The Fire Detection Capabilities of Meteosat Third Generation: A Comparison with Meteosat Second Generation Using Early Operational Data

V. Pampanoni,G. Laneve,Simone Saquella,Alvise Ferrari

Published 2025 in IEEE International Geoscience and Remote Sensing Symposium

ABSTRACT

This study performs a preliminary investigation of the capabilities of the Meteosat Third Generation (MTG) Flexible Combined Imager (FCI) for the detection of thermal anomalies, with a particular focus on the increase in performance compared to its predecessor Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). For this purpose, we used an updated version of the Satellite Fire Detection (SFIDE) algorithm to detect hotspots from FCI and SEVIRI imagery, while using thermal anomalies obtained from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) in Italy as a ground truth. Despite the limitations related to using non-concurrent acquisitions of another satellite as a ground truth and the limited spatial and temporal extension of this preliminary analysis, the results show a significant leap forward in terms of detection sensibility offered by MTG with respect to MSG: while MSG matched only 7% of the thermal anomalies in the MODIS database, MTG matched 34%. This finding highlights the potential of MTG-FCI for operational detection and monitoring of wildfires, volcanic activity, industrial emissions and other applications requiring accurate and timely information on surface temperature variations. Despite the promising results, a validation conducted on a hand-curated thermal anomaly dataset is needed to perform a proper classification accuracy assessment of MTG.

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