Leveraging Mapping Tools and Analytics for Advanced Wildfire Detection and Crisis Management

Aiming at addressing the uncertainty and socio-economic dimensions inherent in wildfire management, and to minimize the impact of wildfires through timely and informed decision-making, our research introduces an architectural framework for a software platform for Detection of Emerging Fire-related Situations and Response Process Management.

The event-driven architecture processes real-time, heterogeneous data from sources like satellite fire detection, meteorological stations, environmental sensors, and AI-enhanced UAV imagery. Events such as temperature anomalies or fire detections trigger dynamic response workflows. Modular, scalable components facilitate seamless ingestion, processing, and analysis of multi-source data. Algorithms model and predict fire behaviour, optimize resource allocation, and guide emergency response strategies. System outputs, including analytics, risk assessments, and situational hazards (e.g., endangered wildlife), are shared via dashboards, mobile apps, AR devices, and text messaging, ensuring broad accessibility.

The most prominent example of said interfaces is an OSM-based mapping tool that emphasizes intuitive navigation, interactive controls, and customizable data visualizations. It incorporates modular components that support real-time data visualization, fire risk assessment, and geospatial analysis. Key features include a user-defined data module enabling seamless integration of custom geospatial data, a non-fuel areas module designed to identify non-fuel zones, and a monitoring module offering comprehensive real-time wildfire surveillance.

The design of both the platform components and the user experience have been co-developed with domain experts, ensuring alignment with operational needs. These experts, including firefighters, environmental engineers, local authorities, and wildlife administrators, contributed to defining event patterns, scenarios, response workflows and feedback on usability, ensuring the system is tailored to real-world wildfire management challenges.

The architectural framework was validated within the TREEADS project, funded by the European Commission’s Horizon 2020 Programme. In particular, two field trials with distinct scenarios took place in Samaria Gorge, Crete, Greece, and the Sorrento Peninsula, Italy, aiming at demonstrating the system’s ability to improve established practices.

Keywords: software architecture; event-driven architectures; decision support system; response process management; remote sensing; data visualisation; mapping tools; real-time data processing; analytics; wildfire management system; real-time risk assessment; OpenStreetMap (OSM); real-time analytics; data stream processing; context-aware wildfire detection; situational awareness

This research has been carried out in the scope of the TREEADS project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101036926. The authors acknowledge valuable help and contributions from all partners of the TREEADS project.