Quantifying human mobility resilience to extreme events using geo-located social media data

EPJ Data Science

Kamol Chandra Roy¹  Samiul Hasan¹  Manuel Cebrian² 

[1] 0000 0001 2159 2859, grid.170430.1, Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, USA;0000 0001 2341 2786, grid.116068.8, Media Laboratory, Massachusetts Institute of Technology, Cambridge, USA;

关键词: Human mobility;    Resilience;    Geo-location data;    Social media;   

DOI  :  10.1140/epjds/s13688-019-0196-6

来源: publisher

【 摘 要 】

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.

【 授权许可】

CC BY