A stochastic model for forest fire growth
We consider a stochastic fire growth model, with the aim of predicting the behavior of large forest fires. Such a model can describe not only average growth, but also the variability of the growth. Fire is modeled as a random phenomenon on a regular spatial grid, specifically, an interacting particle system modeled as a continuous-time Markov chain on a lattice. Each lattice site changes state according to local transition rates, which model the competing physical processes of fire spread; spotting, and burnout. The rate functions, which are currently tentative, could be based on topography, fuel moisture, and local weather. Implementing such a model in a computing environment allows one to obtain probability contour plots, burn size distributions, and distributions of time to specified events. Such a model also allows the incorporation of a stochastic spotting mechanism.
fire spread lattice model markov process