Understanding the Loss in Community Resilience due to Hurricanes using Facebook Data
Understanding the Loss in Community Resilience due to Hurricanes using Facebook Data
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DOI：
10.1016/j.ijdrr.2023.104036
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发表时间：
2023-02
期刊：
影响因子：
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通讯作者：
Tasnuba Binte Jamal;Samiul Hasan
中科院分区：
文献类型：
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作者：
Tasnuba Binte Jamal;Samiul Hasan
由于极端事件导致人类活动减少，在生产率、经济和社会福祉方面观察到了重大的负面影响。社区复原力是一个重要且被广泛使用的概念，用来理解极端事件对人口活动的影响。恢复力通常被定义为系统管理冲击并恢复到稳定状态以应对极端事件的能力。在这项研究中，分析了Facebook在应对飓风艾达时的聚合位置数据。利用灾难发生前、期间和之后Facebook用户数量的变化，社区韧性被量化为影响的程度和从极端情况中恢复的时间的函数。基于弹性函数，对路易斯安那州受影响的社区的人口活动弹性的瞬时损失进行了测量。受影响社区丧失复原力的原因有三种，包括有形基础设施的中断、飓风造成的灾害状况以及社区的社会经济特征。社区复原力的更大损失与电力和交通服务中断以及灾害条件等因素有关。相对于一个社区的中位数收入而言，在丧失韧性方面存在着社会经济差异。通过了解因灾害而减少的人口活动水平以及与韧性丧失相关的因素来了解社区的复原力，将使我们能够改进灾害准备，加强灾害管理实践，并制定更好的恢复政策，以加强基础设施和社区复原力。
Significant negative impacts are observed in productivity, economy, and social wellbeing because of the reduced human activity due to extreme events. Community resilience is an important and widely used concept to understand the impacts of an extreme event to population activity. Resilience is generally defined as the ability of a system to manage shocks and return to a steady state in response to an extreme event. In this study, aggregate location data from Facebook in response to Hurricane Ida are analyzed. Using changes in the number of Facebook users before, during, and after the disaster, community resilience is quantified as a function of the magnitude of impact and the time to recover from the extreme situation. Based on the resilience function, the transient loss of resilience in population activity is measured for the affected communities in Louisiana. The loss in resilience of the affected communities are explained by three types of factors, including disruption in physical infrastructures, disaster conditions due to hurricanes, and a community's socio-economic characteristics. A greater loss in community resilience is associated with factors such as disruptions in power and transportation services and disaster conditions. Socioeconomic disparities in loss of resilience are found with respect to a community's median income. Understanding community resilience using decreased population activity levels due to a disaster and the factors associated with losses in resilience will enable us improve hazard preparedness, enhance disaster management practices, and create better recovery policies towards strengthening infrastructure and community resilience.