Next Article in Journal
Agronomic and Economic Potential of Vegetation Indices for Rice N Recommendations under Organic and Mineral Fertilization in Mediterranean Regions
Previous Article in Journal
Ground-Level PM2.5 Concentration Estimation from Satellite Data in the Beijing Area Using a Specific Particle Swarm Extinction Mass Conversion Algorithm
 
 
Article

Multi-Temporal Vineyard Monitoring through UAV-Based RGB Imagery

1
School of Science and Technology, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal
2
Centre for Robotics in Industry and Intelligent Systems (CRIIS), INESC Technology and Science (INESC-TEC), 4200-465 Porto, Portugal
*
Authors to whom correspondence should be addressed.
Remote Sens. 2018, 10(12), 1907; https://doi.org/10.3390/rs10121907
Received: 30 October 2018 / Revised: 26 November 2018 / Accepted: 27 November 2018 / Published: 29 November 2018
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
This study aimed to characterize vineyard vegetation thorough multi-temporal monitoring using a commercial low-cost rotary-wing unmanned aerial vehicle (UAV) equipped with a consumer-grade red/green/blue (RGB) sensor. Ground-truth data and UAV-based imagery were acquired on nine distinct dates, covering the most significant vegetative growing cycle until harvesting season, over two selected vineyard plots. The acquired UAV-based imagery underwent photogrammetric processing resulting, per flight, in an orthophoto mosaic, used for vegetation estimation. Digital elevation models were used to compute crop surface models. By filtering vegetation within a given height-range, it was possible to separate grapevine vegetation from other vegetation present in a specific vineyard plot, enabling the estimation of grapevine area and volume. The results showed high accuracy in grapevine detection (94.40%) and low error in grapevine volume estimation (root mean square error of 0.13 m and correlation coefficient of 0.78 for height estimation). The accuracy assessment showed that the proposed method based on UAV-based RGB imagery is effective and has potential to become an operational technique. The proposed method also allows the estimation of grapevine areas that can potentially benefit from canopy management operations. View Full-Text
Keywords: unmanned aerial vehicles; precision viticulture; multi-temporal analysis; crop surface models unmanned aerial vehicles; precision viticulture; multi-temporal analysis; crop surface models
Show Figures

Graphical abstract

MDPI and ACS Style

Pádua, L.; Marques, P.; Hruška, J.; Adão, T.; Peres, E.; Morais, R.; Sousa, J.J. Multi-Temporal Vineyard Monitoring through UAV-Based RGB Imagery. Remote Sens. 2018, 10, 1907. https://doi.org/10.3390/rs10121907

AMA Style

Pádua L, Marques P, Hruška J, Adão T, Peres E, Morais R, Sousa JJ. Multi-Temporal Vineyard Monitoring through UAV-Based RGB Imagery. Remote Sensing. 2018; 10(12):1907. https://doi.org/10.3390/rs10121907

Chicago/Turabian Style

Pádua, Luís, Pedro Marques, Jonáš Hruška, Telmo Adão, Emanuel Peres, Raul Morais, and Joaquim J. Sousa. 2018. "Multi-Temporal Vineyard Monitoring through UAV-Based RGB Imagery" Remote Sensing 10, no. 12: 1907. https://doi.org/10.3390/rs10121907

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop