한국산림과학회지 (Journal of Korean Society of Forest Science)

  • 제102권3호
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  • Pages.415-419
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  • 2013
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  • 2586-6613(pISSN)
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  • 2586-6621(eISSN)
한국산림과학회 (Korean Society of Forest Science)
권호 표지

로지스틱 회귀식을 이용한 대형산불판정 모형 개발

Development of Large Fire Judgement Model Using Logistic Regression Equation

  • 이병두 (국립산림과학원 산림방재연구과) ;
  • 김경하 (국립산림과학원 산림방재연구과)
  • Lee, Byungdoo (Division of Forest Disaster Management Korea, Forest Research Institute) ;
  • Kim, Kyongha (Division of Forest Disaster Management Korea, Forest Research Institute)
  • 발행 : 2013.09.30
⟨ 이전 논문 다음 논문 ⟩

초록

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.

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.

키워드

참고문헌

  1. 산림청. 2012. 산림보호법 시행령(대통령령 제23713호). 2012. 4. 10. 개정.
  2. 산림청. 2013. 2012년 산불통계연보. pp. 213.
  3. 이병두. 2005. GIS와 RS를 이용한 2000년 삼척산불 행동 특성 분석 및 산불확산예측프로그램 개발. 서울대학교 박사학위논문. pp. 117.
  4. 이병두, 송정은, 이명보, 정주상. 2007. 한국의 생태지역별 산불특성과 임상분포패턴과의 관계. 한국임학회지 97(1): 1-9.
  5. 이시영. 1990. 환경인자가 산불의 온도 및 진행속도에 미치는 영향. 동국대학교 석사학위논문. pp. 104.
  6. 정태현, 이우철. 1965. 한국삼림식물대 및 적지적소론. 성균관대학교 논문집 10: 329-435.
  7. Bradstock, R.A., Cohn, J.S., Gill, A.M., Bedward, M. and Lucas, C. 2009. Prediction of the probability of large fires in the Sydney region of south-eastern Australia using components of fire weather. International Journal of Wildland Fire 2009: 932-943.
  8. Davis, F.W. and Michaelsen, J. 1995. Sensitivity of fire regime in chaparral ecosystems to global climate change. Ecological Studies 117: 435-456. https://doi.org/10.1007/978-1-4612-4186-7_21
  9. Flannigan, M.D., Amiro, B.D., Logan, K.A., Stocks, B.J. and Wotton, B.M. 2005. Forest fires and climate change in the 21st Century. Mitigation and Adaptation Strategies for Global Change 11: 847-859.
  10. Flannigan, M.D. and Harrington, J.B. 1988. A study of the relation of meteorological variables to monthly provincial area burned by wildfire in Canada (1953-80). Journal of Applied Meteorology 27: 441-452. https://doi.org/10.1175/1520-0450(1988)027<0441:ASOTRO>2.0.CO;2
  11. Gill, A.M. 2005. Landscape fires as social disasters: an overview of the bushfire problem. Global Environmental Change Part B: Environmental Hazards 6: 65-80.
  12. Keeley, J.E. 2004. Impact of Antecedent Climate on Fire Regimes in Coastal California. International Journal of Wildland Fire 13: 1-11. https://doi.org/10.1071/WF03001
  13. Keeley J.E. and Fotheringham, C.J. 2001. Historic fire regime in southern California shrublands. Conservation Biology 15: 1536-1548. https://doi.org/10.1046/j.1523-1739.2001.00097.x
  14. Lee, B., Kim, S.Y., Chung, J. and Park, P.S. 2008. Estimation of fire severity by use of Landsat Tm images and its relevance to vegetation and topography in the 2000 Samcheok forest fire. Journal of Forest Research 13: 197-204. https://doi.org/10.1007/s10310-008-0072-x
  15. Lee, B., Won, M.S., Lee Y., and Lee, M.B. 2012. Crown Fuel Characteristics and Carbon Emission from Japanese Red Pine Stands Burned by Crown Fire in Mt.Palgong, South Korea. Journal of Mountain Science 9: 656-664. https://doi.org/10.1007/s11629-012-2397-3
  16. Moreno J.M. 1998. Large Forest Fires. Backhuys Publishers. Leiden, the Netherlands. pp. 254.
  17. National Wildfire Coordinating Group. 2001. Wildland Fire Investigator Certification Standards. pp. 150.
  18. Peters, D.P.C., Pielke, R.A., Bestelmeyer, B.T., Allen, C.D., Munson-McGee, S. and Havstad, K.M. 2004. Cross-scale interactions, nonlinearities, and forecasting catastrophic events. Proc Natural Academy Science U.S.A. 42: 15130-15135.
  19. Preisler, H.K. and Westerling, A.L. 2006. Statistical model for forecasting monthly large wildfire events in western United States. Journal of Applied Meteorology and Climatology 46(7): 1020-1030.
  20. Pyne, S.J., Patricia, L.A. and Richard D.L. 1996. Introduction to Wildland Fire, second edition, John Wiley & Sons, Inc. New York, U.S.A. pp. 769.
  21. Rothermel, R.C. 1972. A mathematical model for predicting fire spread in wildland fuels. Research Paper INT-115. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. pp. 40.
  22. Scott, J.H. and Reinhardt, E.D. 2001. Assessing crown fire potential by linking models of surface and crown fire behavior. Res. Pap. RMRS-RP-29. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. pp. 59.
  23. Viegas, D.X. 1994. Some thoughts on the wind and slope effects on fire propagation. International Journal of Wildland Fire 4(2): 63-64. https://doi.org/10.1071/WF9940063