## 4 Results and Discussion
### Application of the VR Model
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Independent Variable** & **Classes** & \(\boldsymbol{V_{jk}}^{*}\boldsymbol{V_{jk}}\) & \(\boldsymbol{T^{*}/T}\) & \(\boldsymbol{VR_{jk}}\) \\ \hline \multirow{8}{*}{Land-use} & Farmland & 0.2981 & 0.3063 & 0.9734 \\  & Forest & 0.0199 & 0.4000 & 0.0498 \\  & Grassland & 0.4029 & 0.2345 & 1.7180 \\  & Shrubland & 0.0000 & 0.0021 & 0.0000 \\  & Wetland & 0.0000 & 0.0000 & 0.0000 \\  & Water & 0.0000 & 0.0006 & 0.0000 \\  & Resident land & 0.1313 & 0.0367 & 3.5780 \\  & Bareland & 0.1478 & 0.0198 & 7.4512 \\ \hline \multirow{2}{*}{Lithology} & Sandstone & 0.4169 & 0.2848 & 1.4640 \\  & Loess & 0.5831 & 0.7152 & 0.8152 \\ \hline \multirow{8}{*}{Distant to road (m)} & \textless{}50 & 0.5289 & 0.4101 & 1.2897 \\  & 50–150 & 0.2454 & 0.9813 & 0.2501 \\  & 150–300 & 0.0100 & 0.8237 & 0.0122 \\  & 300–500 & 0.1824 & 0.9151 & 0.1994 \\  & 500–800 & 0.0333 & 1.1883 & 0.0280 \\  & \textgreater{}800 & 0.0000 & 0.0000 & 0.0000 \\ \hline \multirow{8}{*}{Distant to river (m)} & \textless{}50 & 0.7368 & 1.1093 & 0.6642 \\  & 50–150 & 0.2543 & 0.9612 & 0.2645 \\  & 150–300 & 0.0089 & 0.8106 & 0.0110 \\  & \textgreater{}300 & 0.0000 & 0.0000 & 0.0000 \\ \hline \multirow{2}{*}{Profile curvature} & Concave slope & 0.5151 & 0.5384 & 0.9567 \\  & Convex slope & 0.4849 & 0.4616 & 1.0505 \\ \hline \multirow{8}{*}{Rainfall} & Less rainfall area & 0.2051 & 0.9998 & 0.2052 \\  & Medium rainfall area & 0.3779 & 1.0002 & 0.3779 \\ \cline{1-1}  & More rainfall area & 0.2415 & 0.9996 & 0.2416 \\ \cline{1-1}  & Heavy rainfall area & 0.1755 & 0.9996 & 0.1755 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cont. found in the other places since slopes tend be covered by a layer of thin colluvium that is prone to landslides [35; 36]. The NDVI is a measure of surface reflectance to give a quantitative estimate of biomass and vegetation growth [37]. The value of NDVI in the study area ranges from \(-0.27\) to \(0.59\) in the summer. Generally, the larger the NDVI value is, the higher the vegetation coverage is. In the case of NDVI, there is no landslide in the classes of no cover and high cover. In the other classes, the VR value reflected the probability of landslide volume increased with the increase of the plant cover. In other words, the vegetation didn't play important roles in the decrease of the landslide amount. There are positive and negative effects of vegetation cover on landslides. Vegetation roots can reduce the creep of the soil layer by increasing the shear strength of soil, which is negatively correlated with the amount of landslide erosion. On the other hand, in the field investigation of small watersheds, it was found that with the increase of vegetation coverage, the runoff on the slope increased, thereby increasing the gully erosion of the watershed [38]. Plant root splitting may also promote the occurrence of landslide erosion. Land-use is another factor used to consider the natural and man-made environmental impacts on the land surface. The main land use types in the study area were forestland and cropland, accounting for 40% and 31% of the total study area, respectively. Secondly, the grassland accounted for 23% of the total study area. Other classes accounted for a combined 6% of the total study area. The bareland had the highest VR value of 7.4512, followed by resident land (3.5780) and grassland (1.7180). The class of forest and farmland had the VR values of 0.9734 and 0.0498, respectively. In the shrubland, wetland, and water, the VR values are zero. The results indicated surface attachment plays an important role in slope stability compared with bareland, and in our case, the cultivated areas are less prone to landslides when compared to other land cover types. This may be due to positive impacts of land management with better water and soil control measures on slope stability [39]. Different geological formations have different compositions and structure, which contribute to the strength of the material.