FORESTER - Data fusion of sensor networks and fire spread modelling for decision support in forest fire suppression, 2019

FORESTER - Data fusion of sensor networks and fire spread modelling for decision support in forest fire suppression, 2019

In the last 20 years, Portugal has been severely affected by large wildfires with dramatic consequences. The last year was the worst on record, with the largest burnt area extent and the largest number of casualties. It is urgent that the scientific community provides sound and efficient tools capable of improving decision making during wildfires crisis to minimize its negative consequences.

A key issue is the lack of decision support mechanisms for operational interventions [CTI17]. Due to the complexity of large wildfires, their effective suppression requires suitable and well-coordinated resources, up-to-date knowledge of the landscape, and accurate prediction of fire behavior. A Decision Support System (DSS) that can integrate the panoply of required information in a simple and efficient platform is the main scientific challenge of foRESTER. The main goal is to provide fire managers with useful and sound information to improve fire suppression strategy and decisions.

To accomplish this, foRESTER proposes a fast, reliable and informative DSS based on advanced computational intelligence and visualization techniques, that integrates innovative technologies from multi-sensor systems, cutting edge satellite image processing, and near real-time (NRT) fire spread predictions (FSP).