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This research explores the potential to analyze bank card payments and ATMcash withdrawals in order to map and quantify how people are impacted by andrecover from natural disasters. Our approach defines a disaster-affectedcommunity's economic recovery time as the time needed to return to baselineactivity levels in terms of number of bank card payments and ATM cashwithdrawals. For Hurricane Odile, which hit the state of Baja California Sur(BCS) in Mexico between 15 and 17 September 2014, we measured and mappedcommunities' economic recovery time, which ranged from 2 to 40 days indifferent locations. We found that -- among individuals with a bank account --the lower the income level, the shorter the time needed for economic activityto return to normal levels. Gender differences in recovery times were alsodetected and quantified. In addition, our approach evaluated how communitiesprepared for the disaster by quantifying expenditure growth in food or gasolinebefore the hurricane struck. We believe this approach opens a new frontier inmeasuring the economic impact of disasters with high temporal and spatialresolution, and in understanding how populations bounce back and adapt.

Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data