Master dissertation: deep learning analysis for volcanic plume detection using sentinel-5p data
Satellite data offers an alternative, exemplified by the European Space Agency’s Sentinel-5P satellite, which can measure atmospheric SO2 with unprecedented spa- tial resolution. Traditional methods for plume identification are labor-intensive and often impractical for global monitoring. This paper aims to tackle these challenges by developing an automated, transfer learning-based approach for global volcanic activity detection and plume identification.