# Research on Risk Assessment Method for Land Subsidence in Tangshan Based on Vulnerability Zoning
## 2 Materials and Methods  
### ArcGIS-Based Vulnerability Zoning of Ground Subsidence in Tangshan City  
The primary determinants of the ground subsidence in Tangshan City encompass factors such as the lithology, rainfall, population density, road network density, seismic acceleration, and river network density. Spatial analysis, conducted via ArcGIS, was employed for each of these influencing factors to derive their respective classifications. The consolidated classification results of these factors facilitated the generation of a vulnerability zoning map for the ground subsidence in Tangshan City. The delineation of the vulnerability zones within Tangshan City and the subsequent research on the evaluation of the ground subsidence hazard hinged on the acquisition of pertinent data, which formed the bedrock of this study. A variety of data collection methods, as outlined in Table 1, were utilized to ensure a comprehensive and robust analysis. \begin{table}
\begin{tabular}{c c c} \hline
**No.** & **Data Type** & **Data Source** \\ \hline
1 & DEM (Digital Elevation Model) data & GDEMV3 30M ASTGTMV003\_N39E118 \\
2 & Geological data & Geological Cloud, Tangshan City 1:200,000 Geological Map \\
3 & Groundwater data & Geological cloud and well-logging monitoring data \\
4 & Rainfall data & China Meteorological Station \\
5 & Peak ground acceleration and seismic period & “Seismic Ground Motion Parameter Zoning Map of China” [36] \\  & Distribution of historical goal (abandoned mining & \\
6 & area after the completion of mining) subsidence & Detailed Comprehensive Disaster Prevention and Reduction Plan of Tangshan City \\  & & \\  & Distribution of subsidence areas, seismic liquefaction, and fault zones & Detailed Comprehensive Disaster Prevention and Reduction Plan of Tangshan City \\
8 & Road data & Open street map website \\
9 & Water system data & National Geographical Information Resource Catalog Service System \\
10 & Collection of subsidence points in Tangshan City & Literature compilation, news reports \\
11 & Study area map & Google Earth \\ \hline \end{tabular}
\end{table} 
Table 1: Data source introduction. The geological lithology and rainfall patterns within Tangshan City were segmented into five distinct categories. The specific values attributed to each category for both the lithology and rainfall are detailed in Table 2. The classification maps, which visually represent the distribution of the geological lithology and July rainfall across the city, are depicted in Figures 1 and 2, respectively. The population density and road network density within Tangshan City were categorized into five distinct levels. The specific values assigned to each level for both the population density and road network density are detailed in Table 3. The classification maps, which visually represent the population density distribution and road network density across the city, are depicted in Figures 3 and 4, respectively. Figure 3: Classification of population density. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Population Density** & **Value** & **Road Network** & **Value** \\ (**People/km2**) & **Value** & **Density (m -1)** & **Value** \\ \hline \(<\)340.69 & 1 & 0–1.78 & 1 \\
340.69–496.58 & 2 & 1.78–4.63 & 2 \\
496.58–635.15 & 3 & 4.63–9.61 & 3 \\
635.15–1276.03 & 4 & 9.61–22.26 & 4 \\ \(>\)1276.03 & 5 & \(>\)22.26 & 5 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Assigned values of population density and road network density in Tangshan City. Figure 2: Rainfall classification. Figure 6: Classification of river network density. Utilizing the raster calculator tool in ArcGIS, the six datasets were subjected to a simple raster-weighted overlay analysis. This process generated the vulnerability zoning map of the ground subsidence for Tangshan City, as depicted in Figures 7 and 8. Figure 7: Classification of collapse susceptibility.