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

TL;DR

This study uses credit card transaction variances to analyze spatial patterns of disaster impacts and recovery, revealing disparities across income levels and providing insights for improving community resilience and emergency response strategies.

Contribution

It introduces a novel approach of using credit card transaction data to assess spatial disparities in disaster impacts and recovery, offering a timely alternative to traditional survey methods.

Findings

Higher-income ZIP codes experienced more severe impacts and faster recovery.

Credit card transaction variances effectively captured community impacts and recovery patterns.

Spatial disparities in disaster impacts highlight the need for targeted emergency responses.

Abstract

The objective of this study is to examine spatial patterns of impacts and recovery of communities based on variances in credit card transactions. Such variances could capture the collective effects of household impacts, disrupted accesses, and business closures, and thus provide an integrative measure for examining disaster impacts and community recovery in disasters. Existing studies depend mainly on survey and sociodemographic data for disaster impacts and recovery effort evaluations, although such data has limitations, including large data collection efforts and delayed timeliness results. In addition, there are very few studies have concentrated on spatial patterns and disparities of disaster impacts and short-term recovery of communities, although such investigation can enhance situational awareness during disasters and support the identification of disparate spatial patterns of disaster impacts and recovery in the impacted regions. This study examines credit card transaction data Harris County (Texas, USA) during Hurricane Harvey in 2017 to explore spatial patterns of disaster impacts and recovery during from the perspective of community residents and businesses at ZIP code and county scales, respectively, and to further investigate their spatial disparities across ZIP codes. The results indicate that individuals in ZIP codes with populations of higher income experienced more severe disaster impact and recovered more quickly than those located in lower-income ZIP codes for most business sectors. Our findings not only enhance the understanding of spatial patterns and disparities in disaster impacts and recovery for better community resilience assessment, but also could benefit emergency managers, city planners, and public officials in harnessing population activity data, using credit card transactions as a proxy for activity, to improve situational awareness and resource allocation.