## 2 Materials and Methods
### Data  
The correct selection of conditioning factors is necessary to derive an accurate landslide susceptibility spatial distribution map [45]. Most previous studies categorized conditioning factors into five primary types: geological, hydrological, land cover, topographical, and other variables [46]. Therefore, we selected 14 conditioning factors that consider the environmental characteristics of the study area. All data were standardized to a common coordinate system and processed into aligned 1 km \(\times\) 1 km raster grids. These factors include two geological factors: the distance to faults and lithology. The hydrological factors include the distance to rivers, EAP, the stream power index (SPI), the sediment transport index (STI), and the topographic wetness index (TWI). The topographical factors include a digital elevation model (DEM), the slope, the topographic ruggedness index (TRI), and the slope aspect. The land cover factors include the normalized difference vegetation index (NDVI) and soil texture. In addition, human activities also play a major role in landslide activities [47], such as making any slopes progressively less stable during activities such as cutting of the slope, artificial filling, excavation, and the construction of terrace roads. Therefore, to consider the impact of human activities, the index for the distance to roads was selected. The data sources are listed in Table 1, where the lithology data are from the Global Lithological Map database, which was compiled by [PERSON] [48]. Two of the variables are directly extracted from the DEM datasets: the slope and the slope aspect. TWI is a commonly used topographic indicator that describes the potential for water accumulation and soil moisture in a given terrain. It combines the terrain's ability to accumulate water flow in relation to its surface drainage efficiency, making it a key factor in studying hydrological processes and surface moisture distribution. SPI is used to measure the erosive power of flowing water. It reflects the ability of water flow to interact with the terrain and is primarily used to study processes such as river sedimentation, erosion, and soil loss. TRI is used to measure the complexity or roughness of the terrain in an area, which is calculated as the difference in elevation between the highest and lowest pixel values. STI [49] is used to describe the ability of sediment to move under the influence of water flow. It combines flow velocity, discharge, slope, and other topographic features to assess the capacity of the water flow to transport sediment under different conditions. The formulas for these four indicators are as follows:  
\[\text{TWI}=\text{In}\bigg{(}\frac{A_{S}}{\tan(\beta)}\bigg{)} \tag{1}\] \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Data** & **Time** & **Resolution** & **Source** \\ \hline
**Precipitation** & 1961–2024 & Text data & China Meteorological Administration (CMA) \\
**River** & – & Line data & Chinese Academy of Sciences, Resource and \\  & & & Environment Science Data Center \\
**Landslide location** & 1974–2015 & Point data & China Water Resources Authority (CWRA) \\
**Road** & - & Line data & Chinese Academy of Sciences, Resource and \\  & & & Environment Science Data Center \\
**NDVI** & 2000–2022 & 1000 m & National Tibetan Plateau Data Center \\
**Elevation** & - & 30 m & Shuttle Radar Topography Mission (NASA SRTM) \\
**Soil texture** & - & 1000 m & Harmonized World Soil Database (HWSD) \\
**Fault** & - & Line data & Geoscientific Data \& Discovery Publishing System \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Environmental data used in the landslide analysis.