Unveiling Spatial Patterns of Disaster Impacts and Recovery Using Credit Card Transaction Variances

The objective of this study is to examine spatial patterns of impacts and\nrecovery of communities based on variances in credit card transactions. Such\nvariances could capture the collective effects of household impacts, disrupted\naccesses, and business closures, and thus provide an integrative measure for\nexamining disaster impacts and community recovery in disasters. Existing\nstudies depend mainly on survey and sociodemographic data for disaster impacts\nand recovery effort evaluations, although such data has limitations, including\nlarge data collection efforts and delayed timeliness results. In addition,\nthere are very few studies have concentrated on spatial patterns and\ndisparities of disaster impacts and short-term recovery of communities,\nalthough such investigation can enhance situational awareness during disasters\nand support the identification of disparate spatial patterns of disaster\nimpacts and recovery in the impacted regions. This study examines credit card\ntransaction data Harris County (Texas, USA) during Hurricane Harvey in 2017 to\nexplore spatial patterns of disaster impacts and recovery during from the\nperspective of community residents and businesses at ZIP code and county\nscales, respectively, and to further investigate their spatial disparities\nacross ZIP codes. The results indicate that individuals in ZIP codes with\npopulations of higher income experienced more severe disaster impact and\nrecovered more quickly than those located in lower-income ZIP codes for most\nbusiness sectors. Our findings not only enhance the understanding of spatial\npatterns and disparities in disaster impacts and recovery for better community\nresilience assessment, but also could benefit emergency managers, city\nplanners, and public officials in harnessing population activity data, using\ncredit card transactions as a proxy for activity, to improve situational\nawareness and resource allocation.\n