With a combined investment of €3m, the initiatives are designed to improve how Spanish wildfires are anticipated, detected, monitored and managed.
The projects, which signed contracts with ESA InCubed and began in July 2026, bring together satellite Earth observation, artificial intelligence (AI), meteorological modelling and other technologies.
Their applications cover different stages of wildfire management, from prevention and risk forecasting to active-fire monitoring and post-fire assessment.
The programme comes as the need for stronger wildfire capabilities has become increasingly urgent.
Heatwaves, prolonged drought and changing weather patterns are contributing to wildfires becoming more frequent, intense and difficult to predict, while recent Spanish wildfires have highlighted the threat to communities, ecosystems and infrastructure.
Commenting on the initiative, Carlos Urbina Ortega, End-to-end System Engineer at ESA Φ-lab Invest Office and InCubed Officer for the management of this national campaign in Spain, said: “Wildfires are becoming faster and more dangerous, threatening lives, homes and ecosystems.
“Through this InCubed call with AEE, we are turning satellite data into real-world tools for every stage of a fire. These eight new applications will give emergency teams the exact information they need to react quicker, manage crises better and ultimately save lives and protect nature.”
The joint call was launched in 2025 specifically to support Earth observation applications across the wildfire management cycle. The eight selected projects are focused on addressing different limitations in the information available to authorities and emergency teams.
One of the projects, FIREAI-OPS, is being delivered by GEOAI Analytics, Multiverse Computing and CATEC. It aims to bring together Earth observation, airborne and terrestrial information, AI, and physics-based fire modelling in a common operational environment.
The objective is to provide emergency teams with more rapidly updated information, helping them anticipate how a fire may develop, coordinate observations and improve situational awareness during an incident.
FIREWISE, led by the ARQUIMEA Research Centre, takes a different approach by moving AI capabilities closer to where satellite observations are collected. The project is developing a framework for adapting and operating Earth observation foundation models onboard satellites.
This is intended to reduce delays associated with transmitting imagery to the ground and processing it before an alert can be issued. FIREWISE will also provide uncertainty information alongside wildfire alerts to support confidence in the results.
Several of the projects are focused on improving how wildfire risk is assessed before fires occur.
EO4PYRO, led by COTESA alongside Hisdesat, the University of Alicante, and IMIB-CSIC of the University of Oviedo, will integrate multiple Earth observation sources, AI, enhanced-resolution products and digital-twin capabilities within a cloud platform.
The system is intended to support vegetation monitoring, risk assessment, fire-behaviour analysis and evaluation of environmental impacts following a wildfire.
Meanwhile, FirEOcast, led by isardSAT with the University of Alcalá and MeteoGRID, is addressing limitations in conventional fire-danger indices.
The initiative will combine satellite-derived information on fuels with meteorological modelling to produce more detailed information on wildfire danger.
The aim is to provide more dynamic information that can support prevention, preparedness and operational planning.
FireTwin, developed by Agresta Sociedad Cooperativa, will also focus on forecasting. It will combine multi-sensor Earth observation and meteorological data with AI-enhanced models to produce regularly updated wildfire-risk information.
The project will also develop short-term forecasting capabilities intended to help identify critical areas, support preventive action and improve resource allocation.
Other projects are concentrating on the challenge of monitoring Spanish wildfires as they develop.
Thales Alenia Space España is extending its Deeper Vision Self-Trained AI (DVSTAI) cloud service through the Thermal Infrared extension.
The project will add multispectral and thermal-infrared capabilities, alongside semantic-segmentation models, scheduled monitoring, risk alerts and potential-impact mapping.
The extension is designed to turn recent satellite observations into detailed information about wildfire risk and potential impacts at local and regional levels.
PiroSAR, developed by Telespazio Ibérica, addresses another major obstacle: the difficulty of observing active fires when smoke, cloud, darkness or operational restrictions affect conventional systems.
The project will use imagery from multiple Synthetic Aperture Radar (SAR) satellite constellations to provide information on active fire fronts, perimeter changes and fire evolution in different conditions. This is intended to support tactical decision-making by emergency management authorities.
The eighth initiative, Horizon Wildfire Insights (HWI), is being led by Airbus Secure Communications, Airbus GeoTech, Vexiza, and B2Space.
HWI focuses on the fragmented nature of wildfire information, where satellite observations, aerial data, field reports and operational communications may not provide emergency teams with a single, timely picture.
The project will integrate Earth observation data, critical communications and analytical capabilities into one environment. Its applications will span risk anticipation, active-fire monitoring, coordinated decision-making and assessment of affected areas.
Together, the eight projects represent a €3m investment in Earth observation applications intended to strengthen wildfire management in Spain.
By combining satellite data with AI, modelling and other information sources, the initiatives aim to give authorities better tools for anticipating risks, detecting fires and supporting decisions during and after wildfire events.
