ArticleSensors (Basel, Switzerland)2024
Comparative Analysis of TLS and UAV Sensors for Estimation of Grapevine Geometric Parameters.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Dataset of RGB images of healthy grapevine leaves and with downy mildew, powdery mildew, Esca complex, and erineum mite symptoms.Data in brief · 2026Article
- TLS-grapevine2024: A terrestrial laser scanner point cloud dataset of grapevines at different phenological stages.Data in brief · 2026Article
- Secure and Intelligent Low-Altitude Infrastructures: Synergistic Integration of IoT Networks, AI Decision-Making and Blockchain Trust Mechanisms.Sensors (Basel, Switzerland) · 2025Review
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Authors and funding
6 authors.
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Abstract
Understanding geometric and biophysical characteristics is essential for determining grapevine vigor and improving input management and automation in viticulture. This study compares point cloud data obtained from a Terrestrial Laser Scanner (TLS) and various UAV sensors including multispectral, panchromatic, Thermal Infrared (TIR), RGB, and LiDAR data, to estimate geometric parameters of grapevines. Descriptive statistics, linear correlations, significance using the F-test of overall significance, and box plots were used for analysis. The results indicate that 3D point clouds from these sensors can accurately estimate maximum grapevine height, projected area, and volume, though with varying degrees of accuracy. The TLS data showed the highest correlation with grapevine height (
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Registered trials
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