Monitoring methane point sources with multispectral Sentinel-2 satellite observations

We demonstrate the previously undocumented capability of the Sentinel-2 twin satellites (and Landsat) to detect and quantify anomalous methane point sources. See our paper in AMT for the details.

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Estimating methane emissions from individual coal mine vents using GHGSat-D satellite observations

We estimated time-averaged methane emissions from underground coal mines in the United States, China, and Australia by aggregating GHGSat-D observations in time. Check out our 2020 ES&T paper for the full story.

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Monitoring anomalous methane point sources in oil/gas fields with satellites

We quantified massive methane point sources in an oil/gas field using the GHGSat-D and TROPOMI satellite instruments. This was a collaboration between Harvard, GHGSat, and the SRON Netherlands Institute for Space Research. Read more about it in our 2019 GRL paper.

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Deep learning for detecting methane plumes in noisy satellite imagery

We’re training convolutional neural networks to localize methane plumes in noisy GHGSat satellite observations.

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Source rate retrieval algorithms for quantifying methane point sources from space

We developed algorithms for retrieving emission rates from fine-resolution satellite observations of atmospheric methane plumes. You can read more about them in our 2018 AMT paper.

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Previous projects

Star forming galaxies in a merging galaxy supercluster
Temperature variability and climate