Evaluation of UAV and Sentinel 2 images to estimate condition of hop (Humulus lupulus L.) plants
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F14864347%3A_____%2F21%3AN0000020" target="_blank" >RIV/14864347:_____/21:N0000020 - isvavai.cz</a>
Alternative codes found
RIV/60460709:41210/21:89862 RIV/60460709:41310/21:89862
Result on the web
<a href="https://www.actahort.org/books/1328/1328_13.htm" target="_blank" >https://www.actahort.org/books/1328/1328_13.htm</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.17660/ActaHortic.2021.1328.13" target="_blank" >10.17660/ActaHortic.2021.1328.13</a>
Alternative languages
Result language
angličtina
Original language name
Evaluation of UAV and Sentinel 2 images to estimate condition of hop (Humulus lupulus L.) plants
Original language description
Hop garden structure and crop condition can be monitored by many in situ methods but remote sensing offers possibilities of non-destructive monitoring. An organic hop garden with the cultivars ‘Žatecký červeňák’ and ‘Premiant’, and a conventional hop garden with the cultivars ‘Agnus’, ‘Premiant’ and ‘Sládek’ were selected for the experiment. In this study, unmanned aerial vehicle (UAV, eBee X senseFly UAV) equipped with Red Green Blue (RGB), Sensor Optimized for Drone Application (S.O.D.A.), and Sequoia cameras as well as Sentinel 2 satellite images were used for monitoring of hop plants throughout the whole vegetation season. UAV images were pre-processed in Pix4Dmapper software and orthophoto mosaics were derived. RGB vegetation indices and normalized difference vegetation index (NDVI) were calculated for each cultivar from UAV and satellite images. Resulted binary model of portion with green leaves and soil was extracted on the base of threshold value and served for detection of plants area. NDVI spectral index was calculated in order to describe plant condition during the growing season. The results showed significant differences in NDVI values among the conventional and organic hop gardens and among the cultivars as well and showed applicability of UAV and satellite images. Green area of the plants derived from the UAV images was influenced by design and flight parameters of this unmanned aerial system and crop structure.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
40101 - Agriculture
Result continuities
Project
<a href="/en/project/QK1910170" target="_blank" >QK1910170: Ensuring the long-term competitiveness of czech hop production through the basic implementation of the principles of precision agriculture and Smart Farming technologies</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Acta Horticulturae 1328
ISBN
978-94-62613-25-6
ISSN
0567-7572
e-ISSN
2406-6168
Number of pages
8
Pages from-to
95-102
Publisher name
International Society for Horticultural Science
Place of publication
Leuven
Event location
Stuttgart
Event date
Mar 8, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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