长江科学院院报 ›› 2015, Vol. 32 ›› Issue (9): 52-57.DOI: 10.11988/ckyyb.20140259

• 水土保持与生态建设 • 上一篇    下一篇

荆州市洪灾社会脆弱性评价及其空间分异研究

冯滔1a,1b,李畅1a,1b,2,黄建武1a,1b,石倩1a,1b,阁承艳1a,1b,吴江华1a,1b   

  1. 1.华中师范大学 a.城市与环境科学学院;b.地理过程分析与模拟湖北省重点实验室,武汉 430079;2.民政部 减灾和应急工程重点实验室,北京 100124
  • 收稿日期:2014-04-04 出版日期:2015-09-20 发布日期:2015-09-10
  • 作者简介:冯 滔(1992-),男,贵州遵义人,助教,从事地球信息科学及灾害地理相关教学研究,(电话)18085218780(电子信箱)fngtao845@126.com。
  • 基金资助:
    国家自然科学基金项目(41101407);国家级大学生创新创业项目(201310511041);民政部减灾和应急工程重点实验室开放基金项目(LDRERE20120206)

Assessment of Social Vulnerability to Flood and Its Spatial Variation in Jingzhou City

FENG Tao1,2, LI Chang1,2,3,HUANG Jian-wu1,2,SHI Qian1,2, GE Cheng-yan1,2, WU Jiang-hua1,2   

  1. 1.College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China;
    2.Hubei Key Laboratory of Geographic Process Analysis and Simulation,Central China Normal University,Wuhan 430079, China;
    3.KeyLaboratory of Disaster Reduction and Emergency Response Engineering of the Ministry of Civil Affairs, Beijing 100124, China
  • Received:2014-04-04 Published:2015-09-20 Online:2015-09-10

摘要: 洪灾社会脆弱性评价对于灾区减灾、政府决策与预警具有重要的指导意义。首先,利用荆州市社会经济数据,从人口、经济、就业、教育、土地利用与住房条件、交通与通讯、灾害综合管理7个方面32个指标构建洪灾社会脆弱性评价指标体系,通过因子分析确定了5个主因子:综合经济因子、农业与人口因子、逃生因子、社会保障因子、住房因子;然后计算各因子得分以及各地区洪灾社会脆弱性总得分;最后,对地区洪灾社会脆弱性进行系统聚类和GIS制图分析。空间分异结果表明:监利县的洪灾社会脆弱性最高;江陵县、公安县、洪湖市、松滋市和石首市为中高社会脆弱性地区;荆州区为中低区;沙市区为最低区。研究成果揭示了荆州地区洪灾社会脆弱性的空间分布,有利于进一步的防灾减灾。

关键词: 洪灾, 社会脆弱性, 因子分析, 系统聚类, 荆州

Abstract: Assessment on the social vulnerability to flood is of guiding importance to the disaster reduction, decision-making and early warning in flood-stricken areas. According to the socio-economic data of Jingzhou city, we established an assessment index system involving 32 indicators in terms of population, economy, employment, education, land use and housing conditions, transportation and communication, and disaster management. Through factor analysis, we determined five main factors, namely, comprehensive economy, agriculture and population, rescue condition, social security system and housing conditions. Then we calculated the score of each factor and the regional total scores of social vulnerability. Finally, these factor scores are processed by hierarchical cluster procedures and geographic information system (GIS). The social vulnerability to flood is classified into serious, medium-serious, moderate, and gentle class. Among districts in Jingzhou city, Jianli belongs to serious class, Jiangling, Gong’an, Honghu, Songzi and Shishou belong to medium-serious class, Jingzhou district belongs to moderate and Shashi district belongs to gentle class.

Key words: flood disaster, social vulnerability, factor analysis, hierarchical cluster, Jingzhou

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