ESA ASIMOV Project Active Fire Dataset

The ESA funded ASIMOV project is focused on designing, developing, and evaluating trustworthy Artificial Intelligence (AI) architectures for generating downscaled Essential Climate Variables (ECVs), with a specific emphasis on Active Fire detection using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellites. To support this goal, data from multiple sources have been compiled to create a comprehensive dataset for training deep learning-based super-resolution (SR) models aimed at enhancing wildfire detection and monitoring capabilities with SEVIRI observations. The dataset comprises 12 SEVIRI spectral bands paired with MODIS Active Fire product data, collected during fire events reported by the Greek Fire Brigade between 2014 and 2023. Additionally, topographic features such as elevation, slope, and topographic position index—derived from the GTOPO30 Digital Elevation Model—are included for each recorded fire event.