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

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 deve...

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Autores: Escolà i Agustí, Alexandre, Martínez Casasnovas, José Antonio, Rufat i Lamarca, Josep, Arnó Satorra, Jaume, Arbonés, Amadeu, Sebé Feixas, Francesc, Pascual Roca, Miquel, Gregorio López, Eduard, Rosell Polo, Joan Ramon
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2017
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/62753
Acesso em linha:https://doi.org/10.1007/s11119-016-9474-5
http://hdl.handle.net/10459.1/62753
Access Level:acceso abierto
Palavra-chave:LiDAR
Canopy modelling
Precision Fructiculture
Olive orchard
Mobile terrestrial laser scanner
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spelling Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point cloudsEscolà i Agustí, AlexandreMartínez Casasnovas, José AntonioRufat i Lamarca, JosepArnó Satorra, JaumeArbonés, AmadeuSebé Feixas, FrancescPascual Roca, MiquelGregorio López, EduardRosell Polo, Joan RamonLiDARCanopy modellingPrecision FructicultureOlive orchardMobile terrestrial laser scannerLiDAR 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.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.Springer Science+Business Media2018201820172018info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://doi.org/10.1007/s11119-016-9474-5http://hdl.handle.net/10459.1/62753http://hdl.handle.net/10459.1/62753reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/grantAgreement/MICINN//AGL2010-22304-C04-03info:eu-repo/grantAgreement/MINECO//AGL2013-48297-C2-2-RVersió postprint del document publicat a: https://doi.org/10.1007/s11119-016-9474-5Precision Agriculture, 2017, vol. 18, núm.1, p. 111-132(c) Springer Science+Business Media, 2016info:eu-repo/semantics/openAccessoai:recercat.cat:10459.1/627532026-05-29T05:05:01Z
dc.title.none.fl_str_mv Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
title Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
spellingShingle Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
Escolà i Agustí, Alexandre
LiDAR
Canopy modelling
Precision Fructiculture
Olive orchard
Mobile terrestrial laser scanner
title_short Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
title_full Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
title_fullStr Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
title_full_unstemmed Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
title_sort Mobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
dc.creator.none.fl_str_mv Escolà i Agustí, Alexandre
Martínez Casasnovas, José Antonio
Rufat i Lamarca, Josep
Arnó Satorra, Jaume
Arbonés, Amadeu
Sebé Feixas, Francesc
Pascual Roca, Miquel
Gregorio López, Eduard
Rosell Polo, Joan Ramon
author Escolà i Agustí, Alexandre
author_facet Escolà i Agustí, Alexandre
Martínez Casasnovas, José Antonio
Rufat i Lamarca, Josep
Arnó Satorra, Jaume
Arbonés, Amadeu
Sebé Feixas, Francesc
Pascual Roca, Miquel
Gregorio López, Eduard
Rosell Polo, Joan Ramon
author_role author
author2 Martínez Casasnovas, José Antonio
Rufat i Lamarca, Josep
Arnó Satorra, Jaume
Arbonés, Amadeu
Sebé Feixas, Francesc
Pascual Roca, Miquel
Gregorio López, Eduard
Rosell Polo, Joan Ramon
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv LiDAR
Canopy modelling
Precision Fructiculture
Olive orchard
Mobile terrestrial laser scanner
topic LiDAR
Canopy modelling
Precision Fructiculture
Olive orchard
Mobile terrestrial laser scanner
description 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.
publishDate 2017
dc.date.none.fl_str_mv 2017
2018
2018
2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1007/s11119-016-9474-5
http://hdl.handle.net/10459.1/62753
http://hdl.handle.net/10459.1/62753
url https://doi.org/10.1007/s11119-016-9474-5
http://hdl.handle.net/10459.1/62753
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MICINN//AGL2010-22304-C04-03
info:eu-repo/grantAgreement/MINECO//AGL2013-48297-C2-2-R
Versió postprint del document publicat a: https://doi.org/10.1007/s11119-016-9474-5
Precision Agriculture, 2017, vol. 18, núm.1, p. 111-132
dc.rights.none.fl_str_mv (c) Springer Science+Business Media, 2016
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Springer Science+Business Media, 2016
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Science+Business Media
publisher.none.fl_str_mv Springer Science+Business Media
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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