Enhancing wildfire simulation with wind and vegetation parameters using Cellular Automata in Sete Cidades National Park: a study in the Brazilian Cerrado biome
DOI:
https://doi.org/10.5540/tcam.2024.025.e01757Keywords:
Forest fires, cellular automata, computational simulation, wildfire propagation, wind direction, prevention measuresAbstract
Wildfires pose a significant threat to natural ecosystems, human lives, and properties worldwide. Developing effective prevention and control strategies is crucial for minimizing the risk of catastrophic wildfire events. In this context, computational modelling has emerged as a valuable tool for simulating and analyzing wildfire behavior, which can aid in identifying potential areas for intervention and prevention measures. This article presents a cellular automata model for simulating forest fires in Sete Cidades National Park, Brazil. The model takes into account the wind direction and speed, vegetation type, and probability of burning in a two-dimensional lattice representing the forest area of interest. The simulation output is analyzed to determine the extent of the damage caused by the fire and to identify critical parameters for wildfire propagation. The results highlight the importance of considering wind direction and speed when developing prevention and control strategies for wildfires. By providing insights into the behavior of wildfires, computational modeling can support decision-making processes and facilitate the development of effective policies to manage the risk of wildfires.References
S. T. Alvarado, I. S. de Carvalho, T. M. Ferraz, and T. S. Silva, “Effects of fire suppression policies on fire regimes in protected areas in the cerrado.,” Biodiversidade Brasileira-BioBrasil, no. 1, pp. 200–200, 2019.
M. d. Q. Matos and J. M. Felfili, “Florística, fitossociologia e diversidade da vegetação arbórea nas matas de galeria do parque nacional de sete cidades (pnsc), piauí, brasil,” Acta botânica brasílica, vol. 24, pp. 483–496, 2010.
M. E. A. Oliveira, F. R. Martins, A. Castro, and J. R. d. Santos, “Classes de cobertura vegetal do parque nacional de sete cidades (transição campofloresta) utilizando imagens tm/landsat, ne do brasil,” XIII Simpósio Brasileiro de Sensoriamento Remoto, vol. 13, 2007.
C. Tavares and M. Lazo, “Dynamic systems with fractional derivatives applied to interagent populations problems,” Trends in Computational and Applied Mathematics, vol. 23, pp. 299–314, 2022.
D. H. Serrano and A. M. del Rey, “Virtual cyclic cellular automata, finite group actions and recursive properties,” Information Sciences, vol. 608, pp. 917–930, 2022.
M. E. A. Ferreira, A. L. Quinta, D. A. Lima, L. G. Martins, and G. Oliveira, “Automatic evolutionary adjustment of cellular automata model for forest fire propagation,” in International Conference on Cellular Automata for Research and Industry, pp. 235–245, Springer, 2022.
H. A. Lima and D. A. Lima, “Autômatos celulares estocásticos bidimensionais aplicados a simulação de propagação de incêndios em florestas homogêneas,” in Workshop de Comp. Aplicada a Gestão do Meio Amb. e Rec. Naturais, pp. 15– 24, SBC, 2014.
D. A. Lima, E. Cabral Jr, I. T. Almeida, J. P. Andrade, J. P. Fonseca, M. E. Santos, N. T. Nunes, and V. H. Bernardes, “A fire elitist cellular automatonbased model to verify pedestrian flow simulated in real environments using arduino,” Proc. Series of the Brazilian Society of Computational and App. Mathematics, vol. 7, no. 1, 2020.
E. R. Lira, H. B. de Macêdo, D. A. Lima, L. Alt, and G. Oliveira, “A reversible system based on hybrid toggle radius-4 cellular automata and its application as a block cipher,” Natural Computing, pp. 1–17, 2023.
M. El Naschie, “Cellular automata based on the golden mean number system as a foundation for artificial intelligence and artificial life,” International Journal of Artificial Intelligence and Mechatronics, vol. 8, no. 6, 2020.
Y. Zhang and J. Zhang, “Modeling of solidification microstructure evolution in laser powder bed fusion fabricated 316l stainless steel using combined computational fluid dynamics and cellular automata,” Additive Manufacturing, vol. 28, pp. 750–765, 2019.
J. Zeng, Y. Qian, P. Mi, C. Zhang, F. Yin, L. Zhu, and D. Xu, “Freeway traffic flow cellular automata model based on mean velocity feedback,” Physica A: Statistical Mechanics and its Applications, vol. 562, p. 125387, 2021.
B. Kitchenham, O. P. Brereton, D. Budgen, M. Turner, J. Bailey, and S. Linkman, “Systematic literature reviews in software engineering–a systematic literature review,” Information and software technology, vol. 51, no. 1, pp. 7–15, 2009.
S. Fabbri, C. Silva, E. Hernandes, F. Octaviano, A. Di Thommazo, and A. Belgamo, “Improvements in the start tool to better support the systematic review process,” in Proceedings of the 20th international conference on evaluation and assessment in software engineering, pp. 1–5, 2016.
N. M. Gharakhanlou and N. Hooshangi, “Dynamic simulation of fire propagation in forests and rangelands using a gis-based cellular automata model,” International Journal of Wildland Fire, vol. 30, no. 9, pp. 652–663, 2021.
W. Sun, W. Wei, J. Chen, and K. Ren, “Research on amazon forest fire based on cellular automata simulation,” in 2021 20th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES), pp. 175–178, IEEE, 2021.
S. Darmawan, D. K. Sari, K. Wikantika, A. Tridawati, R. Hernawati, and M. K. Sedu, “Identification before-after forest fire and prediction of mangrove forest based on markov-cellular automata in part of sembilang national park, banyuasin, south sumatra, indonesia,” Remote Sensing, vol. 12, no. 22, p. 3700, 2020.
S. Hesam and K. V. Kamran, “Intelligent management occurrence and spread of front fire in gis by using cellular automata. case study: Golestan forest,” International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2019.
F. Giannino, L. Russo, D. Ascoli, A. Migliozzi, C. I. Siettos, and S. Mazzoleni, “Cellular automata simulation of forest fire behavior on italian landscape: The case of sardinia,” in AIP Conference Proceedings, vol. 1906, p. 100006, AIP Publishing LLC, 2017.
A. Schadschneider, A. Kirchner, and K. Nishinari, “Ca approach to collective phenomena in pedestrian dynamics,” in Cellular Automata: 5th International Conference on Cellular Automata for Research and Industry, ACRI 2002 Geneva, Switzerland, October 9–11, 2002 Proceedings 5, pp. 239–248, Springer, 2002.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Trends in Computational and Applied Mathematics
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Copyright
Authors of articles published in the journal Trends in Computational and Applied Mathematics retain the copyright of their work. The journal uses Creative Commons Attribution (CC-BY) in published articles. The authors grant the TCAM journal the right to first publish the article.
Intellectual Property and Terms of Use
The content of the articles is the exclusive responsibility of the authors. The journal uses Creative Commons Attribution (CC-BY) in published articles. This license allows published articles to be reused without permission for any purpose as long as the original work is correctly cited.
The journal encourages Authors to self-archive their accepted manuscripts, publishing them on personal blogs, institutional repositories, and social media, as long as the full citation is included in the journal's website version.
