## 3 Study Area and Data
### Vulnerability Factors  
In order to evaluate the vulnerability of the study area, we adopted five vulnerability factors according to related studies and field investigations. As shown in Table 4, the natural breakpoint method was applied to divide the selected vulnerability factors into six categories. We classified the land use according to its inherent attributes, and the economic values of its classes were ranked as follows: unused land, water, grassland, woodland, farmland, and building land. Additionally, we referred to existing studies on vulnerability and assigned values to each class of the factors based on the classification results shown in Table 4 [57].  
The population density is an important social component and has a significant impact on social vulnerability [58; 59]. Industrial, commercial, and agricultural activities are often vigorous in regions with a high population density [60]. When landslides occur in these  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Vulnerability Factor**} & \multicolumn{6}{c}{**Value**} \\ \cline{2-7}  & **0.1** & **0.2** & **0.3** & **0.4** & **0.5** & **0.6** \\ \hline Population density (persons/km\({}^{2}\)) (\(VF_{1}\)) & 0–827 & 827–2893 & 2893–5475 & 5475–10,123 & 10,123–17,457 & 17,457–26,339 \\ \hline GDP density (CNY 10,000/km\({}^{2}\)) (\(VF_{2}\)) & 0–5 & 5–15 & 15–29 & 29–45 & 45–61 & 61–76 \\ \hline Road density (km/km\({}^{2}\)) (\(VF_{3}\)) & 0–0.27 & 0.27–1.06 & 1.06–2.34 & 2.34–3.92 & 3.92–6.02 & 6.02–9.58 \\ \hline Mine density (points/km\({}^{2}\)) (\(VF_{4}\)) & 0–0.10 & 0.10–0.32 & 0.32–0.55 & 0.55–0.77 & 0.77–1.00 & 1.00–1.38 \\ \hline Land use (\(VF_{S}\)) & Unused land & Water & Grassland & Woodland & Farmland & Building land \\ \hline \hline \end{tabular}
\end{table}
Table 4: The classification results of the vulnerability factors.  
regions, they often cause huge casualties and economic losses. As shown in Figure 6a, the zones with a high population density in the study area are mainly distributed in Kashi City and the surrounding Shufu County and Shule County. The GDP is a commonly used macroeconomic indicator that is adopted to measure the economic operation scale of a country or region [61]. We chose the GDP density as the evaluation factor to reflect the economic level of the study area. Generally speaking, the higher the GDP density, the higher the social vulnerability [58]. As shown in Figure 6b, the regions with a higher GDP density in the study area are mainly distributed in the urban region of Kashi and its surrounding counties and in the county town of Taskorgan County.  
Additionally, the road density (Figure 6c) is frequently used in vulnerability evaluation [14]. Roads are the main trunks of the transportation network in the study area, serving as the connection channels for various human activities between the local urban and rural regions. When roads are damaged by landslides, local personnel exchanges and goods transportation are hindered. Furthermore, it is possible for vehicles to be directly buried or damaged by landslides. Thus, the higher the road density, the higher the vulnerability. Additionally, the mine density (Figure 6d) has a significant impact on the vulnerability of the study area. Mining is a common engineering activity in such areas, especially in mountainous regions prone to landslides. As landslides tend to pose a serious threat to the safety of the mining area, the vulnerability also rises with an increasement in the mine density. Land use is also an important factor in vulnerability assessment as it is closely related to human activities. Generally, the higher the economic value of the land, the higher its vulnerability. The class of building land has the highest value of vulnerability and is essentially distributed in the towns along the KKH (Figure 6e).