Abstract
In urban areas, the occurrence of disasters can cause extensive damage to human society. For this reason, evacuation, regarded as a critical course of action to relocate people and property, helps to alleviate loss of life and property to a great extent. Risk associated with evacuation is an abstract concept that cannot be easily conceptualized. This paper develops a model for assessing and visualizing the risks associated with the evacuation process in response to potential catastrophes. Understanding of evacuation risk, the potential for losing transport connections and the difficulty of transferring rescue resources, was previously limited by considering pre-disaster factors only. This study mitigates such limitation by extending previous research to include the contingent post-disaster factors that have received scant attention to date. Two contingent post-disaster factors: the spatial impact of the disaster and the potential for traffic congestion caused by the evacuee routing behaviors, are discussed in detail and integrated into the model along with other pre-disaster factors. A case study on the transportation network of Beijing, China is used to demonstrate the value of the model. This paper asserts that the notion of evacuation risk is not a static evaluation of such factors as road vulnerability; rather it involves a dynamic process where contingent factors associated with disastrous events play a role. This model can help city emergency planners to identify urban infrastructures that may hinder an efficient evacuation process because of their deficient configuration.
Original language | English (US) |
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Pages (from-to) | 207-217 |
Number of pages | 11 |
Journal | Computers, Environment and Urban Systems |
Volume | 36 |
Issue number | 3 |
DOIs | |
State | Published - May 2012 |
Externally published | Yes |
Keywords
- Critical Cluster Model (CCM)
- Evacuation risk
- Post-disaster factors
- Pre-disaster factors
- Routing
- Spatial impact
ASJC Scopus subject areas
- Geography, Planning and Development
- Ecological Modeling
- General Environmental Science
- Urban Studies