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Empirical Predictive Modeling Approach to Quantifying Social Vulnerability to Natural Hazards
Annals of the American Association of Geographers ( IF 3.2 ) Pub Date : 2020-12-08
Yi (Victor) Wang, Paolo Gardoni, Colleen Murphy, Stéphane Guerrier

Conventionally, natural hazard scholars quantify social vulnerability based on social indicators to manifest the extent to which locational communities are susceptible to adverse impacts of natural hazard events and are prone to limited or delayed recoveries. They usually overlook the different geographical distributions of social vulnerability at different hazard intensities and in distinct response and recovery phases, however. In addition, conventional approaches to quantifying social vulnerability usually establish the relationship between social indicators and social vulnerability with little evidence from empirical data science. In this article, we introduce a general framework of a predictive modeling approach to quantifying social vulnerability given intensity during a response or recovery phase. We establish the relationship between social indicators and social vulnerability with an empirical statistical method and historical data on hazard effects. The new metric of social vulnerability given an intensity measure can be coupled with hazard maps for risk analysis to predict adverse impacts or poor recoveries associated with future natural hazard events. An example based on data on casualties, house damages, and peak ground accelerations of the 2015 Gorkha earthquake in Nepal and pre-event social indicators at the district level shows that the proposed approach can be applied for vulnerability quantification and risk analysis in terms of specific hazard impacts.



中文翻译:

量化自然灾害的社会脆弱性的经验预测建模方法

传统上,自然灾害学者基于社会指标来量化社会脆弱性,以表明当地社区在多大程度上易受自然灾害事件的不利影响并容易受到有限或延迟的恢复。但是,他们通常忽略了在不同危险程度以及不同的响应和恢复阶段中社会脆弱性的不同地理分布。此外,传统的量化社会脆弱性的方法通常在很少有经验数据科学证据的情况下建立社会指标与社会脆弱性之间的关系。在本文中,我们介绍了一种预测建模方法的一般框架,用于量化在响应或恢复阶段给定强度下的社会脆弱性。我们使用经验统计方法和危害影响的历史数据建立社会指标与社会脆弱性之间的关系。给定强度度量的新的社会脆弱性度量可以与危害图一起进行风险分析,以预测与未来自然灾害事件相关的不利影响或不良恢复。根据有关尼泊尔2015年Gorkha地震的人员伤亡,房屋损坏和地面加速度峰值的数据以及地区一级的事前社会指标得出的示例表明,该建议的方法可以用于具体的脆弱性量化和风险分析危害影响。给定强度度量的新的社会脆弱性度量可以与危害图一起进行风险分析,以预测与未来自然灾害事件相关的不利影响或不良恢复。根据有关尼泊尔2015年Gorkha地震的人员伤亡,房屋损坏和地面加速度峰值的数据以及地区一级的事前社会指标得出的示例表明,该建议的方法可以用于具体的脆弱性量化和风险分析危害影响。给定强度度量的新的社会脆弱性度量可以与危害图一起进行风险分析,以预测与未来自然灾害事件相关的不利影响或不良恢复。根据有关尼泊尔2015年Gorkha地震的人员伤亡,房屋损坏和地面加速度峰值的数据以及地区一级的事前社会指标得出的示例表明,该建议的方法可以用于具体的脆弱性量化和风险分析危害影响。

更新日期:2020-12-08
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