Predictions of failed satellite retrieval of air quality using machine learning
Predictions of failed satellite retrieval of air quality using machine learning
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Publisher
Katlenburg-Lindau: Copernicus GmbH
Journal title
Language
English
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Publisher
Katlenburg-Lindau: Copernicus GmbH
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Contents
The growing fleet of Earth observation (EO) satellites is capturing unprecedented quantities of information about the concentration and distribution of trace gases in the Earth's atmosphere. Depending on the instrument and algorithm, the yield of good remote soundings can be a few percent owing to interferences such as clouds, non-linearities in th...
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Full title
Predictions of failed satellite retrieval of air quality using machine learning
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_bf03a9eff703458e9826add8911427c9
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bf03a9eff703458e9826add8911427c9
Other Identifiers
ISSN
1867-8548,1867-1381
E-ISSN
1867-8548
DOI
10.5194/amt-18-1689-2025
