薛莹莹, 贺山峰, 吴绍洪. 四川省自然灾害社会脆弱性评价研究[J]. 华北地震科学, 2018, 36(4): 33-40. DOI: 10.3969/j.issn.1003-1375.2018.04.005
引用本文: 薛莹莹, 贺山峰, 吴绍洪. 四川省自然灾害社会脆弱性评价研究[J]. 华北地震科学, 2018, 36(4): 33-40. DOI: 10.3969/j.issn.1003-1375.2018.04.005
XUE Ying-ying, HE Shan-feng, WU Shao-hong. Assessment of Social Vulnerability to Natural Disasters in Sichuan Province[J]. North China Earthquake Sciences, 2018, 36(4): 33-40. DOI: 10.3969/j.issn.1003-1375.2018.04.005
Citation: XUE Ying-ying, HE Shan-feng, WU Shao-hong. Assessment of Social Vulnerability to Natural Disasters in Sichuan Province[J]. North China Earthquake Sciences, 2018, 36(4): 33-40. DOI: 10.3969/j.issn.1003-1375.2018.04.005

四川省自然灾害社会脆弱性评价研究

Assessment of Social Vulnerability to Natural Disasters in Sichuan Province

  • 摘要: 以四川省为研究区域,从敏感度、应对能力、恢复力3个维度选取自然灾害社会脆弱性初始评价指标,采用相关系数法进行指标二次筛选,应用变异系数法确定指标权重,并采用TOPSIS模型对四川省各市(州)的自然灾害社会脆弱性进行评价。结果显示:成都市和攀枝花市的社会脆弱性最低,内江、眉山等4个市的自然灾害社会脆弱性等级最高;其空间分布格局大致为川西北地区社会脆弱性较低,川东南地区社会脆弱性较高。结合四川省各市具体情况,针对不同脆弱性等级的城市提出了降低社会脆弱性的对策建议,可为四川省的防灾减灾工作和可持续发展提供科学依据和参考。

     

    Abstract: Taking Sichuan province as the research region, this paper selects the initial evaluation indicators for social vulnerability of natural disaster from three aspects of sensitivity, coping capacity and resilience. The correlation coefficient method is adopted to filter the indicators and the variation coefficient method is applied to determine indexes' weights. The TOPSIS model is used to evaluate the social vulnerability of natural disasters in cities (prefectures) of Sichuan province. The results are manifested as follows. The social vulnerabilities of Chengdu and Panzhihua are the lowest, while those of Neijiang, Meishan and other two cities are the highest. The spatial distribution pattern is generally the fact that the social vulnerability of northwest Sichuan is lower than that of southeast Sichuan. Combining the specific situation of cities in Sichuan province, it proposes the countermeasures and suggestions of reducing social vulnerability for cities with different vulnerability levels, in order to provide scientific foundations and references for disaster prevention, mitigation capabilities and sustainable development of Sichuan province.

     

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