Precision Agriculture

, Volume 18, Issue 1, pp 111–132 | Cite as

Mobile terrestrial laser scanner applications in precision fruticulture/horticulture and tools to extract information from canopy point clouds

  • Alexandre EscolàEmail author
  • José A. Martínez-Casasnovas
  • Josep Rufat
  • Jaume Arnó
  • Amadeu Arbonés
  • Francesc Sebé
  • Miquel Pascual
  • Eduard Gregorio
  • Joan R. Rosell-Polo


LiDAR sensors are widely used in many areas and, in recent years, that includes agricultural tasks. In this work, a self-developed mobile terrestrial laser scanner based on a 2D light detection and ranging (LiDAR) sensor was used to scan an intensive olive orchard, and different algorithms were developed to estimate canopy volume. Canopy volume estimations derived from LiDAR sensor readings were compared to conventional estimations used in fruticulture/horticulture research and the results prove that they are equivalent with coefficients of correlation ranging from r = 0.56 to r = 0.82 depending on the algorithms used. Additionally, tools related to analysis of point cloud data from the LiDAR-based system are proposed to extract further geometrical and structural information from tree row crop canopies to be offered to farmers and technical advisors as digital raster maps. Having high spatial resolution information on canopy geometry (i.e., height, width and volume) and on canopy structure (i.e., light penetrability, leafiness and porosity) may result in better orchard management decisions. Easily obtainable, reliable information on canopy geometry and structure may favour the development of decision support systems either for irrigation, fertilization or canopy management, as well as for variable rate application of agricultural inputs in the framework of precision fruticulture/horticulture.


LiDAR Canopy modelling Crop mapping Olive orchard Mobile terrestrial laser scanner Precision fruticulture 



The authors want to thank Ricardo Sanz, Joan Masip, Josep M. Villar and Manel Ribes-Dasi for their contributions to the different phases of the present study.


This work was funded by the Spanish Ministry of Economy and Competitiveness through the projects SAFESPRAY (AGL2010-22304-C04-03) and AgVANCE (AGL2013-48297-C2-2-R) and by the project Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria RTA2012-00059-C02-01.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Alexandre Escolà
    • 1
    Email author
  • José A. Martínez-Casasnovas
    • 2
  • Josep Rufat
    • 3
  • Jaume Arnó
    • 1
  • Amadeu Arbonés
    • 3
  • Francesc Sebé
    • 4
  • Miquel Pascual
    • 5
  • Eduard Gregorio
    • 1
  • Joan R. Rosell-Polo
    • 1
  1. 1.Research Group on AgroICT & Precision Agriculture, Department of Agricultural and Forest EngineeringUniversity of Lleida - Agrotecnio CenterLleidaSpain
  2. 2.Research Group on AgroICT & Precision Agriculture, Department of Environmental and Soil SciencesUniversity of Lleida - Agrotecnio CenterLleidaSpain
  3. 3.Efficient Water UseInstitut de Recerca i Tecnologia Agroalimentàries (IRTA)LleidaSpain
  4. 4.Department of MathematicsUniversity of LleidaLleidaSpain
  5. 5.Department of Horticulture, Botany and GardeningUniversity of LleidaLleidaSpain

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