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.
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.
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.
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.
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.