USING LONGITUDINAL STATION-LEVEL SUBWAY RIDERSHIP DATA TO QUANTIFY DISASTER IMPACTS AND RECOVERY PATTERNS POST-SANDY

That social disruptions underlie all disasters is well recognized by disaster researchers. Yet, the empirical literature on disaster impacts and recovery typically does not account for the social disruptions brought by disasters. In this study, we use longitudinal station-level subway ridership data for New York City to quantify disaster impacts and examine recovery patterns at the census tract level from before to after Hurricane Sandy in 2012. Our results are validated with the flood depth data. With the use of this data source, we demonstrate the feasibility of constructing a temporal trajectory from pre- to post-disaster at a fine spatial scale. Our study highlights three findings: first, the immediate recovery process after the disaster displays a non-linear pattern, without returning to the pre-disaster state at the end of November 2012; second, recovery patterns vary significantly across neighborhoods; and third, in our cross-scale comparisons, neighborhood- and system-level recovery patterns do not agree with each other: the recovery trajectories of neighborhoods show more fluctuations than that of the whole study area.