Simulating wildfire spreading processes in a spatially heterogeneous landscapes using an improved cellular automaton model

A better understanding of wildfire spreading processes is expected both for long-term wildfire management planning and effective suppression strategies so that wildfires-caused losses in natural resources, endangered species, human lives and properties can be reduced. The cellular automaton (CA) method is useful and powerful for modeling natural and artificial systems in which the constituent parts are locally and tightly interacted. The temporal and spatial characteristics of wildfires make the CA method a preferred choice to model the temporal and spatial variability. In this study, hexagonal tessellation space was used to develop a CA model and then the Rothermers fire spreading model (1972) was integrated to the CA model to simulate wildfire-spreading processes spatially and temporally. The hexagon-based wildfire spreading CA model was verified with the experimental data and also tested using the data obtained in the southern part of Gansu province (China), and the comparison between the simulated results and observed data suggests that this CA-based model can be used to provide useful information for managing wildfires over heterogeneous landscapes