Assessing the Impact of Hurricane Sandy on Mobility Patterns in New York City across Scales

Abstract:

Transportation network is a critical infrastructure and a community lifeline in the U.S. that is essential for keeping cities operational at all times. However, disruptions caused by extreme events such as hurricanes or floods to these networks can impact economic activities and social well-being of any location. The resilience of a transportation network depends on its ability to recover from a disruption to an operational level similar to pre-disruption level in a timely manner. The increase in the availability of GPS-based mobility data has enabled exploration of mobility patterns in urban transportation networks. Assessing vulnerability and resilience of these infrastructure networks across multiple scales using such big datasets during natural disasters is crucial for utilities and policymakers for decision-making purposes, such as evacuation and energy restoration planning. Using trajectory data and socio-economic condition of population in traffic zones within New York City, we examined the change in mobility pattern (trip time) within traffic zones before and after hurricane Sandy (2012) based on underlying social vulnerability. Specifically, we implemented a Multiscale Geographically Weighted Regression technique to explore the extent to which spatial scale (i.e., census tract vs county) of analysis impacts relationship between mobility behavior and social vulnerability. Understanding the role of scale in vulnerability assessment and mobility behavior exploration before, during and after a hazard will help (i) decision-makers identify confidence in results so that (ii) appropriate risk communication strategies incorporating uncertainties could be deployed.