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Sentinel Satellites Map Methane Super-Emitters

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The new algorithm automatically calculates the associated emissions based on measured concentrations and concurrent wind speeds.

Methane plumes detected by the Copernicus Sentinel-5P satellite in 2021.

Credit: SRON Netherlands Institute for Space Research

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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