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VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain
LiDAR (Light Detection and Ranging) technology's precision in data collection has gained immense traction in the field of remote sensing, particularly in Precision Agriculture using Unmanned Aerial Vehicles (UAVs). To fulfill the pressing need for public UAV LiDAR datasets in the domain of Agri...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616138/ https://www.ncbi.nlm.nih.gov/pubmed/37915834 http://dx.doi.org/10.1016/j.dib.2023.109686 |
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author | Vélez, Sergio Ariza-Sentís, Mar Valente, João |
author_facet | Vélez, Sergio Ariza-Sentís, Mar Valente, João |
author_sort | Vélez, Sergio |
collection | PubMed |
description | LiDAR (Light Detection and Ranging) technology's precision in data collection has gained immense traction in the field of remote sensing, particularly in Precision Agriculture using Unmanned Aerial Vehicles (UAVs). To fulfill the pressing need for public UAV LiDAR datasets in the domain of Agricultural Sciences, especially for woody crops such as vineyards, this study presents an extensive dataset of LiDAR data collected from vineyards in northern Spain. The DJI M300 multi-rotor platform, equipped with a DJI Zenmuse L1 LiDAR sensor, conducted UAV flights at 20, 30, and 50 meters above ground level (AGL) across two vineyards during three development stages in 2021 and 2022. This dataset is composed of ten high-density 3D LiDAR point clouds stored in .laz format with embedded RGB information in each point. It provides insights into vineyard morphology and development, thereby aiding in the optimization of vineyard management strategies. Furthermore, it serves as a valuable tool for agricultural robotics, offering comprehensive terrain information for developing efficient flight paths and navigation algorithms. Finally, it serves as a reliable “ground truth” dataset to validate satellite-derived models, facilitating the creation of highly accurate digital elevation models (DEMs) and other derived models. |
format | Online Article Text |
id | pubmed-10616138 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-106161382023-11-01 VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain Vélez, Sergio Ariza-Sentís, Mar Valente, João Data Brief Data Article LiDAR (Light Detection and Ranging) technology's precision in data collection has gained immense traction in the field of remote sensing, particularly in Precision Agriculture using Unmanned Aerial Vehicles (UAVs). To fulfill the pressing need for public UAV LiDAR datasets in the domain of Agricultural Sciences, especially for woody crops such as vineyards, this study presents an extensive dataset of LiDAR data collected from vineyards in northern Spain. The DJI M300 multi-rotor platform, equipped with a DJI Zenmuse L1 LiDAR sensor, conducted UAV flights at 20, 30, and 50 meters above ground level (AGL) across two vineyards during three development stages in 2021 and 2022. This dataset is composed of ten high-density 3D LiDAR point clouds stored in .laz format with embedded RGB information in each point. It provides insights into vineyard morphology and development, thereby aiding in the optimization of vineyard management strategies. Furthermore, it serves as a valuable tool for agricultural robotics, offering comprehensive terrain information for developing efficient flight paths and navigation algorithms. Finally, it serves as a reliable “ground truth” dataset to validate satellite-derived models, facilitating the creation of highly accurate digital elevation models (DEMs) and other derived models. Elsevier 2023-10-14 /pmc/articles/PMC10616138/ /pubmed/37915834 http://dx.doi.org/10.1016/j.dib.2023.109686 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Vélez, Sergio Ariza-Sentís, Mar Valente, João VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain |
title | VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain |
title_full | VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain |
title_fullStr | VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain |
title_full_unstemmed | VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain |
title_short | VineLiDAR: High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain |
title_sort | vinelidar: high-resolution uav-lidar vineyard dataset acquired over two years in northern spain |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616138/ https://www.ncbi.nlm.nih.gov/pubmed/37915834 http://dx.doi.org/10.1016/j.dib.2023.109686 |
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