Record link: 
http://hdl.handle.net/20.500.12708/228192
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Title: 
An improved machine learning approach to estimate GPP using vegetation optical depth and other microwave remote sensing observations 
en
Citation: 
Zotta, R.-M., Müller, M. C., Lazameta, R., Walther, S., Forkel, M., & Dorigo, W. (2026). An improved machine learning approach to estimate GPP using vegetation optical depth and other microwave remote sensing observations . In EGU General Assembly 2026. EGU General Assembly 2026, Wien, Austria. https://doi.org/10.5194/egusphere-egu26-7818
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Publisher DOI: 
10.5194/egusphere-egu26-7818
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Publication Type: 
Inproceedings - Abstract Book Contribution
en
Language: 
English
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Authors: 
Zotta, Ruxandra-Maria 
Müller, Moritz Clemens 
Lazameta, Raul 
Walther, Sophia 
Forkel, Matthias 
Dorigo, Wouter 
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Organisational Unit: 
E120-08 - Forschungsbereich Klima- und Umweltfernerkundung 
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Published in: 
EGU General Assembly 2026 
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Date (published): 
May-2026
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Event name: 
EGU General Assembly 2026 
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Event date: 
3-May-2026 - 8-May-2026
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Event place: 
Wien, Austria
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Number of Pages: 
2
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Keywords: 
remote sensing
en
Research Areas: 
Environmental Monitoring and Climate Adaptation: 100%
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Science Branch: 
2074 - Geodäsie, Vermessungswesen: 70%
1020 - Informatik: 15%
1054 - Physische Geographie: 15%
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Appears in Collections:
Conference Paper

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