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Forest fire spread simulation algorithm based on cellular automata

Author

Listed:
  • Xiaoping Rui

    (University of Chinese Academy of Sciences)

  • Shan Hui

    (Land Surveying, Planning and Design Institute of Shaanxi Provincial Land Engineering Construction Group)

  • Xuetao Yu

    (Shijiazhuang Tiedao University)

  • Guangyuan Zhang

    (University of Chinese Academy of Sciences)

  • Bin Wu

    (University of Chinese Academy of Sciences)

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).

Suggested Citation

  • Xiaoping Rui & Shan Hui & Xuetao Yu & Guangyuan Zhang & Bin Wu, 2018. "Forest fire spread simulation algorithm based on cellular automata," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(1), pages 309-319, March.
    • Handle: RePEc:spr:nathaz:v:91:y:2018:i:1:d:10.1007_s11069-017-3127-5
    DOI: 10.1007/s11069-017-3127-5
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    References listed on IDEAS

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    1. Duff, Thomas J. & Chong, Derek M. & Tolhurst, Kevin G., 2015. "Using discrete event simulation cellular automata models to determine multi-mode travel times and routes of terrestrial suppression resources to wildland fires," European Journal of Operational Research, Elsevier, vol. 241(3), pages 763-770.
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    Cited by:

    1. Chen Cheng & Hui Zhou & Xuchao Chai & Yang Li & Danning Wang & Yao Ji & Shichuan Niu & Ying Hou, 2020. "Adoption of image surface parameters under moving edge computing in the construction of mountain fire warning method," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-16, May.
    2. Xinzheng Lu & Donglian Gu & Zhen Xu & Chen Xiong & Yuan Tian, 2020. "CIM-Powered Multi-Hazard Simulation Framework Covering both Individual Buildings and Urban Areas," Sustainability, MDPI, vol. 12(12), pages 1-28, June.
    3. Eric Innocenti & Corinne Idda & Dominique Prunetti & Pierre-Régis Gonsolin, 2022. "Agent-based modelling of a small-scale fishery in Corsica," Post-Print hal-03886619, HAL.
    4. Yuping Tian & Zechuan Wu & Shaojie Bian & Xiaodi Zhang & Bin Wang & Mingze Li, 2022. "Study on Spatial-Distribution Characteristics Based on Fire-Spot Data in Northern China," Sustainability, MDPI, vol. 14(11), pages 1-15, June.

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