Vine canopy reconstruction and assessment with terrestrial lidar and aerial imaging

Petrović, Igor (author), Sečnik, Matej (author), Hočevar, Marko (author), Berk, Peter (author)

For successful dosing of plant protection products, the characteristics of the vine canopies should be known, based on which the spray amount should be dosed. In the field experiment, we compared two optical experimental methods, terrestrial lidar and aerial photogrammetry, with manual defoliation of some selected vines. Like those of other authors, our results show that both terrestrial lidar and aerial photogrammetry were able to represent the canopy well with correlation coefficients around 0.9 between the measured variables and the number of leaves. We found that in the case of aerial photogrammetry, significantly more points were found in the point cloud, but this depended on the choice of the ground sampling distance. Our results show that in the case of aerial UAS photogrammetry, subdividing the vine canopy segments to 5 × 5 cm gives the best representation of the volume of vine canopies.

• Language: English
• Keywords: precision agriculture, remote sensing, 3D point clouds, vineyard, canopy reconstruction, terrestrial lidar, aerial photogrammetry, manual defoliation
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FS - Faculty of Mechanical Engineering
• Publication status: Published
• Publication version: Version of Record
• Year: 2022
• Number of pages: 23 str.
• Numbering: Vol. 14, iss. 12, art. 5894
• PID: 20.500.12556/RUL-154137
• UDC: 634.8:632.9:528.8:004.9
• ISSN on article: 2072-4292
• DOI: 10.3390/rs14225894
• COBISS.SI-ID: 132638723
• Publication date in RUL: 26.01.2024

Record is a part of a journal

• Title: Remote sensing
• Shortened title: Remote sens.
• Publisher: MDPI
• ISSN: 2072-4292
• COBISS.SI-ID: 32345133

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.