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ForestFireAI: Large-scale Prediction of Forest Fire Drivers from Space Using Multi-source Remote Sensing Data and Artificial Intelligence Techniques

CORDIS · observation · Publication date unknown

ForestFireAI: Large-scale Prediction of Forest Fire Drivers from Space Using Multi-source Remote Sensing Data and Artificial Intelligence Techniques With the increasing frequency and intensity of forest fires, it is essential to better understand the drivers causing them. Identifying forest fire drivers offer valuable insights that can enhance our comprehension of forest fire variability and guide targeted regional risk management strategies. Recent advancements in satellite remote sensing and machine learning data processing techniques have significantly improved fire monitoring. However, while these efforts have resulted in accurate fire maps, they do not provide information about the underlying causes. Consequently, the full potential of Earth Observation data, along with advanced data processing and modelling techniques for studying the forest fire drivers, remains largely unexplored. The ForestFireAI project aims to leverage the availability of multi-source and multi-temporal Earth Observation

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recordType

award

status

SIGNED

region

EU

value

260347.92

unit

EUR