An international team of researchers led by the SRON Netherlands Institute for Space Research has developed an algorithm that uses machine learning to automatically detect methane super-emitter plumes in data from the Copernicus Sentinel-5P, Sentinel-2, and Sentinel-3 satellites.
The Sentinel-5P's high-precision methane measurements complement the Sentinel-2's ability to pinpoint major methane leaks via multi-band sensors, while the Sentinel-3 satellites provide daily global coverage and ground pixel resolution of 500 meters (1,640 feet).
The researchers found the Sentinel-3 satellites can detect methane leaks of at least 10 tons per hour each day.
Integrating Sentinel-2 and Sentinel-3 data enables researchers to zoom in precisely to identify, measure, and track methane sources correlating with plumes detected by Sentinel-5P's global observations.
From The European Space Agency
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Abstracts Copyright © 2023 SmithBucklin, Washington, D.C., USA
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