Modeling occurrence and the spread of forest fire using cellular automata approach (Case Study: Arasbaran protected area)

Document Type : Research Paper


1 Department of Remote Sensing and GIS, Faculty of Geography and Planning, University of Tabriz, Iran

2 Department of Civil Engineering, Faculty of Technical and Engineering of Marand, University of Tabriz, Iran


Each year fire damages the natural environment remarkably. Cellular automata is a way of modeling and simulating processes in the real world.
We can take precautionary steps toward preventing fire and damages after, by knowing how it spreads and providing risk plans.
In this research, the fire risk model has been used for modeling fire occurrence which is composed of factors such as slope, slope direction, vegetation cover, and prevailing wind direction. During this process, areas with a high risk of fire have been determined and by using the cellular automata model. In this model, the Alexandridis method in MATLAB was used. it became possible to simulate the fire spread model of Arasbaran forests in the northwest of Iran. This area holds the record of most fire statistics in the whole province and considering huge resources of flora and fauna available there, it is essential to protect this area most of all from fire.
Results have shown that 56.36% of this area is highly exposed to fire. Slope gradient and slope direction are two important factors in the start and spreading of fire. Human factors play a great role in the development of fire. also, results indicate that using cellular automata along with GIS, not only accelerates the simulation of fire but also it has great accuracy.


Aalizadeh, L., Karinian, R., Ejlali, F., 2011. investigating the main causes of Deforestation in forests of Lorestan Province and suggested solutions. Natural hazards. National Congress on Central Zagros Forests, Capabilities and bottlenecks, Lorestan, Iran. (In Persian).
Adab, H., Kanniah, K. D., Solaimani, K., 2013. Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques. Natural hazards, 65(3), 1723-1743. ‏
Ajin, R.S., Loghin, A.M., Vinod, P.G., Jacob, M.K., 2016. Forest fire risk zone mapping using RS and GIS techniques: a study in Achankovil forest division, Kerala, India. Journal of Earth, Environment and Health Sciences, 2(3), 109-115.
Alexandridis, A., Vakalis, D., Siettos, C. I., Bafas, G. V., 2008. A cellular automata model for forest fire spread prediction: The case of the wildfire that swept through Spetses Island in 1990. Applied Mathematics and Computation, 204(1), 191-201. ‏
Ardakani, A., ValadaneZoj, M. J., Mansourian, A., 2009. The spatial analysis of fire across the country using RS and GIS. Journal of (In Persian)
Ebrahimi, H., Rasouli, A. A., Mokhtari, D., 2018. Investigation of changes in fire risk and its influencing factors using MAXENT model, Case Study: Forests and Rangelands of East Azerbaijan Province. Geography and Environmental Hazards, 25, 57-73. (In Persian).  
Encinas, A.H., Encinas, L.H., White, S.H., del Rey, A.M., S’anchez, G.R., 2007.Simulation of forest fire fronts using cellular automata. Advances in Engineering Software Journal, 38, 372–378.
Eskandari, S., 2017. Methods of modeling and evaluation of fire occurrence risk in the forests of world and Iran. Human and Environment, 15 (3), 91-110. (In Persian).  ‏
Eskandari, S., Oladi, J., 2017. Modelling of forest fire spread using Cellular Automata. Natural hazards. Geographical Planning of Space Quarterly Journal, 7(25), 37-53. (In Persian).
Eugenio, F.C., Dos Santos, A.R., Fiedler, N.C., Ribeiro, G.A., da Silva, A.G., Dos Santos, Á.B., Paneto, G.G. and Schettino, V.R., 2016. Applying GIS to develop a model for forest fire risk: a case study in Espírito Santo, Brazil. Environmental Management Journal, 173, 65-71. ‏
Ghaemi Rad T, Karimi M., 2017. Comparison of Different Neighborhoods in Fire Spread Modelling Using Cellular Automata. Geospatial Engineering Journal. 19-27. (In Persian).
Ghaemi Rad, T., Karimi, M., 2015. Evaluation performances of different forest fire spread models using cellular automata (case study: The forests of Lakan district in Rasht). Iranian Journal of Forest and Poplar Research, 23(1), 64-78. (In Persian).  
Hejazi, M., Roustayi, S., Khayam, M., 2009. The introduction and analysis of the physiographic and topographic reactions of Arasbaran biosphere reserve over vegetation zoning. Journal of (In Persian) Quarterly journal of geography and planning, 27, 141-158.
Li, C., Hans, H., Barclay, H., Liu, J., Carlson, G., Campbell, D., 2008. Comparison of spatially explicit forest landscape fire disturbance models. Forest Ecology and Management, 254(3), 499-510. ‏
Marozas, V., Racinskas, J., Bartkevicius, E., 2007. Dynamics of ground vegetation after surface fires in hemiboreal Pinus sylvestris forests. Forest Ecology and Management, 250(1-2), 47-55. ‏
Mohammadi, F., Shabanian, N., Pourhashemi, M., Fatehi, P., 2011. Risk zone mapping of forest fire using GIS and AHP in a part of Paveh forests. Iranian Journal of Forest and Poplar Research, 18, 4(42), 569-586. (In Persian).  
Nematollahi, M.A., Babaei Naiij, M., Layeghi, M., Aghaii Zadeh, R., 2012. Quantifying of schooling responses of rosy barb (Puntius barbus) to acute stress using computer vision. In: McKinlay, D. (Ed.). Proceedings of 10th International Congress on the Biology of Fish, Madison, Wisconsin, USA. 170-180.
Rui, X., Hui, S., Yu, X. Zhang, G., Wu, B., 2018. Forest fire spread simulation algorithm based on cellular automata. Natural hazards, 210(1-2), 71-84. ‏
Vakalis, D., Sarimveis, H., Kiranoudis, C., Alexandridis, A., Bafas, G., 2004. A GIS based operational system for wildland fire crisis management I. Mathematical modelling and simulation. Applied Mathematical Modelling, 28(4), 389-410. ‏
Valizadeh, KH., Omrani, K., Khosroshahi, S. S., 2014. Forest fire risk assessment using multi-criteria analysis: A case study Kaleybar Forest. In International Conference on Agriculture, Environment and Biological Sciences (ICFAE’14) June 4-5, Antalya (Turkey). 30-33. ‏
Wang, S. L., Lee, H. I., Li, S. P., 2014. Fractal dimensions of wildfire spreading. Nonlinear Processes in Geophysics, 21(4), 815-823.‏
Xu, D., Dai, L.M., Shao, G.F., Tang, L., and Wang, H. 2005. Forest fire risk zone mapping from satellite images and GIS for Baihe forestry Bureau, Jilin China. Journal of forestry research, 15(3): 169-174.
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, 210(1-2), 71-84. ‏
Zakeri Pashakolaei M, Alvaninejad S, Esmailzade O., 2014. Relationship Between Plant Biodiversity and Topographical Factors in Forests of West Mazandaran (Case study: Research forest of Tarbiat Modares University). Iranian Journal of Applied Ecology. 3(8) :1-16. (In Persian).