Monitoring vineyard canopy management operations using UAV-acquired photogrammetric point clouds
Fecha
2020Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Identificador del proyecto
Impacto
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10.3390/rs12142331
Resumen
Canopy management operations, such as shoot thinning, leaf removal, and shoot trimming, are among the most relevant agricultural practices in viticulture. However, the supervision of these tasks demands a visual inspection of the whole vineyard, which is time-consuming and laborious. The application of photogrammetric techniques to images acquired with an Unmanned Aerial Vehicle (UAV) has proved ...
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Canopy management operations, such as shoot thinning, leaf removal, and shoot trimming, are among the most relevant agricultural practices in viticulture. However, the supervision of these tasks demands a visual inspection of the whole vineyard, which is time-consuming and laborious. The application of photogrammetric techniques to images acquired with an Unmanned Aerial Vehicle (UAV) has proved to be an efficient way to measure woody crops canopy. Consequently, the objective of this work was to determine whether the use ofUAV photogrammetry allows the detection of canopy management operations. A UAV equipped with an RGB digital camera was used to acquire images with high overlap over different canopy management experiments in four vineyards with the aim of characterizing vine dimensions before and after shoot thinning, leaf removal, and shoot trimming operations. The images were processed to generate photogrammetric point clouds of every vine that were analyzed using a fully automated object-based image analysis algorithm. Two approaches were tested in the analysis of the UAV derived data: (1) to determine whether the comparison of the vine dimensions before and after the treatments allowed the detection of the canopy management operations; and (2) to study the vine dimensions after the operations and assess the possibility of detecting these operations using only the data from the flight after them. The first approach successfully detected the canopy management. Regarding the second approach, significant differences in the vine dimensions after the treatments were detected in all the experiments, and the vines under the shoot trimming treatment could be easily and accurately detected based on a fixed threshold. [--]
Materias
Shoot thinning,
Leaf removal,
Shoot trimming,
Remote sensing,
Change detection,
3D mapping,
OBIA
Editor
MDPI
Publicado en
Remote Sensing, 2020, 12(14), 2331
Departamento
Universidad Pública de Navarra. Departamento de Agronomía, Biotecnología y Alimentación /
Nafarroako Unibertsitate Publikoa. Agronomia, Bioteknologia eta Elikadura Saila
Versión del editor
Entidades Financiadoras
This research was partly financed by the AGL2017-83325-C4-4-R (Spanish Ministry of Science and Innovation AEI/EU-FEDER funds), DECIVID and VINO ROSADO (funds from the Government of Navarra, grant nos. 0011-1365-2017-000113 and 0011-1365-2019-000111), and Intramural-CSIC (grant nos. 201840E002 and 202040E230) projects. Research of Dr. de Castro was supported by the Juan de la Cierva-Incorporación Program. Diana Marin is beneficiary of a postgraduate scholarships funded by the Universidad Pública de Navarra (FPI-UPNA-2016), and Oihane Oneka of a Youth Guarantee grant for R+D (Ministry of Science and Universities, 17/5/2018). The authors acknowledge the support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).