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dc.contributor.authorEscolà i Agustí, Alexandre
dc.contributor.authorMartínez Casasnovas, José Antonio
dc.contributor.authorRufat i Lamarca, Josep
dc.contributor.authorArnó Satorra, Jaume
dc.contributor.authorArbonés, Amadeu
dc.contributor.authorSebé Feixas, Francesc
dc.contributor.authorPascual Roca, Miquel
dc.contributor.authorGregorio López, Eduard
dc.contributor.authorRosell Polo, Joan Ramon
dc.date.accessioned2018-03-08T12:41:05Z
dc.date.available2018-03-08T12:41:05Z
dc.date.issued2017-01-01
dc.identifier.issn1385-2256
dc.identifier.urihttp://hdl.handle.net/10459.1/62753
dc.description.abstractLiDAR 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.
dc.description.sponsorshipThis 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.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer Science+Business Media
dc.relationMICINN/PN2008-2011/AGL2010-22304-C04-03
dc.relationMINECO/PN2013-2016/AGL2013-48297-C2-2-R
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1007/s11119-016-9474-5
dc.relation.ispartofPrecision Agriculture, 2017, vol. 18, núm.1, p. 111-132
dc.rights(c) Springer Science+Business Media, 2016
dc.subjectLiDAR
dc.subjectCanopy modelling
dc.subjectPrecision Fructiculture
dc.subjectOlive orchard
dc.subjectMobile terrestrial laser scanner
dc.titleMobile terrestrial laser scanner applications in precision fruticulture/ horticulture and tools to extract information from canopy point clouds
dc.typeinfo:eu-repo/semantics/article
dc.date.updated2018-03-08T12:41:05Z
dc.identifier.idgrec024779
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1007/s11119-016-9474-5


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