## 4 Results
### Application of the WoE Model  
In terms of slope angle, the slope angle between 10\({}^{\circ}\)-20\({}^{\circ}\) (0.669) is more prone to landslide occurrence. Additionally, the \(W_{f}\) values of the region where slope angles larger than 50\({}^{\circ}\) are 0. For the slope aspect factor, \(W_{f}\) was the highest for south-facing (0.769). Furthermore, southeast-facing (0.310) and east-facing (0.001) also had a positive correlation with landslide occurrence. In the case of elevation, most landslides were distributed in the classes of 442-600 m (0.485), 600-800 m (0.968), and 800-1000 m (0.717). When the elevation was larger than 1200 m, elevation had an inhibitory effect on landslides. In the case of plan curvature, flat areas had a more important impact on landslides, whereas the \(W_{f}\) values of convex areas and concave areas were 0.106 and \(-\)0.203, respectively. In the case of profile curvature, the \(W_{f}\) values of the concave class, flat class, and convex class are 0.042, 0.751, and \(-\)0.271, respectively. For TWI, the highest \(W_{f}\) value was observed for the interval of 5-6 (0.497) while the class \(<\)4 (\(-\)0.945) had the lowest value. For SPI, the class \(<\)20 (0.277) had the highest \(W_{f}\) value, and the areas of SPI 20-40 and \(>\)60 were negative for landslides. For STI, the class \(<\)10 had the highest \(W_{f}\) value of 0.361, while the class 20-30 had the lowest value of \(-\)0.853. In the case of distance to rivers, the classes of \(<\)200 m (0.168) and 600-800 m (0.133) occupied higher \(W_{f}\) values when compared to the other classes. In the case of distance to roads, the class of \(<\)300 m (0.904) had a more intimate correlation with landslide occurrence. In the case of distance to faults, it can be seen that the class \(>\)4000 m had the highest \(W_{f}\) value of 0.246. For soil, citric camisol (1.177) and eutric planosol (1.516) were more likely to induce landslides due to the dramatic falling of soil strength under saturated conditions [85]. For land use, farmland (1.351) had the highest probability of landslide occurrence, which may be essentially caused by irrigation. According to the \(W_{f}\) values of NDVI, the class of 0.36-0.44 (1.121) mainly contributed to landslide occurrence, while the lowest value was for the class of 0.52-0.65 (\(-\)2.212), which indicates that high vegetation coverage can restrain landslides. In the case of lithology, the \(W_{f}\) values of group 1 (Q) (0.588), group 11 (Ar) (0.594), and group 12 (Pt, Pz) (0.417) were larger than 0, indicating that these lithological groups had the highest susceptibility to landslide. In the case of rainfall, the range between 1100-1200 mm/yr (1.030) showed high susceptibility for landslide occurrence. The calculated \(W_{f}\) values for all landslide conditioning factors were summed using the following equation to construct the landslide susceptibility map (LSM): \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Landslide Conditioning Factors**} & \multicolumn{2}{c}{**Collinearity Statistics**} \\ \cline{2-3}  & **Tolerance (TOL)** & **Variance inflation factors (VIF)** \\ \hline Slope angle & 0.761 & 1.315 \\ Slope aspect & 0.883 & 1.133 \\ Elevation & 0.650 & 1.539 \\ Plan curvature & 0.714 & 1.400 \\ Profile curvature & 0.855 & 1.170 \\ TWI & 0.828 & 1.208 \\ SPI & 0.434 & 2.303 \\ STI & 0.402 & 2.489 \\ Distance to rivers & 0.946 & 1.057 \\ Distance to roads & 0.779 & 1.284 \\ Distance to faults & 0.908 & 1.101 \\ NDVI & 0.774 & 1.292 \\ Soil & 0.642 & 1.557 \\ Land use & 0.627 & 1.595 \\ Lithology & 0.765 & 1.308 \\ Rainfall & 0.664 & 1.507 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Multicollinearity analysis. \[