Forest fires are 'quasi-natural' hazards which play an essential role in the evolution and adaptation of ecosystems as well as in the human activities related to the land use.
In environments largely anthropized, as the areas bordering the Mediterranean basin, wildfires are an important cause of environmental vulnerability and risk to human activities. In the last decades, just in the Mediterranean areas, an increase in extreme weather events (increased frequency of heat waves and prolonged dry spells) has been observed, leading to a higher wildfire risk (for intensity, extension and frequency of the events).
In this context a wildfire forecasting system has been developed to simulate forest fires in Sardinia. The system is suitable for a real-time management of wildfire events as well as for the study of past events.
This wildfire forecast system has been developed inside the project "Cloud for Remote Visualization", in collaboration with Nice srl and financed by the Autonomous Region of Sardinia.
The system, implemented on a dedicated Cloud Computing infrastructure, is characterized by a surface spread model based on the Rothermel’s theory and a fire propagation algorithm based on a Fast Marching Method specifically developed for the project. The weather conditions necessary to drive the wildfire model are produced daily by means of a high resolution weather forecast chain based on the Bolam-Moloch models. A higher accuracy of the wind simulation is obtained with a dedicated fluid dynamic solver, build with the CFD package OpenFOAM. This solver is based on the mass-consistent approximation, allowing for a quick and efficient downscaling of the wind from the typical weather scales to the landscape scales compatible with the fire forecast requirements. Furthermore, the high resolution of the dataset used (topography and land use at landscape scales) allows to study also wildfre spreading on wildland–urban interfaces.
A web portal has been therefore developed. It offers a user friendly interface that allows an easy interaction with the complex wildfire forecast system as well as allows the analysis and evaluation of the results through an accelerated remote 3D visualization.

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