Quantifying human mobility resilience to extreme events using geo-located social media data
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13688_2019_Article_196.pdf
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1.62 MB
Format
Adobe PDF
Checksum (MD5)
4d9ba3aca89e82b0efafa287b8a7483a
Author(s)
Roy, Kamol Chandra
Cebrian, Manuel
Hasan, Samiul
Date Issued
May 2019
Journal
EPJ Data Science
Publisher
Springer Science and Business Media LLC
Citation
Roy, Kamol Chandra et al. "Quantifying human mobility resilience to extreme events using geo-located social media data." EPJ Data Science 8, 1 (May 2019): 18 © 2019 Springer Nature
Version
Final published version
Abstract
Mobility is one of the fundamental requirements of human life with significant societal impacts including productivity, economy, social wellbeing, adaptation to a changing climate, and so on. Although human movements follow specific patterns during normal periods, there are limited studies on how such patterns change due to extreme events. To quantify the impacts of an extreme event to human movements, we introduce the concept of mobility resilience which is defined as the ability of a mobility system to manage shocks and return to a steady state in response to an extreme event. We present a method to detect extreme events from geo-located movement data and to measure mobility resilience and transient loss of resilience due to those events. Applying this method, we measure resilience metrics from geo-located social media data for multiple types of disasters occurred all over the world. Quantifying mobility resilience may help us to assess the higher-order socio-economic impacts of extreme events and guide policies towards developing resilient infrastructures as well as a nation’s overall disaster resilience strategies.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1140/epjds/s13688-019-0196-6
