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Record link: 
http://hdl.handle.net/20.500.12708/58444
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Title: 
Predicting maize canopy nitrogen status using the spectral indices CCCI and SCCCI
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Citation: 
Koppensteiner, L., Fitzgerald, G., Neubauer, T., Urban, F., Kaul, H.-P., & Manschadi, A. (2018). Predicting maize canopy nitrogen status using the spectral indices CCCI and SCCCI. In H. Stützel (Ed.), From Big Data to Smart Farming (pp. 108–109). Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften / Verlag Liddy Halm. http://hdl.handle.net/20.500.12708/58444
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Publication Type: 
Inproceedings - Full-Paper Contribution
en
Authors: 
Koppensteiner, Lukas 
Fitzgerald, Glenn 
Neubauer, Thomas 
Urban, F. 
Kaul, Hans-Peter 
Manschadi, Ahmad 
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Organisational Unit: 
E194-01 - Forschungsbereich Information und Software Engineering 
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Published in: 
From Big Data to Smart Farming 
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Date (published): 
2018
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Event name: 
Jahrestagung Gesellschaft für Pflanzenbauwissenschaften 
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Event date: 
25-Sep-2018 - 27-Sep-2018
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Event place: 
Kiel, EU
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Number of Pages: 
2
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Publisher: 
Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften / Verlag Liddy Halm, Band 30
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Peer reviewed: 
No
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Research Areas: 
Information Systems Engineering: 60%
Environmental Monitoring and Climate Adaptation: 20%
außerhalb der gesamtuniversitären Forschungsschwerpunkte: 20%
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Science Branch: 
Informatik
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Appears in Collections:
Conference Paper

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