| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Keine Angabe |
| Titel: | Identifying physiological differences in highly fragmented vineyards using NIR/RGB UAV photography |
| Autor/-in: | Fahrentrapp, Johannes Häfele, Martin Schumacher, Peter Gomez, Cristina Green, David R. |
| Tagungsband: | 19th GiESCO International Meeting Proceedings |
| Band(Heft): | 2 |
| Seite(n): | 660 |
| Seiten bis: | 663 |
| Angaben zur Konferenz: | 19th International Meeting GiESCO, Gruissan, France, 31 May - 5 June 2015 |
| Erscheinungsdatum: | 2015 |
| Sprache: | Englisch |
| Schlagwörter: | Weinbau |
| Fachgebiet (DDC): | 634: Obstanlagen, Früchte und Forstwirtschaft |
| Zusammenfassung: | Remote sensing has been widely used for some time in precision agriculture as well as in viticulture, in many parts of the world, including Europe. However, where small fragmented plots are used to cultivate grapevines, as commonly found in Switzerland and the UK, traditional remote sensing has not been used very often because of the scale problem. Low-cost and easy to use UAVs are now able to carry small high resolution cameras. Thus, there is now considerable scope to explore the application of remote sensing and digital image processing tools and techniques to acquire aerial imagery and data of a vineyard, particularly for vineyards that are not easily accessible, to determine correlations with grape physiology status, pest and pathogen attacks. This paper will examine some of the developments in the application of UAVs for remote sensing of vineyards, with a focus on small fragmented viticultural practices. Preliminary results from a project concerning the correlation of different physiological measures such as photosynthesis and wood weight with NIR/RGB imagery and data will be used to illustrate. |
| Weitere Angaben: | Group of international Experts of vitivinicultural Systems for CoOperation (GiESCO) |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/4091 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | Life Sciences und Facility Management |
| Organisationseinheit: | Institut für Umwelt und Natürliche Ressourcen (IUNR) |
| Publiziert im Rahmen des ZHAW-Projekts: | Multispektrale Bildgebung: Der Schlüssel zur Früherkennung von Blattkrankheiten |
| Enthalten in den Sammlungen: | Publikationen Life Sciences und Facility Management |
Dateien zu dieser Ressource:
Es gibt keine Dateien zu dieser Ressource.
Zur Langanzeige
Fahrentrapp, J., Häfele, M., Schumacher, P., Gomez, C., & Green, D. R. (2015). Identifying physiological differences in highly fragmented vineyards using NIR/RGB UAV photography [Conference paper]. 19th GiESCO International Meeting Proceedings, 2, 660–663.
Fahrentrapp, J. et al. (2015) ‘Identifying physiological differences in highly fragmented vineyards using NIR/RGB UAV photography’, in 19th GiESCO International Meeting Proceedings, pp. 660–663.
J. Fahrentrapp, M. Häfele, P. Schumacher, C. Gomez, and D. R. Green, “Identifying physiological differences in highly fragmented vineyards using NIR/RGB UAV photography,” in 19th GiESCO International Meeting Proceedings, 2015, vol. 2, pp. 660–663.
FAHRENTRAPP, Johannes, Martin HÄFELE, Peter SCHUMACHER, Cristina GOMEZ und David R. GREEN, 2015. Identifying physiological differences in highly fragmented vineyards using NIR/RGB UAV photography. In: 19th GiESCO International Meeting Proceedings. Conference paper. 2015. S. 660–663
Fahrentrapp, Johannes, Martin Häfele, Peter Schumacher, Cristina Gomez, and David R. Green. 2015. “Identifying Physiological Differences in Highly Fragmented Vineyards Using NIR/RGB UAV Photography.” Conference paper. In 19th GiESCO International Meeting Proceedings, 2:660–63.
Fahrentrapp, Johannes, et al. “Identifying Physiological Differences in Highly Fragmented Vineyards Using NIR/RGB UAV Photography.” 19th GiESCO International Meeting Proceedings, vol. 2, 2015, pp. 660–63.
Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt, soweit nicht anderweitig angezeigt.