A fuzzy social vulnerability evaluation from the perception of disaster bearers against meteorological disasters
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A fuzzy social vulnerability evaluation from the perception of disaster bearers against meteorological disasters Mei Cai1,2 · Guo Wei3 Received: 24 June 2019 / Accepted: 22 May 2020 © Springer Nature B.V. 2020
Abstract Because of climatic hazards and extreme weather events, meteorological disasters attract more and more attention of government, national, and international agencies. Every event tests people’s ability to cope with meteorological disasters and generates the need for disaster risk research and assessments. Social vulnerability is an important measure of disaster risk assessments. Social vulnerability assessment problem can be viewed as a multi-criteria decision-making problem. In order to satisfy the perception of special disaster bearers, we need a local-context approach to construct a social vulnerability evaluation index system. The key to this approach is to identify the evaluation criteria structure by analyzing the complicated information gathering from special disaster bearers. It’s natural to use fuzzy language to express disaster bearers’ preferences in a complicated context. This paper attempts to describe the interrelationship between the evaluation factors with linguistic preferences since linguistic variables can better reflect the vagueness of human being. The fuzzy interpretive structural modeling (FISM) approach has been employed to develop the structural relationship between social vulnerability evaluation factors. In FISM, we apply some computational models of computing with words to quantify the fuzzy interrelationship. Finally, we give an example to show the process of our method. Keywords Social vulnerability · Disaster bearers · Fuzzy interpretive structural modeling (FISM) · Linguistic variables
* Mei Cai [email protected] 1
Key Laboratory of Meteorological Disaster (KLME), Ministry of Education and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC‑FEMD), Nanjing University of Information Science and Technology, Nanjing, China
2
School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
3
Department of Mathematics and Computer Science, University of North Carolina At Pembroke, Pembroke, NC 28372, USA
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Natural Hazards
1 Introduction Extreme weather events often lead to meteorological disasters. Take the disaster of southern China in 2008 as an example. This disaster was caused by low temperature, frost and snow. It blocked several provinces’ highway traffic. The economic loss was serious. A total of 162 people died of this disaster (National Bureau of Statistics, 2009). Meteorological disasters occur globally with increasing frequency. Extreme weather events test the ability of government, national, and international agencies to cope with meteorological disasters and generate the needs of disaster risk research and assessments. In the past decades, many innovative approaches have been applied to disaster risk research and assessmen
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