*3.2. Population Density*

Disaster-affected bodies reflect the necessary conditions for disaster resilience, of which population density has a major influence on the number of earthquake casualties and the degree of destruction. High population density provides a vital motivation for the increase in earthquake casualties [42]. In this study, the population dataset that was collected from WorldPop includes raster data on the population distribution of China's mainland every five years from 2000 to 2020 (2000, 2005, 2010, 2015 and 2020). For those five raster datasets, we converted the population count value to population density and calculated the average density, which was implemented using the raster calculator tool in ArcGIS software. The general classification standard of population density was used to divide different population densities into four categroies: extremely sparsely (less than 1 people/km<sup>2</sup> ), sparsely (from 1 to 25 people/km2), moderately (from 25 to 100 people/km2 ), and densely populated (greater than 100). Through this standard, we divided China's population distribution dataset into four parts, as shown in Figure 7.

**Figure 7.** Distribution of classified population density in China's mainland.

#### *3.3. Geological Fault Density*

Disaster-formative environments refer to the natural and human geological background that affects disaster-inducing factors and disaster-affected bodies [17], among which geological faults are the zone blocks that bump into each other and generate shakes. Previous work [28] has demonstrated that the distance from a geological fault is correlated with the number of casualties that are caused by an earthquake. Therefore, we calculated the linear densities of strata faults in China using ArcGIS software. The linear densities were divided into three grades (high, moderate and low) by natural breaks. Figure 8 shows the spatial distribution of the classified geological fault densities in the study area.

**Figure 8.** Distribution of the classified strata fault densities in China's mainland.

#### *3.4. Overlay Analysis*

Overlay analysis is a frequently used geographic computing operation and a significant spatial analysis tool in GIS software, which is widely used in applications that are related to spatial computing [43]. This operation integrates different data layers and their corresponding attributes in the study area, which connects multiple spatial objects from multiple data sources and quantitatively analyzes the spatial range and characteristics of the interactions among different forms of spatial objects. Based on the feature selection results, geological faults are the birthplace of an earthquake, and humans are the victims of seismic disasters. In earthquakes with similar seismicity, denser strata fault lines and higher population density will lead to a greater risk to personnel safety [28]. For the above reasons, this study divided the study area into parts according to the variations in population density and strata fault density and established a corresponding partition standard. We developed a comprehensive partition standard that was used to overlay the classification results. Then, we divided the study area into risk areas of three grades: low risk, moderate risk, and high risk zones. The theory and procedure of the proposed spatial division method are illustrated in Figure 9.

**Figure 9.** Spatial division process.
