Assessing the impact of geo-targeted warning messages on residents’ evacuation decisions before a hurricane using agent-based modeling
Assessing the impact of geo-targeted warning messages on residents’ evacuation decisions before a hurricane using agent-based modeling
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使用基于代理的建模评估飓风前地理定位警告消息对居民疏散决策的影响
DOI：
10.1007/s11069-021-04576-1
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发表时间：
2021
期刊：
影响因子：
3.7
通讯作者：
Wang, Yan
中科院分区：
文献类型：
--
作者：
Gao, Shangde;Wang, Yan
飓风危害的频率和强度不断增加，提高飓风预警有效性的紧迫性，特别是在激励高风险地区居民疏散方面。传统的飓风预警在发送粗略空间尺度（例如县级）的一般信息方面存在局限性，并且不包括针对更精细尺度的不同区域的居民的特定风险和命令。为了克服这些限制，人们提出了针对地理的飓风预警系统，但在实践中，现有系统的准确性较低，因为它们在定义预警区域时忽略了环境因素。现有文献主要集中于优化地理警报的传递过程，而在地理定义警报区域方面的努力有限。目前尚不清楚有针对性的警告在多大程度上促使居民在飓风来临前从高风险地区撤离。因此，我们开发了一种基于代理的模型（ABM）来模拟居民在地理定向警报下的疏散决策，该警报是根据飓风灾害和建筑环境的特征生成的。我们以飓风多里安的预报信息作为案例研究；然后根据地理目标警报、一般警报和基于风暴潮规划区的警报进行反导；然后我们比较了三个结果。该研究找到了一种利用建筑环境数据来地理定义警戒区域的有效方法。结果表明，有针对性的警告可以促使高风险地区更多居民撤离。这些发现有助于理解地理针对性警报对疏散的影响，并表明具有更具体内容的警报对于更精细的空间尺度的重要性。
The increasing frequency and intensity of hurricane hazards have raised the urgency of improving hurricane warning effectiveness, especially in terms of motivating the evacuation of people living in high-risk areas. Traditional warnings for hurricanes have limitations of sending a general message for coarse spatial scales (e.g., county level) and do not include specific risks and orders for residents in distinct areas of finer scales. To overcome these limitations, geo-targeted hurricane warning systems have been proposed, but in practice, the existing systems have low accuracy because they neglect environmental factors when defining warning zones. Extant literature has focused on optimizing the geo-delivering process of warnings with limited efforts on geo-defining warning zones. It is still unclear to what extent the geo-targeted warnings motivate residents to evacuate from high-risk areas before a hurricane. Therefore, we developed an agent-based model (ABM) to simulate residents’ evacuation decision-making under geo-targeted warnings, which were generated based on characteristics of both hurricane hazards and the built environment. We used forecasted information of Hurricane Dorian as a case study; then conducted the ABMs under geo-targeted warnings, a general warning, and warnings based on storm surge planning zones; then we compared the three outcomes. The research finds an effective way to geo-define warning zones using the built environment data. The result suggests that geo-targeted warnings can motivate more residents in high-risk areas to evacuate. These findings contribute to the understanding of the effect of geo-targeted warning on evacuation and suggest the importance of warnings with more specific contents for finer spatial scales.
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