A Cellular Automata Model for Fire Spreading Prediction

The modeling of fire spread in a flammable area is an interesting and challenging issue, widely studied in literature. Some of the models used for fire front evolution prediction are based on Cellular Automata (CA) approach, and they have shown a good agreement with other models and with experimental data. In this paper, the authors propose a new approach to this kind of models, introducing an "ignition probability" in the transition rules. This probability depends on several parameters, such as number of burning neighbors, wind direction and speed, land slope, fuel typology, etc.. As a starting approach, the number of neighbors that already burn seems to be the more interesting parameter to be considered in the ignition probability. Thus, the evolution of each single cell is governed by the presence of burning cells in its neighbourhood and, according to reality, the simulated fire spread does not present a regular shape of the fire front.