Articles | Volume 17, issue 9
https://doi.org/10.5194/amt-17-2625-2024
https://doi.org/10.5194/amt-17-2625-2024
Research article
 | 
06 May 2024
Research article |  | 06 May 2024

U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers

Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob

Data sets

U-Plume Training Data Jack Bruno https://doi.org/10.7910/DVN/YFRQU4

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Short summary
Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.