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Orange tree canopy volume estimation by manual and LiDAR-based methods

Published online by Cambridge University Press:  01 June 2017

A. F. Colaço
Affiliation:
University of São Paulo, ‘Luiz de Queiroz’ College of Agriculture, Biosystems Engineering Department, Piracicaba-SP, Brazil
R. G. Trevisan
Affiliation:
University of São Paulo, ‘Luiz de Queiroz’ College of Agriculture, Biosystems Engineering Department, Piracicaba-SP, Brazil
J. P. Molin
Affiliation:
University of São Paulo, ‘Luiz de Queiroz’ College of Agriculture, Biosystems Engineering Department, Piracicaba-SP, Brazil
J. R. Rosell-Polo
Affiliation:
University of Lleida – Agrotecnio Center, School of Agrifood and Forestry Science and Engineering, Department of Agricultural and Forest Engineering, Research Group on AgroICT & Precision Agriculture, Lleida - Catalonia, Spain
A. Escolà
Affiliation:
University of Lleida – Agrotecnio Center, School of Agrifood and Forestry Science and Engineering, Department of Agricultural and Forest Engineering, Research Group on AgroICT & Precision Agriculture, Lleida - Catalonia, Spain
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Abstract

LiDAR (Light detection and ranging) technology is an alternative to current manual methods of canopy geometry estimations in orange trees. The objective of this work was to compare different types of canopy volume estimations of orange trees, some inspired on manual methods and others based on a LiDAR sensor. A point cloud was generated for 25 individual trees using a laser scanning system. The convex-hull and the alpha-shape surface reconstruction algorithms were tested. LiDAR derived models are able to represent orange trees more accurately than traditional methods. However, results differ significantly from the current manual method. In addition, different 3D modeling algorithms resulted in different canopy volume estimations. Therefore, a new standard method should be developed and established.

Type
Precision Horticulture and Viticulture
Copyright
© The Animal Consortium 2017 

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References

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Orange tree canopy volume estimation by manual and LiDAR-based methods
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