Quantification of Urban and Community Resilience to Natural Hazards from Cell-Phone GPS Location and Traffic-Flow Data

Quantification of Urban and Community Resilience to Natural Hazards from Cell-Phone GPS Location and Traffic-Flow Data

In view that cities will continue to house the majority of the world’s population at an increasing rate in association with the face of climate change, in this lecture we quantify urban and community resilience by processing human mobility data in large American cities prior and upon historic natural hazards strike.

During the talk we first uncover that the time-histories of traffic-flow data (number of vehicles per time) recorded at various locations of major traffic city arteries exhibit striking similarities with the time-histories of the mean square displacement of citizens computed by tracking GPS locations from individual cell-phone users.

The recorded mean-square displacements of large numbers of cell-phone users from the cities of Houston, Miami and Jacksonville when struck by hurricanes Harvey 2017, Irma 2017 and Dorian 2019 together with the recorded human mobility data from the citizens of Dallas, and Houston when experienced the 2021 North American winter storm, revert immediately to their pre-event steady-state response, suggesting that large cities when struck by natural hazards manifest an inherent and invariable high level of  resilience.

The significant number of human mobility records presented in this study also validate a mechanical model for cities, recently developed by the speaker, which is rooted in Langevin dynamics and predicts, that following a natural hazard, large cities revert immediately to their initial steady-state regime and resume their normal, pre-event activities. This is possible by recognizing that the mean-square displacement from a random (stochastic) process is intimately related to deterministic, emergent time-response functions.