Methane Plume Detection with U-Net Segmentation on Sentinel-2 Image Data

Dec 15, 2023



Methane emissions have a significant impact on increasing global warming. Satellite-based methane detection methods can help mitigate methane emissions, as they provide a constant and global detection. The Sentinel-2 constellation, in particular, offers frequent and publicly accessible images on a global scale. We propose a deep learning approach to detect methane plumes from Sentinel-2 images. We construct a dataset of 5200 satellite images with identified methane plumes, on which we train a U-Net model. Preliminary results demonstrate that the model is able to correctly identify methane plumes on training data, although generalization to new methane plumes remains challenging. All code, data, and models are made available online.


Store presentation

Should this presentation be stored for 1000 years?

How do we store presentations

Total of 0 viewers voted for saving the presentation to eternal vault which is 0.0%


Recommended Videos

Presentations on similar topic, category or speaker

Interested in talks like this? Follow NeurIPS 2023