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Forest fire spread model based on the grey system theory

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Abstract

Accurate prediction of forest fire spread is very essential for minimizing its effects. Although many models have been developed to predict the forest fire spread, all these models require several parameters, sometimes, cannot be obtained in a real time. In this paper, the grey system theory was applied for forest fire spread model developing. By preprocessing and fusing the MODIS remote sensing data, the sequence data of the grey model can be confirmed. After making precision comparison among least square estimation algorithm, least square interpolation algorithm and ER algorithm, forest fire spread GM(1, 1) model was developed with ER algorithm and precision of the model was evaluated at the same time. The results showed that the fitting precision and predicting precision of the model were both high, of which the one-level model made up 50%, the two-level 25% and the model between the one-level and the two-level 25%. The prediction accuracy of forest fire spreading model was tested to meet the requirement of modeling. GM(1, 1) model provided a new approach for the study of forest fire spread simulation.

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References

  1. Chang Y, Zhu Z, Feng Y, Li Y, Bu R, Hu Y (2016) The spatial variation in forest burn severity in Heilongjiang Province, China. Nat Hazards 81:981–1001

    Article  Google Scholar 

  2. Quintano C, Fernández-Manso A, Roberts DA (2013) Multiple endmember spectral mixture analysis (MESMA) to map burn severity levels from Landsat images in Mediterranean countries. Remote Sens Environ 136:76–88

    Article  Google Scholar 

  3. Sun T, Zhang L, Chen W, Tang X, Qin Q (2013) Mountains forest fire spread simulator based on geo-cellular automaton combined with Wang Zhengfei velocity model. IEEE J Sel Top Appl Earth Obs Remote Sens 6:1971–1987

    Article  Google Scholar 

  4. Zheng Z, Zeng Y, Li S, Huang W (2016) A new burn severity index based on land surface temperature and enhanced vegetation index. Int J Appl Earth Obs Geoinf 45:84–94

    Article  Google Scholar 

  5. Yuan CM, Wen DY (2000) Outline of forest fire behavior research. World For Res 13(6):27–31

    Google Scholar 

  6. Du JH, Tian XR (2012) Forest fire spreading model and its application. For Fire Prev 2:31–34

    Google Scholar 

  7. Perry GLW (1998) Current approaches to modeling the spread of wildland fire: a review. Prog Phys Geogr 22:222–245

    Article  Google Scholar 

  8. Dupuy JL (1999) An analysis of semi-empirical and physical models for fire spread in wildland fuels. In: Eftichidis G, Balabanis P, Ghazi A (eds) Proceedings of the Advanced Study Course on Wildfire Management. Algosystems S.A., Athens, pp 419–438

  9. Andre JCS, Viegas DX (1994) A strategy to model the average fireline movement of a light to medium intensity surface forest fire. In: Proceedings of the 2nd International Conference on Forest Fire Research, Coimbra, pp 221–242

  10. Weber RO (2001) Wildland fire spread models. In: Johnson EA, Miyanishi K (eds) Forest fires behaviour and ecological effects. Academic Press, San Diego, pp 151–169

    Chapter  Google Scholar 

  11. Pastor E, Zarate L, Planas E, Arnaldos J (2003) Mathematical models and calculation systems for the study of wildland fire behaviour. Prog Energy Combus Sci 29:139–153

    Article  Google Scholar 

  12. Mell WE, Manzello SL, Maranghides A (2006) Numerical modeling of fire spread through trees and shrubs. In: Proceedings of the International Conference on Forest Fire Research, Figueira da Foz

  13. Pitts WM (1991) Wind effects on fires. Prog Energy Combust Sci 17:83–134

    Article  Google Scholar 

  14. Beer T (1991) Bushfire rate-of-spread forecasting: deterministic and statistical approaches to fire modeling. J. Forecast 10:301–317

    Article  Google Scholar 

  15. Halada L, Weisenpacher P (2005) Principles of forest fire spread models and their simulation. J Appl Math Stat Inf 1(1):3–13

    Google Scholar 

  16. Glasa J, Halada L (2008) On elliptical model for forest fire spread modeling and simulation. Math Comput Simul 78(1):76–88

    Article  MathSciNet  Google Scholar 

  17. Zhao FA (2017) Review of wildland fire spread modelling. World For Res 30(2):46–50

    Google Scholar 

  18. Oldehoeft R (2000) Taming complexity in high-performance computing. Math Comput Simul 54:314–357

    Article  MathSciNet  Google Scholar 

  19. Artés T, Cortes A, Margalef T (2016) Large forest fire spread prediction: data and computational science. Proc Comput Sci 80:909–918

    Article  Google Scholar 

  20. Fu ZQ, Sun QH, Cai YL, Dai EF (2002) Research on forecasting model of forest fire based on grey system theory. Sci Silvae Sin 38(5):95–100

    Google Scholar 

  21. Deng JL (1982) Control problems of grey systems. Syst Control Lett 5:288–294

    MathSciNet  MATH  Google Scholar 

  22. Deng JL (1982) Grey control system. J Huazhong Univ Sci Technol 3:9–18

    Google Scholar 

  23. Liu SF (1999) Grey system theory and its application. The Science Publishing Company, Beijing, pp 117–122

    Google Scholar 

  24. Zheng Z, Huang W, Li S, Zeng Y (2017) Forest fire spread simulating model using cellular automaton with extreme learning machine. Ecol Model 348(348):33–43

    Article  Google Scholar 

Download references

Acknowledgements

Financial support for this study was provided through the Fundamental Research Funds for the Central University (2015ZCQ-LX-01), National Natural Science Foundation of China (No. 41401650). We are grateful to the undergraduate students and staff of the Laboratory of Forest Management and “3S” technology, Beijing Forestry University.

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Authors and Affiliations

  1. Beijing Key Laboratory of Precision Forestry, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Box 111, Beijing, 100083, China

    Chundong Lv, Jia Wang & Fanfei Zhang

  2. College of Forestry, Beijing Forestry University, No. 35 Qinghua East Road, Haidian District, Box 111, Beijing, 100083, China

    Chundong Lv, Jia Wang & Fanfei Zhang

Authors
  1. Chundong Lv
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  2. Jia Wang
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  3. Fanfei Zhang
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Correspondence to Jia Wang.

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Lv, C., Wang, J. & Zhang, F. Forest fire spread model based on the grey system theory. J Supercomput 76, 3602–3614 (2020). https://doi.org/10.1007/s11227-018-2560-x

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  • DOI: https://doi.org/10.1007/s11227-018-2560-x

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