## 2 Materials and Methods  
### Study Area and Landslide Impact Factors  
In this research, Jiuzhaigou County was investigated, which covers the northwest of Sichuan province. The research area covers an area of 642.97 km\({}^{2}\) (Figure 1). The research area comprises most of the Jiuzhaigou National Nature Reserve and is located between 33.12\({}^{\circ}\) and 33.35\({}^{\circ}\) N and 103.74\({}^{\circ}\) and 103.98\({}^{\circ}\) E. The area is high in the south and low in the north, with deep valleys and great differences in elevation, due to glaciers and obvious hydrological influences, ranging from 1830 to 4488 m [30]. The research region has a high stream density and a well-developed Karst landform [31]. The region has a complex geological background with a wide distribution of carbonates, and significant Karst action [32]. Jiuzhaigou is located in a climate transition zone between the wet Sichuan Basin and the semiarid Tibetan Plateau [33]. Annual precipitation ranges from 539 to 771 mm on average, with the wet season accounting for more than 80% of total precipitation [34]. On 8 August 2017, the MS 7.0 earthquake struck the Jiuzhaigou country, resulting in a number of co-seismic landslides. These landslides were mostly shallow rockslides and rockfalls, according to field surveys conducted by [PERSON] et al. [4; 6], which seriously damaged roads, blocked rivers, and closed scenic areas. Some landslides occurred in the area after the earthquake, and landslide susceptibility changed [35; 36]. In order to obtain the LSM of the area, SAR data, optical remote sensing data, geographical data, landslide impact factors, and landslide inventories were applied to this study [37; 38; 39]. Tables 1 and 2 describe the source, type, and purpose of these data. The coverage region of Sentinel-1 SAR scenarios is depicted in Figure 1. Between 2017 and 2020, we used 82 descending track SAR images from Sentinel-1 satellites, spanning the research region in Jiuzhaigou. Landslide inventories, which were often derived via surface surveys and remote sensing identification, represented the spatial distribution and scale of landslides in the region [40; 41; 42]. The landslide inventory included the geological survey report (provided by the Sichuan Institute of Ecological Restoration of Land Space and Geological Disaster Prevention) and earthquake-induced landslide (EIL) locations visually interpreted by [PERSON] et al. (Provided by National Cryosphere Desert Data Center) [43]. Figure 2 shows a map of landslide locations combining the above data, including earthquake-induced landslides (red) and pre-earthquake landslides (purple). As shown in Figure 3, twelve causative factors were chosen, based on the natural conditions and data available in the study area: elevation, distance from a fault, NDVI, aspect, rainfall, topographic water index, LULC, slope, plan/profile curvature, lithology and distance from a river [44; 45; 46; 47; 48]. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No.** & **Data** & **Resolution** & **Source** & **Purpose** \\ \hline
1 & DEM & 30 & SRTM 30 m & Preparing factor maps \\
2 & Remote sensing images & 30 & Landsat 8 Satellite & NDVI \\
3 & Geological map & 30 & Sichuan Ecological and & \\  & & & Environmental Restoration Institute & Lithology and faults \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Data and data sources.