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The objective of this study is to examine spatial patterns of impacts andrecovery of communities based on variances in credit card transactions. Suchvariances could capture the collective effects of household impacts, disruptedaccesses, and business closures, and thus provide an integrative measure forexamining disaster impacts and community recovery in disasters. Existingstudies depend mainly on survey and sociodemographic data for disaster impactsand recovery effort evaluations, although such data has limitations, includinglarge data collection efforts and delayed timeliness results. In addition,there are very few studies have concentrated on spatial patterns anddisparities of disaster impacts and short-term recovery of communities,although such investigation can enhance situational awareness during disastersand support the identification of disparate spatial patterns of disasterimpacts and recovery in the impacted regions. This study examines credit cardtransaction data Harris County (Texas, USA) during Hurricane Harvey in 2017 toexplore spatial patterns of disaster impacts and recovery during from theperspective of community residents and businesses at ZIP code and countyscales, respectively, and to further investigate their spatial disparitiesacross ZIP codes. The results indicate that individuals in ZIP codes withpopulations of higher income experienced more severe disaster impact andrecovered more quickly than those located in lower-income ZIP codes for mostbusiness sectors. Our findings not only enhance the understanding of spatialpatterns and disparities in disaster impacts and recovery for better communityresilience assessment, but also could benefit emergency managers, cityplanners, and public officials in harnessing population activity data, usingcredit card transactions as a proxy for activity, to improve situationalawareness and resource allocation.

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