U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers
Abstract × O ps = Q/(U W Δ B), as a single dimensionless number to predict plume detectability and source rate quantification error from an instrument as a function of source rate Q U W Δ B. We show that O ps kg h - 1 in GHGSat-C1 images over surfaces with low background noise and successfully handles larger point sources over surfaces with substantial background noise. We find that the IME method for source quantification is unbiased over the full range of source rates, while the CNN method is biased towards the mean of its training range. The total error in source rate quantification is dominated by wind speed at low wind speeds and by the masking algorithm at high wind speeds. A wind speed of 2–4 m s - 1 is optimal for detection and quantification of point sources from satellite data.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers ; volume:17 ; number:9 ; year:2024 ; pages:2625-2636 ; extent:12
Atmospheric measurement techniques ; 17, Heft 9 (2024), 2625-2636 (gesamt 12)
- Urheber
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Bruno, Jack H.
Jervis, Dylan
Varon, Daniel J.
Jacob, Daniel J.
- DOI
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10.5194/amt-17-2625-2024
- URN
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urn:nbn:de:101:1-2405090430317.615140814957
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 11:02 MESZ
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Beteiligte
- Bruno, Jack H.
- Jervis, Dylan
- Varon, Daniel J.
- Jacob, Daniel J.
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