On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System

Moreno Párrizas, Hugo and Valero Ubierna, Constantino and Bengochea-Guevara, José María and Ribeiro Seijas, Ángela and Garrido Izard, Miguel and Andújar Sánchez, Dionisio (2020). On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System. "Sensors", v. 20 (n. 4); p. 1102. ISSN 1424-8220. https://doi.org/10.3390/s20041102.

Description

Title: On-Ground Vineyard Reconstruction Using a LiDAR-Based Automated System
Author/s:
  • Moreno Párrizas, Hugo
  • Valero Ubierna, Constantino
  • Bengochea-Guevara, José María
  • Ribeiro Seijas, Ángela
  • Garrido Izard, Miguel
  • Andújar Sánchez, Dionisio
Item Type: Article
Título de Revista/Publicación: Sensors
Date: February 2020
ISSN: 1424-8220
Volume: 20
Subjects:
Freetext Keywords: laser measurements; plant volume estimation; vineyard proximal sensing; vineshoot volume
Faculty: E.T.S. de Ingeniería Agronómica, Alimentaria y de Biosistemas (UPM)
Department: Ingeniería Agroforestal
UPM's Research Group: Técnicas Avanzadas en Agroalimentación LPF-TAGRALIA
Creative Commons Licenses: None

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Abstract

Crop 3D modeling allows site-specific management at different crop stages. In recent years, light detection and ranging (LiDAR) sensors have been widely used for gathering information about plant architecture to extract biophysical parameters for decision-making programs. The study reconstructed vineyard crops using light detection and ranging (LiDAR) technology. Its accuracy and performance were assessed for vineyard crop characterization using distance measurements, aiming to obtain a 3D reconstruction. A LiDAR sensor was installed on-board a mobile platform equipped with an RTK-GNSS receiver for crop 2D scanning. The LiDAR system consisted of a 2D time-of-flight sensor, a gimbal connecting the device to the structure, and an RTK-GPS to record the sensor data position. The LiDAR sensor was facing downwards installed on-board an electric platform. It scans in planes perpendicular to the travel direction. Measurements of distance between the LiDAR and the vineyards had a high spatial resolution, providing high-density 3D point clouds. The 3D point cloud was obtained containing all the points where the laser beam impacted. The fusion of LiDAR impacts and the positions of each associated to the RTK-GPS allowed the creation of the 3D structure. Although point clouds were already filtered, discarding points out of the study area, the branch volume cannot be directly calculated, since it turns into a 3D solid cluster that encloses a volume. To obtain the 3D object surface, and therefore to be able to calculate the volume enclosed by this surface, a suitable alpha shape was generated as an outline that envelops the outer points of the point cloud. The 3D scenes were obtained during the winter season when only branches were present and defoliated. The models were used to extract information related to height and branch volume. These models might be used for automatic pruning or relating this parameter to evaluate the future yield at each location. The 3D map was correlated with ground truth, which was manually determined, pruning the remaining weight. The number of scans by LiDAR influenced the relationship with the actual biomass measurements and had a significant effect on the treatments. A positive linear fit was obtained for the comparison between actual dry biomass and LiDAR volume. The influence of individual treatments was of low significance. The results showed strong correlations with actual values of biomass and volume with R2 = 0.75, and when comparing LiDAR scans with weight, the R2 rose up to 0.85. The obtained values show that this LiDAR technique is also valid for branch reconstruction with great advantages over other types of non-contact ranging sensors, regarding a high sampling resolution and high sampling rates. Even narrow branches were properly detected, which demonstrates the accuracy of the system working on difficult scenarios such as defoliated crops

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainAGL2017-83325-C4-3-RUnspecifiedCSICDISEÑO, DESARROLLO Y EVALUACION DE SISTEMAS AUTONOMOS PARA LA INSPECCION TERRESTRE EFECTIVA Y LA ACTUACION PRECISA EN CULTIVOS EXTENSIVOS Y LEÑOSOS

More information

Item ID: 66813
DC Identifier: https://oa.upm.es/66813/
OAI Identifier: oai:oa.upm.es:66813
DOI: 10.3390/s20041102
Official URL: https://doi.org/10.3390/s20041102
Deposited by: Profesor Constantino Valero Ubierna
Deposited on: 21 Apr 2021 13:04
Last Modified: 21 Apr 2021 13:37
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