Zhou Yang, Li Ning, Wu Wenxiang, Wu Jidong, Shi Peijun
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China; Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs and Ministry of Education, Beijing, China.
Risk Anal. 2014 Apr;34(4):614-39. doi: 10.1111/risa.12193. Epub 2014 Mar 27.
The identification of societal vulnerable counties and regions and the factors contributing to social vulnerability are crucial for effective disaster risk management. Significant advances have been made in the study of social vulnerability over the past two decades, but we still know little regarding China's societal vulnerability profiles, especially at the county level. This study investigates the county-level spatial and temporal patterns in social vulnerability in China from 1980 to 2010. Based on China's four most recent population censuses of 2,361 counties and their corresponding socioeconomic data, a social vulnerability index for each county was created using factor analysis. Exploratory spatial data analysis, including global and local autocorrelations, was applied to reveal the spatial patterns of county-level social vulnerability. The results demonstrate that the dynamic characteristics of China's county-level social vulnerability are notably distinct, and the dominant contributors to societal vulnerability for all of the years studied were rural character, development (urbanization), and economic status. The spatial clustering patterns of social vulnerability to natural disasters in China exhibited a gathering-scattering-gathering pattern over time. Further investigations indicate that many counties in the eastern coastal area of China are experiencing a detectable increase in social vulnerability, whereas the societal vulnerability of many counties in the western and northern areas of China has significantly decreased over the past three decades. These findings will provide policymakers with a sound scientific basis for disaster prevention and mitigation decisions.
识别社会脆弱县和地区以及导致社会脆弱性的因素对于有效的灾害风险管理至关重要。在过去二十年中,社会脆弱性研究取得了重大进展,但我们对中国的社会脆弱性状况仍知之甚少,尤其是在县级层面。本研究调查了1980年至2010年中国县级社会脆弱性的时空格局。基于中国最近四次对2361个县的人口普查及其相应的社会经济数据,利用因子分析创建了每个县的社会脆弱性指数。应用探索性空间数据分析,包括全局和局部自相关分析,以揭示县级社会脆弱性的空间格局。结果表明,中国县级社会脆弱性的动态特征显著不同,在所研究的所有年份中,导致社会脆弱性的主要因素是农村特征、发展(城市化)和经济状况。中国自然灾害社会脆弱性的空间聚类模式随时间呈现出聚集—分散—聚集的模式。进一步调查表明,中国东部沿海地区的许多县的社会脆弱性正在明显增加,而中国西部和北部地区的许多县的社会脆弱性在过去三十年中显著下降。这些发现将为政策制定者提供灾害预防和减灾决策的坚实科学依据。