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Vegetation Fire Behavior Prediction in Russia

  • Aleksandra V. VolokitinaEmail author
  • Tatiana M. Sofronova
  • Mikhail A. Korets
Conference paper
  • 28 Downloads

Abstract

The systems for vegetation (including forest) fire behavior prediction in the USA and Canada are analyzed. The conclusion is drawn about the complexity of their use in other countries due to natural differences and historically established different approaches to the classification of vegetation. Russia has all the prerequisites to develop a system for fire behavior prediction. Developed are guidelines for improving forest fire danger rating and fire hazard assessment; classification of vegetation fuels and methods of their mapping; a registered software for automatized vegetation fuel mapping; an example of a map for the nature reserve Stolby. A fire spread model is selected based on the availability of the input data. A fire behavior prediction software program is developed to predict spread of tactical fire parts over the area, fire intensity, development of the fire (from the surface fire to the crown or ground one) and immediate fire effects. In addition, the program allows you to calculate the manpower and means for fire suppression. The results of a retrospective software performance test are given on the example of the nature reserve Stolby. The software performance test is planned to be carried out on active fires with the participation of forest fire protection experts.

Keywords

Vegetation fires Vegetation fuel maps Fire behavior prediction Fire effects 

References

  1. 1.
    Burgan RE, Rothermel RG (1984) BEHAVE: fire behavior prediction and fuel modeling system – FUEL subsystem. Gen Tech rep INT-167. US Department of Agriculture, Forest Service. Intermountain Forest and Range Experiment Station, Ogden, UT, 126 pGoogle Scholar
  2. 2.
    Forestry Canada, Fire Danger Group (1992) Development and structure of the Canadian forest fire behavior prediction system. Science and sustainable development directorate. Inf rep ST-X-3, Ottawa, 63 pGoogle Scholar
  3. 3.
    Mavsar R, Cabán AG, Varela E (2013) The state of development of fire management decision support systems in America and Europe. For Policy Econ 29:45–55CrossRefGoogle Scholar
  4. 4.
    Rothermel RC (1991) Predicting behaviour and size of crown fires in the Northern Rocky Mountains. USDA forest service, Research paper INT-438, Ogden, UT, USA, 40 pGoogle Scholar
  5. 5.
    Silva F, Martínez J, Machuca M, Leal JR (2013) VISUAL-SEVEIF, a tool for integrating the behavior simulation and economic evaluation of the impacts of wildfires. In: Proceedings of the fourth international symposium on fire economics, planning and policy: climate change and wildfires. General Technical report, vol 245, pp 163–178Google Scholar
  6. 6.
    Bartalyov SA, Stytsenko FV, Khvostikov SA, Lupyan EA (2017) Methodology of monitoring and prediction of fire-caused stand mortality using satellite observations data. Sovr Probl DZZ Kosm 14(6):176–193 [Current problems in remote sensing of the Earth from space]CrossRefGoogle Scholar
  7. 7.
    Guidelines for forest fire detection and suppression [Ukazaniya po obnaruzheniyu i tusheniyu lesnykh pozharov] (1995) Federal forestry service of Russia, Moscow, 110 pGoogle Scholar
  8. 8.
    Volokitina AV, Korets MA, Sofronova TM (2013) Development of the Russian system of forest fire behavior prediction for fire management on GIS basis. In: International congress: forest fire fighting technologies, 11–13 November, pp 70–71. Ecology. Climate. NovosibirskGoogle Scholar
  9. 9.
    Volokitina AV, Sofronova TM, Korets MA (2018) Improvement of fire danger rating in the forest [Sovershenstvovanie otsenki pozharnoy opasnosti v lesu] (Methodical guidelines). IL SO RAN, KGPU, Krasnoyarsk, 43 pGoogle Scholar
  10. 10.
    Volokitina AV (2014) Prediction of pyrological situations in boreal forests. Vestn KrasGAU (1), 77–83Google Scholar
  11. 11.
    Korets MA, Volokitina AV (2014) Certificate of state registration for software program: program for calculation of pyrological description of forest inventory plots no 2014660252, October 3 2014Google Scholar
  12. 12.
    Sofronov MA, Volokitina AV (2010) Analysis of forest fire spread models. Izv S-Peterb Lesotekhnicheskoy Akad (191), 78–85Google Scholar
  13. 13.
    Sofronov MA (1964) Effect of relief on forest fire in Western Sayan. In: Soviet progress in forest fire control, pp 13–21. Consultants Bureau Enterprises, New YorkGoogle Scholar
  14. 14.
    Sofronov MA, Volokitina AV, Sofronova TM (2008) Wildland fires in mountain forests [Pozhary v gornykh lesakh]. IL SO RAN, KGPU, Krasnoyarsk, 388 pGoogle Scholar
  15. 15.
    Korets MA, Volokitina AV (2015) Certificate of state registration for software program: program for surface fire behavior prediction no. 2015661771, November 9 2015Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Aleksandra V. Volokitina
    • 1
    Email author
  • Tatiana M. Sofronova
    • 2
  • Mikhail A. Korets
    • 1
  1. 1.Sukachev Institute of Forest SB RASKrasnoyarskRussia
  2. 2.Astafiev Krasnoyarsk, State Pedagogical UniversityKrasnoyarskRussia

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