Affiliations: [a] Beijing Municipal Institute of Labor Protection, Beijing, China | [b] School of Economics, Wuhan University of Technology, Wuhan, Hubei, China | [c] Safety and Emergency Management, Research Center Henan Polytechnic University, Jiaozuo, Henan, China | [d] College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, Henan, China | [e] Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China | [f] University of Chinese Academy of Sciences, Beijing, China
Correspondence:
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Corresponding author: Yingchao Ma, School of Economics, Wuhan University of Technology, Wuhan, Hubei 430000, China. %****␣idt-14-idt190086_temp.tex␣Line␣25␣**** E-mail: myc@hpu.edu.cn.
Abstract: Natural disaster that contributes to the economic crisis all over the world has a crucial role in emergency management. The assessment of regional risk to natural disasters is normally studied as a multi-criteria decision making (MCDM) problem in the literature. However little effort was devoted into the comparison of temporary disaster risk of regions. In this paper, a hybrid approach is proposed integrating MCDM and clustering for evaluating and comparing the regional risk to natural disasters. Our two-stage method is applied to thirty-one Chinese regions over the past two consecutive years. In the first stage MCDM is used to prioritize the regions yearly yielding a set of risk vectors over the given period. In the second stage, K-means clustering is applied to divide the regions into a number of clusters characterized by different risk variation patterns. The derived patterns reveal the variation of regions in perspective of natural disaster risk and therefore offer valuable suggestions for disaster risk reduction.
