We developed a Reaction Diffusion Convection (RDC) model for forest fire propagation coupled to a visualization platform with several functionalities requested by local firefighters. The dynamical model aims to understand the key mechanisms driving fire propagation in the Patagonian region. We'll show in this work the first tests considering combustion and diffusion in artificial landscapes. The simulator, developed in CUDA/OpenGL, integrates several layers including topography, weather, and fuel data. It allows to visualize the fire propagation and also to interact with the user in simulation time. The Fire Weather Index (FWI), extensively used in Argentina to support operative preventive measures for forest fires management, was also coupled to our visualization platform. This additional functionality allows the user to visualize on the landscape the fire risks, that are closely related to FWI, for Northwest Patagonian forests in Argentina.

Our motivation comes from the need of a tailored computational tool for simulation and prediction of forest fire propagation, to be used by firefighters in Patagonia, Argentina. Based on previous works on Graphic Processing Units (GPU) for fitting and simulating fires in our region, we developed a visualization interface for real time computing, simulation and prediction of fire propagation. We have the possibility of changing the ensemble of raster maps layers to change the region in which fire will propagate.The visualization platform runs on GPUs and the user can rotate and zoom the landscape to select the optimal view of fire propagation. Opacity of different layers can be regulated by the user, allowing to see fire propagation at the same time that underlying vegetation, wind direction and intensity. The ignition point can also be selected by the user, and firebreaks can be plotted while simulation is going on.After the performance of a high number of stochastic simulations in parallel in GPUs, the application shows a map of the final fire surface colored according to the probability that a given cell burns. In this way the user can visually identify the most critical direction for fire propagation, a useful information to stop fire optimizing resources, which is specially important when they are scarce like is the case of our Patagonia region.