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Development of Fire Weather Index Model in Inaccessible Areas using MOD14 Fire Product and 5km-resolution Meteorological Data

MODIS Fire Spot 정보와 5km 기상 재분석 자료를 활용한 접근불능지역의 산불기상위험지수 산출 모형 개발

  • WON, Myoung-Soo (Division of Forest Ecology and Climate Change, National Institute of Forest Science) ;
  • JANG, Keun-Chang (Division of Forest Ecology and Climate Change, National Institute of Forest Science) ;
  • YOON, Suk-Hee (Division of Forest Ecology and Climate Change, National Institute of Forest Science)
  • 원명수 (국립산립과학원 기후변화생태연구과) ;
  • 장근창 (국립산립과학원 기후변화생태연구과) ;
  • 윤석희 (국립산립과학원 기후변화생태연구과)
  • Received : 2018.08.23
  • Accepted : 2018.09.30
  • Published : 2018.09.30

Abstract

This study has developed a forest fire occurrence probability model for inaccessible areas such as North Korea and Demilitarized Zone and we have developed a real-time forest fire danger rating system that can be used in fire-related works. There are limitations on the research that it is impossible to conduct site investigation for data acquisition and verification for forest fire weather index model and system development. To solve this problem, we estimated the fire spots in the areas where access is impossible by using MODIS satellite data with scientific basis. Using the past meteorological reanalysis data(5㎞ resolution) produced by the Korea Meteorological Administration(KMA) on the extracted fires, the meteorological characteristics of the fires were extracted and made database. The meteorological factors extracted from the forest fire ignition points in the inaccessible areas are statistically correlated with the forest fire occurrence and the weather factors and the logistic regression model that can estimate the forest fires occurrence(fires 1 and non-fores 0). And used to calculate the forest fire weather index(FWI). The results of the statistical analysis show that the logistic models(p<0.01) strongly depends on maximum temperature, minimum relative humidity, effective humidity and average wind speed. The logistic regression model constructed in this study showed a relatively high accuracy of 66%. These findings may be beneficial to the policy makers in Republic of Korea(ROK) and Democratic People's Republic of Korea(DPRK) for the prevention of forest fires.

본 연구는 북한 및 비무장지대 등 접근불능지역에 대한 기상에 의한 산불발생예측 알고리즘을 개발하고, 실제 현장과 현업에서 활용할 수 있는 실시간 산불위험예보 체계를 개발하는데 있다. 산불기상위험지수 산출 모형 개발을 위해 자료의 취득과 검증을 위한 현장조사가 불가능하다는 연구적 한계가 존재하므로, 이를 해결하기 위해 MODIS 위성자료를 활용하여 접근이 불가능한 지역의 산불발화지점(fire spot)을 과학적 근거를 가지고 추정하였다. 추출된 산불발화지점을 대상으로 기상청에서 생산된 과거 기상 재분석자료(5㎞ 해상도)를 활용하여 산불발화지점에 대한 기상특성을 추출하여 데이터베이스화 하였다. 접근불능지역의 산불발화지점에서 추출된 기상요소들은 산불발생과 기상요인들과의 통계적 상관성과 산불발생 유무(산불발생 1, 산불 미발생 0)를 추정할 수 있는 로지스틱 회귀모형을 활용하여 실시간 기상변화에 의한 산불기상위험지수(Fire Weather Index, FWI)를 개발하였다. FWI 모형의 예측정확도는 66.6%로 나타나 모형의 적합도는 비교적 높은 것으로 나타났다. 이 연구결과는 남 북한의 산불 방지를 위한 정책 입안자들의 의사결정에 유용하게 활용될 것으로 기대한다.

Keywords

References

  1. An, S.H., M.S. Won, D.H. Kim, Y.H. Kang, M.B. Lee and S.Y. Lee. 2005. Classification of forest fire risk and hazard regions in Uiseong-gun. Journal of the Korean Association of Geograhpic Information Studies 8(2):117-124.
  2. Cunningham, A.A. and D.L. Martell. 1972. A stochastic model for the occurrence of man-caused forest fires. Canadian Journal of Forest Research 3:282-287.
  3. Choi, G., J. Kim and M.S. Won. 2006. Spatial Patterns and Temporal Variability of the Haines Index related to the Wildland Fire Growth Potential over the Korean Peninsula. Journal of the Korean Geographical Society 41(2):168-187.
  4. Davis, K.P. and A.A. Brown. 1959. Fire in the Forests. In: Forest Fire Control and Use Second Edition. McGraw-Hill. pp.3 -259.
  5. Giglio L., J. Descloitres, C.O. Justice and Y.J. Kaufman. 2003. An enhanced contextual fire detection algorithm for MODIS. Romote Sensing of Environment 87:273-282. https://doi.org/10.1016/S0034-4257(03)00184-6
  6. Hong, S.K. 1987. Meteorology and fire. Kyohak Research Press. pp.67-71.
  7. Lee, S.Y., S.Y. Han, M.S. Won, S.H. An and M.B. Lee. 2004. Developing of forest fire occurrence probability model by using the meteorological characteristics in Korea. Korean Journal of Agricultureal and Forest Meteorology 6(4):242-249.
  8. Lee, S.Y., M.S. Won and S.Y. Han. 2005. Developing of forest fire occurrence danger index using fuel and topographical characteristics on the condition of ignition point in Korea. Korean Institute of Fire Science & Engineering 19(4):75-79.
  9. Lee, S.J., M.S. Won, K.C. Jang, B.D. Lee, S.W. Byun, K.J. Kim and Y.W. Lee. 2016. Construction of GIS Database for wildfire in the Korean Peninsula using MODIS data. Journal of the Korean Cartographic Association 16(3):129-137.
  10. National Institute of Forest & Science, Korea Forest Service. Korean Forest Fire Danger Rating System. www.forestfire.nifos.go.kr.
  11. Kang, S.C., M.S. Won and S.H. Yoon. 2016. Large fire forecasting depending on the changing wind speed and effective humidity in korean red pine forests through a case study. Journal of the Korean Association of Geograhpic Information Studies 19(4):146-156. https://doi.org/10.11108/kagis.2016.19.4.146
  12. Korea Centre for Atmospheric Environment Research. 2012. Study on detection of forest fires and air-pollution using satellites p.125.
  13. Korea Forest Research Institute. 2008. Degraded forest survey of North Korea with SPOT imagery. p7.
  14. Korea Forest Service. 2015. Statistical Yearbook of Forestry. 44.
  15. Korea Meteorological Administration. 2015. Abnormal Climate Report 2014 p.169.
  16. Sung, M.K., G.H. Lim, E.H. Choi, Y.Y. Lee, M.S. Won and K.S. Koo. 2010. Climate change over Korea and its relation to the forest fire occurrence. Atmosphere 20(1):27-35.
  17. Won, M.S., K.S. Koo and M.B. Lee. 2006. An analysis of forest occurrence hazards by changing temperature and humidity of ten-day intervals for 30 years in spring. Korean Journal of Agricultural and Forest Meteorology 8(4):250-259.
  18. Won, M.S., S.Y. Lee, M.B. Lee and S. Ohga. 2010a. Development and application of a forest fire danger rating system in South Korea. Journal of the Faculty of Agriculture Kyushu University 55(2):221-229.
  19. Won, M.S., M. Danesh, K.S. Koo, M.B. Lee and M.Y. Shin. 2010b. Meteorological determinants of forest fire occurrence in the fall, South Korea. Journal of Korean Forest Society 99(2):163-171.
  20. Won, M.S., S.H. Yoon, K.S. Koo and K.H. Kim. 2011. Spatio-temporal analysis of forest fire occurrences during the dry season between 1990s and 2000s in South Korea. Journal of the Korean Association of Geograhpic Information Studies 14(3):150-162.
  21. Won, M.S., M.B. Lee, W.K. Lee and S.H. Yoon. 2012. Prediction of forest fire danger rating over the Korean Peninsula with the digital forecast data and daily weather index(DWI) model. Korean Journal of Agricultural and Forest Meteorology 14(1):1-10. https://doi.org/10.5532/KJAFM.2012.14.1.001
  22. Won, M.S., S.H. Yoon and K.C. Jang. 2016. Developing Korean forest fire occurrence probability model reflecting climate change in the spring of 2000s. Korean Journal of Agricultureal and Forest Meteorology 18(4):199-207. https://doi.org/10.5532/KJAFM.2016.18.4.199
  23. Yoon, S.H. and M.S. Won. 2016. Correlation analysis of forest fire occurrences by change of standardized precipitation index. Journal of the Korean Association of Geograhpic Information Studies 19(2): 14-26. https://doi.org/10.11108/kagis.2016.19.2.014