Prediction of highway blockage caused by earthquake-induced landslides for improving earthquake emergency response

Jiwen An (), Xianfu Bai, Jinghai Xu, Gaozhong Nie and Xiuying Wang

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2015, vol. 79, issue 1, 536 pages

Abstract: Earthquake emergency response (EER) supported by the prompt assessment of seismic impact is an effective way to reduce seismic casualties and losses after an earthquake. However, in mountainous areas, highway blockages due to earthquake-induced landslides can delay EER, which, to date, EER planning has not included in assessments to identify. This paper proposes a set of rules to predict the location of highway blockages caused by these landslides. Such predictions would promote rapid implementation of traffic control plans and the prompt clearing of the blocked highways to help keep emergency efforts efficient. We propose a procedure based on the decision tree method to correlate the potential highway blockages with the earthquake-induced landslide susceptibility (ELS), which integrates the classification and quantification aspects of the ELS. Using correlation analysis, a set of rules that judge whether a highway section is likely to be blocked is proposed. These rules are based on the preexisting ELS database for China. This set of rules has been applied in a case study of the 2014 Ludian earthquake to predict the highway blockages caused by the earthquake-induced landslides. The results from this case study showed good agreement with the actual highway blockages as determined by the interpretation of unmanned aerial vehicle images. The predicted results were used to make suggestions about traffic control and blocked highway clearing for EER. The proposed set of rules appears to be effective. Copyright Springer Science+Business Media Dordrecht 2015

Keywords: Prediction; Highway blockage; Earthquake-induced landslide susceptibility; Earthquake emergency response; Correlation analysis; Decision tree (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11069-015-1859-7

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