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태풍 재해에 대한 건물 취약성의 피해손실 데이터 기반 분석

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)
  • 투고 : 2019.09.30
  • 심사 : 2019.11.12
  • 발행 : 2019.12.20

초록

태풍은 전 세계적으로 상당한 재정적 피해를 입힌다. 정부, 지방자치단체, 보험회사는 태풍 위험 평가 모델을 개발하여 자연 재해에 따른 재정 위험을 정량화하고 완화하고자 한다. 이에 태풍 위험 평가 모델의 중요성이 증가하고 있으며, 정교한 평가를 위한 국지적 취약성을 반영하는 것이 중요하다. 자연 재해와 관련된 경제적 손실에 대한 실질적인 기존 연구들이 필수적인 위험 지표를 확인했지만 취약성과 경제적 손실 사이의 상관관계를 다루는 종합적인 연구가 여전히 필요하다. 본 연구의 목적은 태풍 매미로 인한 손실 데이터를 바탕으로 태풍 피해 예측 함수에 대한 평가지표를 개발하기 위함이다. 본 연구에서는 취약성 함수를 만들기 위해 풍속과 해안가로부터의 거리, 그리고 건물가치, 건물 유형, 층수 및 지하층 수의 정보를 사용하였으며 국내 보험사가 제공하는 태풍 매미의 실제 손실 기록을 분석하고 취약성 함수를 개발하여 최대 손실 발생의 예방에 기여하고자 하였다. 본 연구의 결과와 지표는 건물의 실제 재정 손실과 지역 취약성을 반영하는 정부 기관 및 보험 회사의 취약성 함수 개발을 위한 실질적인 지침으로 활용될 수 있다.

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.

키워드

참고문헌

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