CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
<p>We present a deep learning model, CH4Net, for automated monitoring of methane super-emitters from Sentinel-2 data. When trained on images of 23 methane super-emitter locations from 2017–2020 and evaluated on images from 2021, this model detects 84 % of methane plumes compared with 24 % of p...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2024-05-01
|
| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/17/2583/2024/amt-17-2583-2024.pdf |