Deep learning applied to CO2 power plant emissions quantification using simulated satellite images

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Abstract CO 2 M (Copernicus Anthropogenic Carbon Dioxide Monitoring) satellite constellation in 2026 is expected to provide high-resolution images of CO 2 XCO 2 CO 2 CO 2 M will encounter various obstacles. A challenge is the low CO 2 XCO 2 XCO 2 XCO 2 NO 2 ∼ XCO 2 NO 2 XCO 2 CO 2 emissions from satellite images.

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: Deep learning applied to CO₂ power plant emissions quantification using simulated satellite images ; volume:17 ; number:5 ; year:2024 ; pages:1995-2014 ; extent:20
Geoscientific model development ; 17, Heft 5 (2024), 1995-2014 (gesamt 20)

Creator: Dumont Le Brazidec, Joffrey
Vanderbecken, Pierre
Farchi, Alban
Broquet, Grégoire
Kuhlmann, Gerrit
Bocquet, Marc

DOI: 10.5194/gmd-17-1995-2024

URN: urn:nbn:de:101:1-2024030703161056214833

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:46 AM CEST

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Dumont Le Brazidec, Joffrey
Vanderbecken, Pierre
Farchi, Alban
Broquet, Grégoire
Kuhlmann, Gerrit
Bocquet, Marc

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Deep learning applied to CO<sub>2</sub> power plant emissions quantification using simulated satellite images

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