Abstract
This article presents an explorative analysis of community resilience to seismic hazard in the 2008 Wenchuan Earthquake area of Southwest China. We used a regression model to analyze the impact of 13 key socioeconomic and demographic variables on community resilience in 105 counties, based on data derived from population census and provincial statistical yearbooks of China. In this research, we argue that community resilience should be measured by the change of population growth rate (Δdp) instead of population growth rate (dp) when using socioeconomic data from a fast-growing country such as China. Using Δdp as the dependent variable resulted in a better regression model. To avoid the common multicollinearity problems among the independent variables, a principal component-based factor analysis was used to consolidate the socioeconomic variables into four comprehensive factors. The geographically weighted regression coefficient maps revealed the spatial pattern of the association of the variables with resilience. We also used the K-means cluster method to segment the study area into four subregions that exhibit localized characteristics defined by the regression coefficients. In this way, we could infer location-sensitive disaster management policies that help to enhance social resilience to seismic hazards.
Highlights
In a rapidly developing country like China, society becomes more vulnerable to seismic hazards because of the relatively low preparedness for disasters in comparison with the high speed growth of economy and population accompanied by fast urban expansion (Zheng et al 2015)
The study area is the region in southwestern China that was impacted by the Wenchuan Earthquake in 2008, including the epicenter and surrounding areas in Sichuan Province (Fig. 1a)
We make this assumption based on the following reasoning: (1) population growth rate is relatively stable in China unless there is an abrupt change in policies, such as birth control or fertility, (2) if the first assumption holds true, the change in population growth rate of the area during the 2005–2010 period should be associated with the major disaster event of 2008, and (3) communities with high resilience should maintain a relatively stable population growth rate when hit by such disasters
Summary
In a rapidly developing country like China, society becomes more vulnerable to seismic hazards because of the relatively low preparedness for disasters in comparison with the high speed growth of economy and population accompanied by fast urban expansion (Zheng et al 2015). 1), which considers resilience to be ‘‘...the ability to prepare and plan for, absorb, recover from, and more successfully adapt to adverse events over time.’’ Through an explorative analysis using regression models, this research identifies the economic and social characteristics of disaster-stricken communities that could affect their postdisaster recovery. Bruneau et al (2003) developed a quantitative framework that measured the speed of recovery using four resilience dimensions (technical, organizational, social, and economic) of four systems (electric power, water, hospital, and local response and recovery systems). Based on this framework, they evaluated how economic losses would affect resilience. We can derive location-specific disaster management plans that effectively assist to enhance the sustainability of those areas that are threatened by seismic hazards
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