometric synthetic aperture radar (INSAR) technology and C-band sensor-1A data to study the surface displacement of a large ancient landslide in Xuecheng Town, Lixian County, Sichuan Province [12]. [PERSON] et al. summarized the formation and evolution mechanism of the Zhangjiawan landslide through a field investigation and analysis of geological environmental conditions. Using limit equilibrium and numerical simulation methods to evaluate the stability of Zhangjiawan landslide [13], [PERSON] et al. used synthetic aperture radar interferometry (D-InSAR) and continuous scattering interferometry (PSI) techniques to evaluate and monitor the displacement caused by landslides in the Bam area and identified the relationship between climate conditions and landslide displacement [14].