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Mapping Social Vulnerability and Exposure Parameters to Extreme Heat Events in Missouri.

机译：将社会脆弱性和暴露参数映射到密苏里州的极端高温事件。

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摘要

Extreme heat events are considered to be the natural disasters with most deaths in the United States. Due to the global warming phenomenon, extreme heat events are expected to increase in frequency, duration, and intensity in the coming years. Multiple heat-specific social vulnerability studies have been published in the literature recently but many focused on metropolitan areas with very few studies including rural areas. In this study we aimed to apply two common methods of social vulnerability assessment to study county-level statewide extreme heat vulnerability and propose a new methodology for vulnerability prediction.;The coincidence matrix analysis was carried out to evaluate the performance and compare the different methodologies by comparing the results of each method to the hyperthermia morbidity rates per county. The overall coincidence percentage was 32.6% for the EHRI, 37.4%, for the CEVI, and 83.2% for the PHV method. The PHV method using decision tree analysis outperformed EHRI and CEVI in extreme- heat social vulnerability assessment. The decision tree-based approach provided a reliable, easy to implement and interpret approach for identifying heat vulnerable counties.;The state of Missouri was chosen for the extreme heat vulnerability assessment because Missouri is expected to have more extreme heat events in the future, and because social vulnerability has not been studied recently for the entire state. Fifteen heat vulnerability indicator variables were included in the analysis, namely: population density; age over 65; age under 5; disabled over 65; poor; living alone; race other than White; low education; low English skills; no vehicles; unemployed; outdoor workers; land cover; crime index; and heat exposure. The two methods were; the Extreme Heat Risk Index (EHRI) using the percentile ranking methodology, and the Combined Exposure Vulnerability Index (CEVI) using the principal component analysis statistical method. The study also proposed a new method, Predictive Heat Vulnerability (PHV), using the decision tree analysis. The spatial distribution of heat vulnerability was different between the three different methods, but in general, the southeast counties of Missouri had the highest heat vulnerability scores for all methods. Urban counties had low vulnerability scores.
机译：在美国，极端高温事件被认为是自然灾害，死亡人数最多。由于全球变暖现象，预计未来几年极端热事件的频率，持续时间和强度都会增加。最近在文献中发表了多种针对热的社会脆弱性研究，但许多研究集中在大都市地区，很少有研究包括农村地区。在这项研究中，我们旨在应用两种常见的社会脆弱性评估方法来研究县级全州范围内的极端高温脆弱性，并提出一种新的脆弱性预测方法。;进行符合矩阵分析以评估绩效并比较不同的方法。将每种方法的结果与每个县的热病发病率进行比较。 EHRI的总重合率为32.6％，CEVI的总重合率为37.4％，PHV方法的总重合率为83.2％。在极端热社会脆弱性评估中​​，使用决策树分析的PHV方法优于EHRI和CEVI。基于决策树的方法为识别热脆弱县提供了可靠，易于实施和解释的方法。密苏里州被选为极端热脆弱性评估，因为预计未来密苏里州将发生更多极端热事件，并且因为最近尚未针对整个州研究社会脆弱性。分析中包括了15个热脆弱性指标变量，即：人口密度； 65岁以上； 5岁以下； 65岁以上的残疾人士；较差的;一个人生活;怀特以外的种族；低学历；英语水平低；没有车辆；失业户外工人；土地覆盖；犯罪指数和热暴露。两种方法分别是：使用百分位数排名方法的极端热风险指数（EHRI），以及使用主成分分析统计方法的综合暴露风险指数（CEVI）。该研究还使用决策树分析提出了一种新方法，即预测热脆弱性（PHV）。三种方法之间的热脆弱性空间分布不同，但总体而言，密苏里州东南部县在所有方法中的热脆性得分最高。市区县的脆弱性得分较低。

著录项

  • 作者

    Bakhsh, Heba.;

  • 作者单位

    University of Illinois at Chicago.;

  • 授予单位 University of Illinois at Chicago.;
  • 学科 Public health.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 123 p.
  • 总页数 123
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 遥感技术;
  • 关键词

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