Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners

Mapping the leaf area index (LAI) by using mobile terrestrial laser scanners (MTLS) is of significance for viticulture. LAI is related to plant vigour and foliar development being an important parameter for many agricultural practices. Since it may present spatial variability within vineyards, it is...

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Autores: Arnó Satorra, Jaume, Escolà i Agustí, Alexandre, Rosell Polo, Joan Ramon
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2017
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/59391
Acceso en línea:https://doi.org/10.1007/s11119-016-9451-z
http://hdl.handle.net/10459.1/59391
Access Level:acceso abierto
Palabra clave:LAI estimate
Precision viticulture
LiDAR
Viticultura
Agricultura
Viticulture
Agriculture
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spelling Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scannersArnó Satorra, JaumeEscolà i Agustí, AlexandreRosell Polo, Joan RamonLAI estimatePrecision viticultureLiDARViticulturaAgriculturaViticultureAgricultureMapping the leaf area index (LAI) by using mobile terrestrial laser scanners (MTLS) is of significance for viticulture. LAI is related to plant vigour and foliar development being an important parameter for many agricultural practices. Since it may present spatial variability within vineyards, it is very interesting monitoring it in an objective repeatable way. Considering the possibility of using on-the-go sensors such as MTLS within an agricultural plot, it is necessary to set a proper length of the row to be scanned at each sample point for a reliable operation of the scanner. Three different row length sections of 0.5, 1, and 2 m have been tested. Data analysis has shown that models required to estimate LAI differ significantly depending on the scanned length of the row; the model required to estimate LAI for short sections (0.5 m) is different from that required for longer sections (1 and 2 m). Of the two models obtained, we recommend using MTLS for scanning row length sections of 1 m because the practical use of the sensor in the field is simplified without compromising the results (there is little variation in the model when the row length section changes from 1 to 2 m). In addition, a sufficient number of sampling points is obtained to support a map of the LAI. Linear regression models using as explanatory variable the tree area index, obtained from the data provided by the scanner, are used to estimate the LAI.The authors acknowledge funding from the Spanish Ministry of Science and Education (OPTIDOSA research project, AGL2007-66093-C04-03) and the ERDF (European Regional Development Fund). The agreement with Codornıu allowing the use of the vineyard in Raimat is also acknowledgedSpringer Science+Business Media2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://doi.org/10.1007/s11119-016-9451-zhttp://hdl.handle.net/10459.1/59391reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)Inglésinfo:eu-repo/grantAgreement/MEC//AGL2007-66093-C04-03Versió postprint del document publicat a: https://doi.org/10.1007/s11119-016-9451-zPrecision Agriculture, 2017, vol. 18, núm. 2, p. 145-151(c) Springer Science+Business Media, 2017info:eu-repo/semantics/openAccessoai:repositori.udl.cat:10459.1/593912026-06-24T12:42:17Z
dc.title.none.fl_str_mv Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners
title Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners
spellingShingle Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners
Arnó Satorra, Jaume
LAI estimate
Precision viticulture
LiDAR
Viticultura
Agricultura
Viticulture
Agriculture
title_short Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners
title_full Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners
title_fullStr Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners
title_full_unstemmed Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners
title_sort Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners
dc.creator.none.fl_str_mv Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
Rosell Polo, Joan Ramon
author Arnó Satorra, Jaume
author_facet Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
Rosell Polo, Joan Ramon
author_role author
author2 Escolà i Agustí, Alexandre
Rosell Polo, Joan Ramon
author2_role author
author
dc.subject.none.fl_str_mv LAI estimate
Precision viticulture
LiDAR
Viticultura
Agricultura
Viticulture
Agriculture
topic LAI estimate
Precision viticulture
LiDAR
Viticultura
Agricultura
Viticulture
Agriculture
description Mapping the leaf area index (LAI) by using mobile terrestrial laser scanners (MTLS) is of significance for viticulture. LAI is related to plant vigour and foliar development being an important parameter for many agricultural practices. Since it may present spatial variability within vineyards, it is very interesting monitoring it in an objective repeatable way. Considering the possibility of using on-the-go sensors such as MTLS within an agricultural plot, it is necessary to set a proper length of the row to be scanned at each sample point for a reliable operation of the scanner. Three different row length sections of 0.5, 1, and 2 m have been tested. Data analysis has shown that models required to estimate LAI differ significantly depending on the scanned length of the row; the model required to estimate LAI for short sections (0.5 m) is different from that required for longer sections (1 and 2 m). Of the two models obtained, we recommend using MTLS for scanning row length sections of 1 m because the practical use of the sensor in the field is simplified without compromising the results (there is little variation in the model when the row length section changes from 1 to 2 m). In addition, a sufficient number of sampling points is obtained to support a map of the LAI. Linear regression models using as explanatory variable the tree area index, obtained from the data provided by the scanner, are used to estimate the LAI.
publishDate 2017
dc.date.none.fl_str_mv 2017
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/s11119-016-9451-z
http://hdl.handle.net/10459.1/59391
url https://doi.org/10.1007/s11119-016-9451-z
http://hdl.handle.net/10459.1/59391
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MEC//AGL2007-66093-C04-03
Versió postprint del document publicat a: https://doi.org/10.1007/s11119-016-9451-z
Precision Agriculture, 2017, vol. 18, núm. 2, p. 145-151
dc.rights.none.fl_str_mv (c) Springer Science+Business Media, 2017
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Springer Science+Business Media, 2017
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:Repositori Obert UdL
instname:Universitat de Lleida (UdL)
instname_str Universitat de Lleida (UdL)
reponame_str Repositori Obert UdL
collection Repositori Obert UdL
repository.name.fl_str_mv
repository.mail.fl_str_mv
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