Journal of Korean Society of Forest Science (한국산림과학회지)

Korean Society of Forest Science (한국산림과학회)
권호 표지

Development of Large Fire Judgement Model Using Logistic Regression Equation

로지스틱 회귀식을 이용한 대형산불판정 모형 개발

  • Lee, Byungdoo (Division of Forest Disaster Management Korea, Forest Research Institute) ;
  • Kim, Kyongha (Division of Forest Disaster Management Korea, Forest Research Institute)
  • 이병두 (국립산림과학원 산림방재연구과) ;
  • 김경하 (국립산림과학원 산림방재연구과)
  • Published : 2013.09.30
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Abstract

To mitigate forest fire damage, it is needed to concentrate suppression resources on the fire having a high probability to become large in the initial stage. The objective of this study is to develop the large fire judgement model which can estimate large fire possibility index between the fire size and the related factors such as weather, terrain, and fuel. The results of logistic regression equation indicated that temperature, wind speed, continuous drought days, slope variance, forest area were related to the large fire possibility positively but elevation has negative relationship. This model may help decision-making about size of suppression resources, local residents evacuation and suppression priority.

산불로 인한 피해를 최소화하기 위해서는 대형산불 가능성이 있는 산불에 대해 초기 단계에서부터 진화자원을 집중해야 한다. 따라서 본 연구에서는 산불 발생 초기에 대형화 여부를 판정할 수 있는 모형을 개발하고자 하였다. 이를 위해 132건의 산불에 대해 피해 규모를 현장조사하고, 발화지를 중심으로 100 ha 이내의 기상, 지형, 연료인자를 분석하였다. 그리고 분석 내용을 로지스틱 회귀식을 적용한 결과, 산불은 온도, 풍속, 무강우일수, 경사변이, 산림면적이 높을수록 대형화되었으며, 고도는 낮을수록 그 확률이 높았다. 본 모형을 사용하면 산불 발생 초기에 대형화 여부를 판단할 수 있으므로, 초기 진화자원의 규모와 지역 주민 대피 결정에 근거 자료로 활용될 수 있다.

Keywords

References

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