Daily Global Methane Super‐Emitter Detection and Source Identification With Sub‐Daily Tracking
Sign Up to like & getrecommendations! Published in 2025 at "Geophysical Research Letters"
DOI: 10.1029/2024gl111824
Abstract: We use the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instruments to retrieve atmospheric methane enhancements with 750 m resolution. We show that the three VIIRS instruments in orbit uniquely enhance tracking of methane super‐emission… read more here.
Keywords: detection; global methane; methane super; daily global ... See more keywords
A data-efficient deep transfer learning framework for methane super-emitter detection in oil and gas fields using the Sentinel-2 satellite
Sign Up to like & getrecommendations! Published in 2025 at "Atmospheric Chemistry and Physics"
DOI: 10.5194/acp-25-4035-2025
Abstract: Abstract. Efficiently detecting large methane point sources (super-emitters) in oil and gas fields is crucial for informing stakeholder decisions about mitigation actions. Satellite measurements by multispectral instruments, such as Sentinel-2, offer global and frequent coverage.… read more here.
Keywords: detection; transfer learning; methane super; methane ... See more keywords
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
Sign Up to like & getrecommendations! Published in 2024 at "Atmospheric Measurement Techniques"
DOI: 10.5194/amt-17-2583-2024
Abstract: Abstract. We present a deep learning model, CH4Net, for automated monitoring of methane super-emitters from Sentinel-2 data. When trained on images of 23 methane super-emitter locations from 2017–2020 and evaluated on images from 2021, this… read more here.
Keywords: deep learning; methane super; monitoring methane; ch4net ... See more keywords