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http://dx.doi.org/10.5345/JKIBC.2019.19.6.529

Analysis of Building Vulnerabilities to Typhoon Disaster Based on Damage Loss Data  

Ahn, Sung-Jin (Department of Architectural Engineering, Mokpo University)
Kim, Tae-Hui (Department of Architectural Engineering, Mokpo University)
Son, Ki-Young (School of Architectural Engineering, University of Ulsan)
Kim, Ji-Myong (Department of Architectural Engineering, Mokpo University)
Publication Information
Journal of the Korea Institute of Building Construction / v.19, no.6, 2019 , pp. 529-538 More about this Journal
Abstract
Typhoons can cause significant financial damage worldwide. For this reason, states, local governments and insurance companies attempt to quantify and mitigate the financial risks related to these natural disasters by developing a typhoon risk assessment model. As such, the importance of typhoon risk assessment models is increasing, and it is also important to reflect local vulnerabilities to enable sophisticated assessments. Although a practical study of economic losses associated with natural disasters has identified essential risk indicators, comprehensive studies covering the correlation between vulnerability and economic loss are still needed. The purpose of this study is to identify typhoon damage indicators and to develop evaluation indicators for typhoon damage prediction functions, utilizing the loses from Typhoon Maemi as data. This study analyzes actual loss records of Typhoon Maemi provided by local insurance companies to prepare for a scenario of maximum losses. To create a vulnerability function, the authors used the wind speed and distance from the coast and the total value of property, construction type, floors, and underground floor indicators. The results and metrics of this study provide practical guidelines for government agencies and insurance companies in developing vulnerability functions that reflect the actual financial losses and regional vulnerabilities of buildings.
Keywords
damage record; building vulnerability; vulnerability function; natural catastrophe model;
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