13 citations as recorded by crossref.

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3. Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data H. Wang et al. 10.3390/rs16061023
4. Geostationary satellite observations of extreme and transient methane emissions from oil and gas infrastructure M. Watine-Guiu et al. 10.1073/pnas.2310797120
5. Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers A. Ayasse et al. 10.5194/amt-16-6065-2023
6. Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al. 10.5194/acp-23-9071-2023
7. Detection, localization, and quantification of single-source methane emissions on oil and gas production sites using point-in-space continuous monitoring systems W. Daniels et al. 10.1525/elementa.2023.00110
8. S2MetNet: A novel dataset and deep learning benchmark for methane point source quantification using Sentinel-2 satellite imagery A. Radman et al. 10.1016/j.rse.2023.113708
9. Assessing the Relative Importance of Satellite-Detected Methane Superemitters in Quantifying Total Emissions for Oil and Gas Production Areas in Algeria S. Naus et al. 10.1021/acs.est.3c04746
10. Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
11. Daily detection and quantification of methane leaks using Sentinel-3: a tiered satellite observation approach with Sentinel-2 and Sentinel-5p S. Pandey et al. 10.1016/j.rse.2023.113716
12. Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Sentinel-2 Imagery T. Ehret et al. 10.1021/acs.est.1c08575
13. Semantic segmentation of methane plumes with hyperspectral machine learning models V. Růžička et al. 10.1038/s41598-023-44918-6