Journal
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
Volume 34, Issue 12, Pages 2434-2450Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/13658816.2019.1694681
Keywords
Resilience; accessibility; crowdsourced data; empirical study; natural hazards; time-geography
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Funding
- U.S. National Science Foundation under the Coastlines and People (CoPe) Program [1940091]
- U.S. National Science Foundation under the Methodology, Measurement & Statistics (MMS) Program [1853866]
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Climate change and natural hazards pose great threats to road transport systems which are 'lifelines' of human society. However, there is generally a lack of empirical data and approaches for assessing resilience of road networks in real hazard events. This study introduces an empirical approach to evaluate road network resilience using crowdsourced traffic data in Google Maps. Based on the conceptualization of resilience and the Hansen accessibility index, resilience of road network is measured from accumulated accessibility reduction over time during a hazard. The utility of this approach is demonstrated in a case study of the Cleveland metropolitan area (Ohio) in Winter Storm Harper. The results reveal strong spatial variations of the disturbance and recovery rate of road network performance during the hazard. The major findings of the case study are: (1) longer distance travels have higher increasing ratios of travel time during the hazard; (2) communities with low accessibility at the normal condition have lower road network resilience; (3) spatial clusters of low resilience are identified, including communities with low socio-economic capacities. The introduced approach provides ground-truth validation for existing quantitative models and supports disaster management and transportation planning to reduce hazard impacts on road network.
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