Publikationen in Zusammenarbeit mit Forschern von Instituto Tecnológico Agrario de Castilla y León (19)

2024

  1. Digital ampelography: deep learning (CNN) using Keras to identify grapevine cultivars

    Acta Horticulturae, pp. 311-320

  2. Efectos del nivel de rendimiento en las características de la uva y del vino en la variedad tempranillo

    Tierras: Agricultura, Núm. 329, pp. 76-85

  3. Effects of vineyard production level on 'Tempranillo' grape and wine characteristics

    Acta Horticulturae, pp. 15-22

  4. Evaluación de índices espectrales obtenidos mediante UAV sobre variedades minoritarias de vid

    Tierras: Agricultura, Núm. 330, pp. 70-74

  5. Field-Deployed Spectroscopy from 350 to 2500 nm: A Promising Technique for Early Identification of Powdery Mildew Disease (Erysiphe necator) in Vineyards

    Agronomy, Vol. 14, Núm. 3

  6. Relationship between vegetation indices calculated from Sentinel-2 imagery and vineyard ground-truth data

    Acta Horticulturae, pp. 301-310

  7. Thermoregulation capability of the leaf canopy according to canopy area and grapevine cultivar

    Acta Horticulturae, pp. 81-88

2023

  1. Remote Sensing for Sustainable Pistachio Cultivation and Improved Quality Traits Evaluation through Thermal and Non-Thermal UAV Vegetation Indices

    Applied Sciences (Switzerland), Vol. 13, Núm. 13

2022

  1. A Novel Technique Using Planar Area and Ground Shadows Calculated from UAV RGB Imagery to Estimate Pistachio Tree (Pistacia vera L.) Canopy Volume

    Remote Sensing, Vol. 14, Núm. 23

  2. Estimación del dosel foliar para una gestión diferenciada del viñedo a nivel de planta

    Vida rural, Núm. 518, pp. 14-16

  3. High-Resolution UAV RGB Imagery Dataset for Precision Agriculture and 3D Photogrammetric Reconstruction Captured over a Pistachio Orchard (Pistacia vera L.) in Spain

    Data, Vol. 7, Núm. 11

  4. Potential of functional analysis applied to Sentinel-2 time-series to assess relevant agronomic parameters at the within-field level in viticulture

    Computers and Electronics in Agriculture, Vol. 194

  5. UAV RGB imagery dataset captured at nadir and oblique angles over pistachio trees in Spain, including images, GCPs, 3D point cloud and orthomosaic.

    Zenodo

  6. UAV RGB imagery dataset captured at nadir and oblique angles over pistachio trees in Spain, including images, GCPs, 3D point cloud and orthomosaic.

    Zenodo

  7. UAV RGB imagery dataset captured at nadir and oblique angles over pistachio trees in Spain, including images, GCPs, 3D point cloud and orthomosaic.

    Zenodo

2021

  1. Estimation of leaf area index in vineyards by analysing projected shadows using uav imagery

    Oeno One, Vol. 55, Núm. 4, pp. 159-180

2020

  1. Effect of missing vines on total leaf area determined by NDVI calculated from sentinel satellite data: Progressive vine removal experiments

    Applied Sciences (Switzerland), Vol. 10, Núm. 10

  2. Sentinel-2 satellite imagery for agronomic and quality variability assessment of pistachio (Pistacia vera l.)

    Sustainability (Switzerland), Vol. 12, Núm. 20, pp. 1-12

2019

  1. Agronomic classification between vineyards ('Verdejo') using NDVI and Sentinel-2 and evaluation of their wines

    Vitis - Journal of Grapevine Research, Vol. 58, pp. 33-38