Deep learning for detecting methane plumes in noisy satellite imagery
I’m training convolutional neural networks to localize methane plumes in noisy GHGSat satellite observations.
Estimating methane emissions from coal mine vents using GHGSat-D satellite observations
I’m estimating methane emissions from underground coal mines in the United States, China, and Australia by aggregating GHGSat-D observations in time. Check out my 2018 AGU poster for details and these Bloomberg and Scientific American articles for the big picture.
Source rate retrieval algorithms for quantifying methane point sources from space
I developed algorithms for retrieving emission rates from fine-resolution satellite observations of atmospheric methane plumes. You can read more about them in my 2018 AMT paper.