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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Authors: Arnó Satorra, Jaume; Escolà i Agustí, Alexandre; Rosell Polo, Joan Ramon
Format: Article
Status:Accepted version
Publication date:2017
Country:España
Institution:Universitat de Lleida (UdL)
Repository:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/59391
Online Access:https://doi.org/10.1007/s11119-016-9451-z
http://hdl.handle.net/10459.1/59391
Access Level:Open access
Keyword:LAI estimate
Precision viticulture
LiDAR
Viticultura
Agricultura
Viticulture
Agriculture
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author Arnó Satorra, Jaume
author2 Escolà i Agustí, Alexandre
Rosell Polo, Joan Ramon
author2_role author
author
author_browse Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
Rosell Polo, Joan Ramon
author_facet Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
Rosell Polo, Joan Ramon
author_role author
collection Repositori Obert UdL
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.
eu_rights_str_mv openAccess
format article
id ES_78adf6df7c2cc04bd866117fe53965d9
institution Universitat de Lleida (UdL)
instname_str Universitat de Lleida (UdL)
network_acronym_str ES
network_name_str España
oai_identifier_str oai:repositori.udl.cat:10459.1/59391
publishDate 2017
publishDateSort 2017
publisher Springer Science+Business Media
publisherStr Springer Science+Business Media
reponame_str Repositori Obert UdL
spelling Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners Arnó Satorra, Jaume Escolà i Agustí, Alexandre Rosell Polo, Joan Ramon LAI estimate Precision viticulture LiDAR Viticultura Agricultura Viticulture Agriculture 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. 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 acknowledged Springer Science+Business Media https://doi.org/10.1007/s11119-016-9451-z http://hdl.handle.net/10459.1/59391
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
status_str acceptedVersion
title 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_short 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
topic LAI estimate
Precision viticulture
LiDAR
Viticultura
Agricultura
Viticulture
Agriculture
topic_facet LAI estimate
Precision viticulture
LiDAR
Viticultura
Agricultura
Viticulture
Agriculture
url https://doi.org/10.1007/s11119-016-9451-z
http://hdl.handle.net/10459.1/59391