A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees

In recent decades, a considerable number of sensors have been developed to obtain 3D point clouds that have great potential in optimizing management in agriculture through the application of precision agriculture techniques. In order to use the data provided by these sensors, it is essential to know...

Descripción completa

Detalles Bibliográficos
Autores: Lavaquiol Colell, Bernat, Sanz Cortiella, Ricardo, Llorens Calveras, Jordi, Arnó Satorra, Jaume, Escolà i Agustí, Alexandre
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución: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:10459.1/72407
Acceso en línea:https://doi.org/10.1016/j.compag.2021.106553
http://hdl.handle.net/10459.1/72407
Access Level:acceso abierto
Palabra clave:Photogrammetry
Ground-truth
Precision agriculture
3D sensors
Image-based point cloud
id ES_0e9b0bb957daad79ab4c834337e4f366
oai_identifier_str oai:recercat.cat:10459.1/72407
network_acronym_str ES
network_name_str España
repository_id_str
spelling A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit treesLavaquiol Colell, BernatSanz Cortiella, RicardoLlorens Calveras, JordiArnó Satorra, JaumeEscolà i Agustí, AlexandrePhotogrammetryGround-truthPrecision agriculture3D sensorsImage-based point cloudIn recent decades, a considerable number of sensors have been developed to obtain 3D point clouds that have great potential in optimizing management in agriculture through the application of precision agriculture techniques. In order to use the data provided by these sensors, it is essential to know their measurement error. In this paper, a methodology is presented for obtaining a 3D point cloud of a central axis training system defoliated fruit tree (Malus domestica Bork.) obtained from stereophotogrammetry techniques based on structure-from-motion (SfM) and multi-view stereo-photogrammetry (MVS). The point cloud was made from a set of 288 photographs of the scene including the ground truth tree which was used to generate the digital 3D model. The resulting point cloud was validated and proven to faithfully represent reality. The bias of the resulting model is −0.15 mm and 0.05 mm, for diameters and lengths, respectively. In addition, the presented methodology allows small changes in the ground truth actual tree to be detected as a consequence of the wood dehydration process. Having an actual and a digital ground-truth is the basis for validating other sensing systems for 3D vegetation characterization which can be used to obtain data to make more informed management decisions.This research was funded by the Spanish Ministry of Economy and Competitiveness and the Ministry of Science, Innovation and Universities through the program Plan Estatal I+D+i Orientada a los Retos de la Sociedad, Project PAgFRUIT RTI2018-094222-B-I00. In addition, this work was also supported by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya under Grant 2017-SGR-646 and under the research grant program BFC2020S - Programa Santander Predocs UdL 2020. We would also like to thank Jaume Badia from Nufri for providing the tree used in this article as ground truth.Elsevier2021202120212021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.1016/j.compag.2021.106553http://hdl.handle.net/10459.1/72407http://hdl.handle.net/10459.1/72407reponame: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/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094222-B-I00Reproducció del document publicat a: https://doi.org/10.1016/j.compag.2021.106553Computers and Electronics in Agriculture, 2021, vol. 191, p. 106553cc-by-nc-nd (c) Lavaquiol et al., 2021info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/3.0/esoai:recercat.cat:10459.1/724072026-05-29T05:05:01Z
dc.title.none.fl_str_mv A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees
title A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees
spellingShingle A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees
Lavaquiol Colell, Bernat
Photogrammetry
Ground-truth
Precision agriculture
3D sensors
Image-based point cloud
title_short A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees
title_full A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees
title_fullStr A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees
title_full_unstemmed A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees
title_sort A photogrammetry-based methodology to obtain accurate digital ground-truth of leafless fruit trees
dc.creator.none.fl_str_mv Lavaquiol Colell, Bernat
Sanz Cortiella, Ricardo
Llorens Calveras, Jordi
Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
author Lavaquiol Colell, Bernat
author_facet Lavaquiol Colell, Bernat
Sanz Cortiella, Ricardo
Llorens Calveras, Jordi
Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
author_role author
author2 Sanz Cortiella, Ricardo
Llorens Calveras, Jordi
Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
author2_role author
author
author
author
dc.subject.none.fl_str_mv Photogrammetry
Ground-truth
Precision agriculture
3D sensors
Image-based point cloud
topic Photogrammetry
Ground-truth
Precision agriculture
3D sensors
Image-based point cloud
description In recent decades, a considerable number of sensors have been developed to obtain 3D point clouds that have great potential in optimizing management in agriculture through the application of precision agriculture techniques. In order to use the data provided by these sensors, it is essential to know their measurement error. In this paper, a methodology is presented for obtaining a 3D point cloud of a central axis training system defoliated fruit tree (Malus domestica Bork.) obtained from stereophotogrammetry techniques based on structure-from-motion (SfM) and multi-view stereo-photogrammetry (MVS). The point cloud was made from a set of 288 photographs of the scene including the ground truth tree which was used to generate the digital 3D model. The resulting point cloud was validated and proven to faithfully represent reality. The bias of the resulting model is −0.15 mm and 0.05 mm, for diameters and lengths, respectively. In addition, the presented methodology allows small changes in the ground truth actual tree to be detected as a consequence of the wood dehydration process. Having an actual and a digital ground-truth is the basis for validating other sensing systems for 3D vegetation characterization which can be used to obtain data to make more informed management decisions.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1016/j.compag.2021.106553
http://hdl.handle.net/10459.1/72407
http://hdl.handle.net/10459.1/72407
url https://doi.org/10.1016/j.compag.2021.106553
http://hdl.handle.net/10459.1/72407
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094222-B-I00
Reproducció del document publicat a: https://doi.org/10.1016/j.compag.2021.106553
Computers and Electronics in Agriculture, 2021, vol. 191, p. 106553
dc.rights.none.fl_str_mv cc-by-nc-nd (c) Lavaquiol et al., 2021
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/3.0/es
rights_invalid_str_mv cc-by-nc-nd (c) Lavaquiol et al., 2021
http://creativecommons.org/licenses/by-nc-nd/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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
_version_ 1869403407119286272
score 15,811543

Similares en LA Referencia