Lifestyle pattern analysis unveils recovery trajectories of communities impacted by disasters
Lifestyle pattern analysis unveils recovery trajectories of communities impacted by disasters
复制标题
生活方式模式分析揭示了受灾害影响的社区的恢复轨迹
DOI：
10.1057/s41599-023-02312-7
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发表时间：
2023
影响因子：
--
通讯作者：
Mostafavi, Ali
中科院分区：
文献类型：
--
作者：
Coleman, Natalie;Liu, Chenyue;Zhao, Yiqing;Mostafavi, Ali
生活方式的恢复反映了人口活动以及基础设施和商业服务的恢复所产生的集体影响。这项研究使用了一种新的方法来利用隐私增强的位置智能数据，这些数据是匿名和聚合的，以描述独特的生活方式模式，并揭示2017年德克萨斯州哈里斯县飓风哈维之后的恢复轨迹。该分析整合了多个数据源，以记录基线和灾害期间从家庭人口普查区块组（CBG）到该县不同兴趣点（POI）的访问次数。在方法上，该研究利用无监督机器学习和ANOVA统计测试来描述使用隐私增强的位置智能数据恢复生活方式的特征。首先，使用k-均值的主要聚类表征了四种不同的基本和非基本生活方式模式。对于每个主要的生活方式集群，第二集群根据最大破坏的严重程度和恢复的持续时间将飓风的影响分为四种可能的恢复轨迹。研究结果进一步揭示了每个生活方式集群中的多个恢复轨迹和持续时间，这意味着相似生活方式和不同人口群体之间的恢复率不同。洪水对生活方式恢复的影响超出了洪水泛滥的地区，因为59%的CBG具有极端的恢复时间，但没有至少1%的直接洪水影响。研究结果提供了双重理论意义：（1）生活方式的恢复是一个重要的里程碑，需要在灾后进行检查，量化和监测;（2）由人类流动和设施分布形成的城市空间结构扩展了洪水对人口生活方式影响的空间范围。这些为公共官员和应急管理人员提供了新的数据驱动的见解，以检查，测量和监测基于生活方式恢复正常的社区恢复轨迹的关键里程碑。
Lifestyle recovery captures the collective effects of population activities as well as the restoration of infrastructure and business services. This study uses a novel approach to leverage privacy-enhanced location intelligence data, which is anonymized and aggregated, to characterize distinctive lifestyle patterns and to unveil recovery trajectories after 2017 Hurricane Harvey in Harris County, Texas (USA). The analysis integrates multiple data sources to record the number of visits from home census block groups (CBGs) to different points of interest (POIs) in the county during the baseline and disaster periods. For the methodology, the research utilizes unsupervised machine learning and ANOVA statistical testing to characterize the recovery of lifestyles using privacy-enhanced location intelligence data. First, primary clustering using k-means characterized four distinct essential and non-essential lifestyle patterns. For each primary lifestyle cluster, the secondary clustering characterized the impact of the hurricane into four possible recovery trajectories based on the severity of maximum disruption and duration of recovery. The findings further reveal multiple recovery trajectories and durations within each lifestyle cluster, which imply differential recovery rates among similar lifestyles and different demographic groups. The impact of flooding on lifestyle recovery extends beyond the flooded regions, as 59% of CBGs with extreme recovery durations did not have at least 1% of direct flooding impacts. The findings offer a twofold theoretical significance:(1) lifestyle recovery is a critical milestone that needs to be examined, quantified, and monitored in the aftermath of disasters;(2) spatial structures of cities formed by human mobility and distribution of facilities extend the spatial reach of flood impacts on population lifestyles. These provide novel data-driven insights for public officials and emergency managers to examine, measure, and monitor a critical milestone in community recovery trajectory based on the return of lifestyles to normalcy.
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影响因子：
4.6
作者：
Farahmand, Hamed;Xu, Yuanchang;Mostafavi, Ali
通讯作者：
Mostafavi, Ali
影响因子：
3.9
作者：
Mitsova, Diana;Escaleras, Monica;Lamadrid, Alberto J.
通讯作者：
Lamadrid, Alberto J.
影响因子：
2.2
作者：
Lee, Dalbyul
通讯作者：
Lee, Dalbyul
影响因子：
4.6
作者：
Lee, Cheng-Chun;Chou, Charles;Mostafavi, Ali
通讯作者：
Mostafavi, Ali
影响因子：
3.9
作者：
T. Yabe;K. Tsubouchi;N. Fujiwara;Y. Sekimoto;S. Ukkusuri
通讯作者：
T. Yabe;K. Tsubouchi;N. Fujiwara;Y. Sekimoto;S. Ukkusuri