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Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour

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  • Yassemi, S.
  • Dragićević, S.
  • Schmidt, M.

Abstract

The integration of geographic information systems (GIS) and environmental modelling has been widely investigated for more than a decade. However, such integration has remained a challenging task due to the temporal changes of environmental processes and the static nature of GIS. This study integrates GIS and cellular automata (CA) techniques to develop a fire behaviour model with a flexible and user-friendly end-user interface. The developed model incorporates topographic, forest fuel and weather variables. The performance of the implemented fire model is evaluated by comparison with fire spread simulations derived from Prometheus, the national Canadian fire behaviour modelling tool based on elliptical wave propagation principles. The developed fire behaviour model was tested using spatial data from the 2001 Dogrib Fire near Nordegg Alberta, Canada. Results from the simulations of the CA and wave propagation spread models indicate comparable agreement. This study shows that the GIS-CA model can simulate realistic forest fire scenarios. The developed GIS-based modelling tool enables dynamic animation within the GIS interface. Further, this tool can be adapted to other CA-based spatio-temporal modelling applications.

Suggested Citation

  • Yassemi, S. & Dragićević, S. & Schmidt, M., 2008. "Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour," Ecological Modelling, Elsevier, vol. 210(1), pages 71-84.
    • Handle: RePEc:eee:ecomod:v:210:y:2008:i:1:p:71-84
    DOI: 10.1016/j.ecolmodel.2007.07.020
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    References listed on IDEAS

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    1. P. D. Morley & Julius Chang, 2004. "Critical Behavior In Cellular Automata Animal Disease Transmission Model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 149-162.
    2. M Batty & Y Xie, 1994. "From Cells to Cities," Environment and Planning B, , vol. 21(7), pages 31-48, December.
    3. R White & G Engelen, 1997. "Cellular Automata as the Basis of Integrated Dynamic Regional Modelling," Environment and Planning B, , vol. 24(2), pages 235-246, April.
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    Citations

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    Cited by:

    1. Jonathan Corcoran & Gary Higgs & David Rohde & Prem Chhetri, 2011. "Investigating the association between weather conditions, calendar events and socio-economic patterns with trends in fire incidence: an Australian case study," Journal of Geographical Systems, Springer, vol. 13(2), pages 193-226, June.
    2. Naderpour, Mohsen & Rizeei, Hossein Mojaddadi & Khakzad, Nima & Pradhan, Biswajeet, 2019. "Forest fire induced Natech risk assessment: A survey of geospatial technologies," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    3. Liang, Lu & Li, Xuecao & Huang, Yanbo & Qin, Yuchu & Huang, Huabing, 2017. "Integrating remote sensing, GIS and dynamic models for landscape-level simulation of forest insect disturbance," Ecological Modelling, Elsevier, vol. 354(C), pages 1-10.
    4. Carlos Díaz‐Avalos & Pablo Juan, 2022. "Modeling the spatial evolution wildfires using random spread process," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    5. Morales, Juan Manuel & Mermoz, Mónica & Gowda, Juan Haridas & Kitzberger, Thomas, 2015. "A stochastic fire spread model for north Patagonia based on fire occurrence maps," Ecological Modelling, Elsevier, vol. 300(C), pages 73-80.
    6. Muzy, A. & Nutaro, J.J. & Zeigler, B.P. & Coquillard, P., 2008. "Modeling and simulation of fire spreading through the activity tracking paradigm," Ecological Modelling, Elsevier, vol. 219(1), pages 212-225.
    7. Xiaoli Hu & Xin Li & Ling Lu, 2018. "Modeling the Land Use Change in an Arid Oasis Constrained by Water Resources and Environmental Policy Change Using Cellular Automata Models," Sustainability, MDPI, vol. 10(8), pages 1-14, August.
    8. Gong, Jian-zhou & Liu, Yan-sui & Xia, Bei-cheng & Zhao, Guan-wei, 2009. "Urban ecological security assessment and forecasting, based on a cellular automata model: A case study of Guangzhou, China," Ecological Modelling, Elsevier, vol. 220(24), pages 3612-3620.
    9. Perez, Liliana & Dragicevic, Suzana, 2012. "Landscape-level simulation of forest insect disturbance: Coupling swarm intelligent agents with GIS-based cellular automata model," Ecological Modelling, Elsevier, vol. 231(C), pages 53-64.
    10. Susete Marques & Marco Marto & Vladimir Bushenkov & Marc McDill & JoséG. Borges, 2017. "Addressing Wildfire Risk in Forest Management Planning with Multiple Criteria Decision Making Methods," Sustainability, MDPI, vol. 9(2), pages 1-17, February.
    11. Wu, Daqian & Liu, Jian & Zhang, Gaosheng & Ding, Wenjuan & Wang, Wei & Wang, Renqing, 2009. "Incorporating spatial autocorrelation into cellular automata model: An application to the dynamics of Chinese tamarisk (Tamarix chinensis Lour.)," Ecological Modelling, Elsevier, vol. 220(24), pages 3490-3498.

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