Modeling forest fire spread and spotting process with small world networks

Porterie, B.; Zekri, N.; Clerc, Jean-Pierre; Loraud, J. C.

doi:10.1016/j.combustflame.2006.12.008

Cited by 45 publications

(24 citation statements)

References 34 publications

(51 reference statements)

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“…This is based on a cellular automata approach by introducing a two-dimensional lattice to mimic the forests that the wildfires would spread in. There exist works using a cellular automata or lattice model approach to study wildfire; see, e.g., Bak et al (1990), Caldarelli et al (2001), and Porterie et al (2007). For example, people have used hexagonal cellular automata to model wildfire spreading (Trunfio, 2004;Hernandez Encinas et al, 2007;Avolio et al, 2012).…”

Section: Model and Numerical Simulationmentioning

confidence: 99%

“…Therefore, each lattice site will only be affected by four nearest neighbors during our simulation. On the other hand, if the site has a neighboring site in state I, it will then to study wildfire, see e.g., Caldarelli et al, 2001;Porterie et al, 2007). For example, people have used hexagonal cellular automata to model wildfire spreading (Trunfio, 2004;Hernandez Encinas et al, 2007;Avolio et al, 2012).…”

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confidence: 99%

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Fractal dimensions of wildfire spreading

Wang

Lee

2014

Nonlin. Processes Geophys.

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Abstract. The time series data of 31 wildfires in 2012 in the US were analyzed. The fractal dimensions (FD) of the wildfires during spreading were studied and their geological features were identified. A growth model based on the cellular automata method is proposed here. Numerical study was performed and is shown to give good agreement with the fractal dimensions and scaling behaviors of the corresponding empirical data.

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Section: Model and Numerical Simulationmentioning

confidence: 99%

mentioning

confidence: 99%

Fractal dimensions of wildfire spreading

Wang

Lee

2014

Nonlin. Processes Geophys.

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“…Recent simulation studies have attempted to explicitly model the transport and distribution of firebrands ahead of idealized fires (e.g., Porterie et al 2007, Sardoy et al 2008. The extent that new ignitions ahead of the main fire front result in an increase in the overall rate of fire spread (Fig.…”

Section: Model Applicabilitymentioning

confidence: 99%

Limitations on the accuracy of model predictions of wildland fire behaviour: A state-of-the-knowledge overview

AlexanderMartin

Cruz

2013

The Forestry Chronicle

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The degree of accuracy in model predictions of wildland fire behaviour characteristics are dependent on the model's applicability to a given situation, the validity of the model's relationships, and the reliability of the model input data. While much progress has been made by fire behaviour research in the past 35 years or so in addressing these three sources of model error, the accuracy in model predictions are still very much at the mercy of our present understanding of the natural phenomena exhibited by free-burning wildland fires and the inherent temporal and spatial variability in the fire environment. This paper will serve as a state-of-the-art primer on the subject of error sources in model predictions of wildland fire behaviour and includes a short historical overview of wildland fire behaviour research as it relates to model development.

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“…Case 6 -Porterie et al [23] used a layer of pine needles from Pinus Pinaster. Our model prediction was in good agreement with the one provided by the small network calculation that they used (Fig.…”

Section: -Comparison With Different Experiments (Laboratory and Fieldmentioning

confidence: 99%