Fractals in the Propagation of Forest Fires and Stochastic Models

Abstract

The goal of this study is to compare models and real data to better understand the role of stochastic dynamics in forest-fire propagation rendering fractal geometries. I analysed empirical data and developed stochastic models to simulate fire spread. The main results show that forest fires have fractal dimensions, shown as repetitive and self-similar patterns in their structure. This discovery suggests that stochastic models can be useful in understanding and predicting the dynamics of forest fire spread. Furthermore, the simulation using the bond percolation stochastic model has yielded more similar results to the empirical data compared to site percolation, although there is room for improvement. Discrepancies might be caused by not considering the existence of natural boundaries, changes in atmospheric conditions, or human intervention in the evolution of a forest fire