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RecovUS: An Agent-Based Model of Post-Disaster Household Recovery
Journal of Artificial Societies and Social Simulation ( IF 3.506 ) Pub Date : 2020-01-01 , DOI: 10.18564/jasss.4445
Saeed Moradi , Ali Nejat

The housing sector is an important part of every community. It directly affects people, constitutes a major share of the building market, and shapes the community. Meanwhile, the increase of developments in hazard-prone areas along with the intensification of extreme events has amplified the potential for disaster-induced losses. Consequently, housing recovery is of vital importance to the overall restoration of a community. In this relation, recovery models can help with devising data-driven policies that can better identify pre-disaster mitigation needs and post-disaster recovery priorities by predicting the possible outcomes of different plans. Although several recovery models have been proposed, there are still gaps in the understanding of how decisions made by individuals and different entities interact to output the recovery. Additionally, integrating spatial aspects of recovery is a missing key in many models. The current research proposes a spatial model for simulation and prediction of homeowners’ recovery decisions through incorporating recovery drivers that could capture interactions of individual, communal, and organizational decisions. RecovUS is a spatial agent-based model for which all the input data can be obtained from publicly available data sources. The model is presented using the data on the recovery of Staten Island, New York, after Hurricane Sandy in 2012. The results confirm that the combination of internal, interactive, and external drivers of recovery affect households’ decisions and shape the progress of recovery.

中文翻译:

RecovUS:基于代理的灾后家庭恢复模型

住房部门是每个社区的重要组成部分。它直接影响着人们,构成了建筑市场的主要份额,并塑造了社区。同时,灾害多发地区的开发增加以及极端事件的加剧,扩大了灾害引起的损失的可能性。因此,住房恢复对于社区的整体恢复至关重要。在这种关系中,恢复模型可以帮助设计数据驱动的政策,通过预测不同计划的可能结果,更好地确定灾前缓解需求和灾后恢复优先事项。尽管已经提出了几种恢复模型,但对于个人和不同实体做出的决策如何相互作用以输出恢复的理解仍然存在差距。此外,整合恢复的空间方面是许多模型中缺失的关键。目前的研究提出了一个空间模型,用于模拟和预测房主的恢复决策,通过整合可以捕捉个人、社区和组织决策相互作用的恢复驱动因素。RecovUS 是一种基于空间代理的模型,其所有输入数据都可以从公开可用的数据源中获取。该模型使用纽约史泰登岛在 2012 年飓风桑迪之后的恢复数据呈现。结果证实,恢复的内部、互动和外部驱动因素相结合会影响家庭的决策并影响恢复进程. 目前的研究提出了一个空间模型,用于模拟和预测房主的恢复决策,通过整合可以捕捉个人、社区和组织决策相互作用的恢复驱动因素。RecovUS 是一种基于空间代理的模型,其所有输入数据都可以从公开可用的数据源中获取。该模型使用纽约史泰登岛在 2012 年飓风桑迪之后的恢复数据呈现。结果证实,恢复的内部、互动和外部驱动因素相结合会影响家庭的决策并影响恢复进程. 目前的研究提出了一个空间模型,用于模拟和预测房主的恢复决策,通过整合可以捕捉个人、社区和组织决策相互作用的恢复驱动因素。RecovUS 是一种基于空间代理的模型,其所有输入数据都可以从公开可用的数据源中获取。该模型使用纽约史泰登岛在 2012 年飓风桑迪之后的恢复数据呈现。结果证实,恢复的内部、互动和外部驱动因素相结合会影响家庭的决策并影响恢复进程. RecovUS 是一种基于空间代理的模型,其所有输入数据都可以从公开可用的数据源中获取。该模型使用纽约史泰登岛在 2012 年飓风桑迪之后的恢复数据呈现。结果证实,恢复的内部、互动和外部驱动因素相结合会影响家庭的决策并影响恢复进程. RecovUS 是一种基于空间代理的模型,其所有输入数据都可以从公开可用的数据源中获取。该模型使用纽约史泰登岛在 2012 年飓风桑迪之后的恢复数据呈现。结果证实,恢复的内部、互动和外部驱动因素相结合会影响家庭的决策并影响恢复进程.
更新日期:2020-01-01
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