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中国地震灾害宏观人口脆弱性评估

Macro Assessment of Seismic Population Vulnerability in China

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【作者】 聂承静杨林生李海蓉

【Author】 NIE Chengjing1,2,YANG Linsheng1,Li Hairong1(1.Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China;2.Graduate University of Chinese Academy of Sciences,Beijing 100049,China)

【机构】 中国科学院地理科学与资源研究所中国科学院研究生院

【摘要】 地震灾害脆弱性不但是国家和地区中长期规划的基础,也是地震应急时的重要决策依据,因此地震灾害脆弱性评估是当前研究的热点和重点。本文首先介绍了地震灾害人口脆弱性定义,指出了地震灾害人口脆弱性的影响因子和影响模式;然后通过分析传统地震灾害人口脆弱性的宏观和微观评价方法和模型,利用人口总量、儿童人口比例、老年人口比例、人口密度和人均GDP 5个指标建立了地震灾害宏观人口脆弱性综合评价模型,并对全国各县市区的人口脆弱性进行了评估。结果表明:中国地震灾害人口脆弱性区域差异明显,东部地区人口脆弱性明显高于西部;人口总量是脆弱性的主要因素,宏观人口脆弱性综合评估模型对地震灾害人口脆弱性的修正作用显著。

【Abstract】 Seismic vulnerability assessment is not only the basis for a long-term planning,but also provides support for emergency decision-making in earthquake emergency,therefore it is a focus in current research of vulnerability.First,this paper introduced the definition of seismic population vulnerability,and proposed its vulnerability factors and influence patterns.Second,after researching the macro and micro assessment models and methods of seismic population vulnerability,the macro assessment model of seismic population vulnerability was established by using five indicators,which are the total population,proportion of the young,proportion of the the old,population density and per capita GDP.The seismic population vulnerability at county level was assessed across China.The results showed that the differences of seismic population vulnerability were significant,the vulnerability in the eastern region was higher than that in the western,and the total population was the key factor.The assessment model designed in this paper had a significant effect on the amendment to the population vulnerability of the earthquake.

【关键词】 地震灾害宏观人口脆弱性评估中国
【Key words】 seismicmacropopulation vulnerabilityassessmentChina
【基金】 中国科学院知识创新工程重要方向项目(KZCX2-YW-Q03-01);国家科技支撑计划课题(2008BAK50B05)
  • 【文献出处】 地理科学进展 ,Progress in Geography , 编辑部邮箱 ,2012年03期
  • 【分类号】C924.2;P315.9;X43
  • 【被引频次】28
  • 【下载频次】994
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