Impact Plan ML
Project Aerosol
We use machine learning techniques to detect methane plumes in satellite data. The first project focused on detection of methane plumes in TROPOMI data. We use machine learning techniques to scan through millions of methane observations to find methane plumes originating from super-emitters. When combined with targeted high-resolution observations, this allows us to pinpoint large leaks, enabling mitigation activities (see IMEO Mars). This work is described in Schuit et al, 2023, and forms the basis for our weekly plume detections that you can find at our dedicated page.
In the next step of the project, we will apply machine learning to other (high-resolution) satellite datasets.
All methane plumes detected in 2021 TROPOMI data, grouped into one of the four dominant anthropogenic source types based on bottom-up emission inventories (Schuit et. al., 2023)
Experts who worked on this project:
Berend Schuit
PhD StudentMeet our Partners
Partners-
GHGSAT
25 november 2022
Project
SPEXone for PACE
SPEXone is a compact five-angle spectropolarimeter instrument developed as a contributed payload for the NASA Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) observatory, to be launched in 2024.
25 november 2022
Project
TROPOMI
The Dutch Tropospheric Monitoring Instrument (TROPOMI) is flying onboard the Copernicus Sentinel-5p mission, launched in 2017. Every day it scans the entire globe for e.g. methane and carbon monoxide concentrations at city-scale level.
Our project contact
Get in touchWould you like to learn more about this project? Please feel free to contact on of our project experts within SRON Earth.
