Integrating Place Attachment into Housing Recovery Simulations to Estimate Population Losses
Integrating Place Attachment into Housing Recovery Simulations to Estimate Population Losses
复制标题
将地方依恋融入住房恢复模拟中以估计人口损失
DOI：
10.1061/(asce)nh.1527-6996.0000571
复制
发表时间：
2022
影响因子：
2.7
通讯作者：
Baker, Jack W.
中科院分区：
文献类型：
--
作者：
Costa, Rodrigo;Wang, Chenbo;Baker, Jack W.
灾难发生后，一个社区的居民可能会从他们受损的房屋中流离失所，导致昂贵和长期的破坏，许多人选择永久搬离。人口减少可能会阻碍复苏，并加剧社区间的不平等。本研究考虑了家庭的地方依恋，并确定了低地方依恋以及昂贵和缓慢的灾后恢复的群体。我们开发了一个框架，将地方依恋因素整合到住房恢复模拟中。我们使用来自美国住房调查的数据来开发住房和社区满意度模型，并确定居民依恋最少的社区。计算模拟框架用于模拟震后社区的住房恢复，并评估预期成本和时间框架。我们使用低地方依恋、高成本和缓慢恢复的三位一体来识别易于永久搬离社区的家庭。一个关于旧金山附近假定地震后住房恢复的案例研究证明了该方法的应用。我们发现，在一些社区，大约10%的人口在大地震后倾向于搬走。低收入家庭、租房者和那些住在老房子里的人最有可能有较低的地方依恋，经历昂贵和缓慢的恢复。虽然现有的方法依赖于启发式，但本文的方法和结果提供了定量的方法来评估潜在的种群损失，并为减少它们的努力提供信息。将地方依恋整合到住房恢复模拟的框架是通用的，并采用了公开可用的信息，使其可转移到其他社区。
Following a disaster, residents of a community may be displaced from their damaged homes, leading to expensive and lengthy disruption, with many choosing to move away permanently. Population losses may hinder recovery and exacerbate inequalities across neighborhoods. This study considered household place attachment and identified groups with low place attachment along with expensive and slow postdisaster recovery. We developed a framework to integrate place attachment considerations into housing recovery simulations. We used data from the American Housing Survey to develop housing and neighborhood satisfaction models and identify the neighborhoods with the least-attached residents. A computational simulation framework was used to simulate postearthquake housing recovery for a community and assess expected costs and time frames. We used the triad of low place attachment, high cost, and slow recovery to identify households prone to permanently moving away from their communities. A case study of housing recovery after a hypothetical earthquake near San Francisco demonstrated the application of the methodology. We found that about 10% of the population in some neighborhoods are prone to moving away after a large earthquake. Households with low income, renters, and those in older buildings are most likely to have low place attachment and experience costly and slow recovery. Whereas existing approaches rely on heuristics, the approach and results in this paper provide quantitative means to assess potential population losses and inform efforts to reduce them. The framework to integrate place attachment into housing recovery simulations is versatile and employs publicly available information making it transferable to other communities.
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