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Measuring Canopy Geometric Structure Using Optical Sensors Mounted on Terrestrial Vehicles: A Case Study in Vineyards

Author

Listed:
  • Daniel Queirós da Silva

    (INESC Technology and Science (INESC TEC), 4200-465 Porto, Portugal
    School of Science and Technology, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal
    Current address: Campus da FEUP, Rua Dr. Roberto Frias 400, 4200-465 Porto, Portugal.)

  • André Silva Aguiar

    (INESC Technology and Science (INESC TEC), 4200-465 Porto, Portugal
    School of Science and Technology, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal)

  • Filipe Neves dos Santos

    (INESC Technology and Science (INESC TEC), 4200-465 Porto, Portugal)

  • Armando Jorge Sousa

    (INESC Technology and Science (INESC TEC), 4200-465 Porto, Portugal
    Faculty of Engineering, University of Porto (FEUP), 4200-465 Porto, Portugal)

  • Danilo Rabino

    (Institute of Sciences and Technologies for Sustainable Energy and Mobility, National Research Council (STEMS-CNR), 10135 Turin, Italy)

  • Marcella Biddoccu

    (Institute of Sciences and Technologies for Sustainable Energy and Mobility, National Research Council (STEMS-CNR), 10135 Turin, Italy)

  • Giorgia Bagagiolo

    (Institute of Sciences and Technologies for Sustainable Energy and Mobility, National Research Council (STEMS-CNR), 10135 Turin, Italy)

  • Marco Delmastro

    (Institute of Sciences and Technologies for Sustainable Energy and Mobility, National Research Council (STEMS-CNR), 10135 Turin, Italy)

Abstract

Smart and precision agriculture concepts require that the farmer measures all relevant variables in a continuous way and processes this information in order to build better prescription maps and to predict crop yield. These maps feed machinery with variable rate technology to apply the correct amount of products in the right time and place, to improve farm profitability. One of the most relevant information to estimate the farm yield is the Leaf Area Index. Traditionally, this index can be obtained from manual measurements or from aerial imagery: the former is time consuming and the latter requires the use of drones or aerial services. This work presents an optical sensing-based hardware module that can be attached to existing autonomous or guided terrestrial vehicles. During the normal operation, the module collects periodic geo-referenced monocular images and laser data. With that data a suggested processing pipeline, based on open-source software and composed by Structure from Motion, Multi-View Stereo and point cloud registration stages, can extract Leaf Area Index and other crop-related features. Additionally, in this work, a benchmark of software tools is made. The hardware module and pipeline were validated considering real data acquired in two vineyards—Portugal and Italy. A dataset with sensory data collected by the module was made publicly available. Results demonstrated that: the system provides reliable and precise data on the surrounding environment and the pipeline is capable of computing volume and occupancy area from the acquired data.

Suggested Citation

  • Daniel Queirós da Silva & André Silva Aguiar & Filipe Neves dos Santos & Armando Jorge Sousa & Danilo Rabino & Marcella Biddoccu & Giorgia Bagagiolo & Marco Delmastro, 2021. "Measuring Canopy Geometric Structure Using Optical Sensors Mounted on Terrestrial Vehicles: A Case Study in Vineyards," Agriculture, MDPI, vol. 11(3), pages 1-19, March.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:3:p:208-:d:510273
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    References listed on IDEAS

    as
    1. Alexandros Sotirios Anifantis & Salvatore Camposeo & Gaetano Alessandro Vivaldi & Francesco Santoro & Simone Pascuzzi, 2019. "Comparison of UAV Photogrammetry and 3D Modeling Techniques with Other Currently Used Methods for Estimation of the Tree Row Volume of a Super-High-Density Olive Orchard," Agriculture, MDPI, vol. 9(11), pages 1-14, October.
    2. Jizhang Wang & Yun Zhang & Rongrong Gu, 2020. "Research Status and Prospects on Plant Canopy Structure Measurement Using Visual Sensors Based on Three-Dimensional Reconstruction," Agriculture, MDPI, vol. 10(10), pages 1-27, October.
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