TLS-grapevine2024: A terrestrial laser scanner point cloud dataset of grapevines at different phenological stages

Grapevines (<i>Vitis vinifera</i> L.) undergo structural and physiological changes throughout the growing season, progressing through distinct phenological stages that require regular monitoring. This dataset consists of high-resolution point cloud data acquired with a stationary terrestrial laser scanner (TLS) to document grapevine development from early leaf development to dormancy. Georeferenced point clouds were generated from 15 TLS scans along two vineyard rows at nine phenological stages. The dataset also includes multispectral and RGB photogrammetric point clouds and orthorectified raster products from an unmanned aerial vehicle survey conducted before harvest. Ground-truth measurements leaf area index, grape production, and pruning wood biomass were collected for each monitored grapevine. As a result, the dataset provides multi-temporal TLS observations that support grapevine structural analysis and development, phenological monitoring, and can be used for the development of AI-based models for precision viticulture.

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Publication Details

Journal
Data in Brief
Published
2026-02-24
DOI
https://doi.org/10.1016/j.dib.2026.112614
Primary Topic
Horticultural and Viticultural Research
Type
article
Field-Weighted Citation Impact
0.00

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article

TLS-grapevine2024: A terrestrial laser scanner point cloud dataset of grapevines at different phenological stages

Fernando Portela, Raúl Martínez Morais, Luís Pádua, J. M. Sousa et al.
Data in Brief
Horticultural and Viticultural Research
article

TLS-grapevine2024: A terrestrial laser scanner point cloud dataset of grapevines at different phenological stages

Fernando Portela, Raúl Martínez Morais, Luís Pádua, J. M. Sousa, Leilson Ferreira, Emanuel Peres, Pedro Marques
article en

Abstract

Grapevines (<i>Vitis vinifera</i> L.) undergo structural and physiological changes throughout the growing season, progressing through distinct phenological stages that require regular monitoring. This dataset consists of high-resolution point cloud data acquired with a stationary terrestrial laser scanner (TLS) to document grapevine development from early leaf development to dormancy. Georeferenced point clouds were generated from 15 TLS scans along two vineyard rows at nine phenological stages. The dataset also includes multispectral and RGB photogrammetric point clouds and orthorectified raster products from an unmanned aerial vehicle survey conducted before harvest. Ground-truth measurements leaf area index, grape production, and pruning wood biomass were collected for each monitored grapevine. As a result, the dataset provides multi-temporal TLS observations that support grapevine structural analysis and development, phenological monitoring, and can be used for the development of AI-based models for precision viticulture.

Data in BriefVol. 65
University of Trás-os-Montes and Alto Douro (PT), Universidade Politécnica de Viana do Castelo (PT), INESC TEC (PT)
Directorate for Biological Sciences, Fundação para a Ciência e a Tecnologia, European Regional Development Fund
Openalex Percentile: Top 46%
Horticultural and Viticultural Research
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