IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v11y2021i3p208-d510273.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/11/3/208/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/11/3/208/
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Artur Kraszkiewicz & Artur Przywara & Alexandros Sotirios Anifantis, 2020. "Impact of Ignition Technique on Pollutants Emission during the Combustion of Selected Solid Biofuels," Energies, MDPI, vol. 13(10), pages 1-13, May.
    2. Gabriel G. R. de Castro & Guido S. Berger & Alvaro Cantieri & Marco Teixeira & José Lima & Ana I. Pereira & Milena F. Pinto, 2023. "Adaptive Path Planning for Fusing Rapidly Exploring Random Trees and Deep Reinforcement Learning in an Agriculture Dynamic Environment UAVs," Agriculture, MDPI, vol. 13(2), pages 1-25, January.
    3. Artur Przywara & Francesco Santoro & Artur Kraszkiewicz & Anna Pecyna & Simone Pascuzzi, 2020. "Experimental Study of Disc Fertilizer Spreader Performance," Agriculture, MDPI, vol. 10(10), pages 1-11, October.
    4. Simone Pascuzzi & Alexandros Sotirios Anifantis & Francesco Santoro, 2020. "The Concept of a Compact Profile Agricultural Tractor Suitable for Use on Specialised Tree Crops," Agriculture, MDPI, vol. 10(4), pages 1-10, April.
    5. Riccardo Lo Bianco & Primo Proietti & Luca Regni & Tiziano Caruso, 2021. "Planting Systems for Modern Olive Growing: Strengths and Weaknesses," Agriculture, MDPI, vol. 11(6), pages 1-18, May.
    6. Volodymyr Bulgakov & Simone Pascuzzi & Semjons Ivanovs & Francesco Santoro & Alexandros Sotirios Anifantis & Ievhen Ihnatiev, 2020. "Performance Assessment of Front-Mounted Beet Topper Machine for Biomass Harvesting," Energies, MDPI, vol. 13(14), pages 1-12, July.
    7. Simone Pascuzzi & Volodymyr Bulgakov & Francesco Santoro & Alexandros Sotirios Anifantis & Semjons Ivanovs & Ivan Holovach, 2020. "A Study on the Drift of Spray Droplets Dipped in Airflows with Different Directions," Sustainability, MDPI, vol. 12(11), pages 1-15, June.
    8. Yawei Wang & Yifei Chen & Xiangnan Zhang & Wenwen Gong, 2021. "Research on Measurement Method of Leaf Length and Width Based on Point Cloud," Agriculture, MDPI, vol. 11(1), pages 1-13, January.
    9. Salvatore Camposeo & Gaetano Alessandro Vivaldi & Giovanni Russo & Francesca Maria Melucci, 2022. "Intensification in Olive Growing Reduces Global Warming Potential under Both Integrated and Organic Farming," Sustainability, MDPI, vol. 14(11), pages 1-19, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:11:y:2021:i:3:p:208-:d:510273. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.