Natural Hazards

, Volume 91, Issue 1, pp 309–319 | Cite as

Forest fire spread simulation algorithm based on cellular automata

  • Xiaoping Rui
  • Shan Hui
  • Xuetao Yu
  • Guangyuan Zhang
  • Bin Wu
Original Paper
  • 134 Downloads

Abstract

Traditional models result in low efficiency and poor accuracy when simulating the spread of large-scale forest fires. We constructed an improved model that couples cellular automata with an existing forest fire model to ensure better time accuracy of forest fire spread. Our model considers the impact of time steps on simulation accuracy to provide an optimal time step value. The model was tested using a case study of forest fire spread at Daxing’an Mountain in May 2006. The results show that the optimal time step for the forest fire spread geographic cellular automata simulation algorithm is 1/8 of the time taken for cellular material to be completely combusted. When compared with real fire data from Landsat Thematic Mapper (TM) images, our model was found to have high temporal and spatial consistency, with a mean Kappa coefficient of 0.6352 and mean accuracy of 87.89%. This algorithm can be used to simulate and predict forest fire spread and is also reversible (i.e., it can identify fire source points).

Keywords

Forest fire spread simulation Cellular automata Remote sensing Fire point identification Forest fire disaster 

Notes

Acknowledgements

This study was supported by the National Key Research and Development Program (Grant No: 2017YFB0503600) the National Natural Science Foundation of China (Grant No. 41771478), the Beijing Natural Science Foundation (Grant No. 8172046), and the Hebei Province Natural Science Fund (Grant No. D2016210008).

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijingChina
  2. 2.Land Surveying, Planning and Design Institute of Shaanxi Provincial Land Engineering Construction GroupXi’anChina
  3. 3.School of Traffic and TransportationShijiazhuang Tiedao UniversityShijiazhuangChina

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