About the Project
FORESTER - Data Fusion of Sensor Networks and Fire Spread Modelling for Decision Support in Forest Fire Suppression
The FORESTER project, "Data Fusion of Sensor Networks and Fire Spread Modelling for Decision Support in Forest Fire Suppression," responds to Portugal's increasing vulnerability to devastating wildfires over the past two decades. The catastrophic 2017 wildfire season highlighted the urgent need for innovative tools to support effective decision-making in crisis situations. FORESTER seeks to address this challenge by developing an advanced Decision Support System (DSS) that combines multiple data sources with state-of-the-art fire behavior modeling.
The DSS integrates data from multi-sensor networks, cutting-edge satellite image processing, and near real-time fire spread predictions (FSP). Its design ensures that fire managers receive fast, reliable, and comprehensive information tailored to their operational needs. The project emphasizes the use of computational intelligence and visualization technologies to streamline complex information into actionable insights. By providing detailed predictions of fire behavior and real-time landscape analysis, FORESTER aims to transform wildfire suppression strategies, reducing environmental, economic, and human losses.
Scientific innovations include:
- Advanced data fusion techniques to merge information from ground, aerial, and satellite-based sensors.
- Real-time landscape monitoring using high-resolution satellite imagery.
- Predictive modeling of fire dynamics, enabling proactive resource allocation and strategic planning.
FORESTER's outcomes have the potential to significantly improve the efficiency of wildfire management, contributing to the protection of ecosystems, communities, and infrastructure in fire-prone regions like Portugal.
