Leaf area index estimation in vineyards using a ground-based LiDAR scanner

Estimation of grapevine vigour using mobile proximal sensors can provide an indirect method for determining grape yield and quality. Of the various indexes related to the characteristics of grapevine foliage, the leaf area index (LAI) is probably the most widely used in viticulture. To assess the fe...

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Autores: Arnó Satorra, Jaume, Escolà i Agustí, Alexandre, Vallès Petit, Josep Maria, Llorens Calveras, Jordi, Sanz Cortiella, Ricardo, Masip Vilalta, Joan, Palacín Roca, Jordi, Rosell Polo, Joan Ramon
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2013
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:10459.1/49362
Acesso em linha:https://doi.org/10.1007/s11119-012-9295-0
http://hdl.handle.net/10459.1/49362
Access Level:acceso abierto
Palavra-chave:LAI
Precision viticulture
Proximal sensing
Terrestrial laser scanner
Vinya
Lidar
Radar òptic
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repository_id_str
spelling Leaf area index estimation in vineyards using a ground-based LiDAR scannerArnó Satorra, JaumeEscolà i Agustí, AlexandreVallès Petit, Josep MariaLlorens Calveras, JordiSanz Cortiella, RicardoMasip Vilalta, JoanPalacín Roca, JordiRosell Polo, Joan RamonLAIPrecision viticultureProximal sensingTerrestrial laser scannerVinyaLidarRadar òpticEstimation of grapevine vigour using mobile proximal sensors can provide an indirect method for determining grape yield and quality. Of the various indexes related to the characteristics of grapevine foliage, the leaf area index (LAI) is probably the most widely used in viticulture. To assess the feasibility of using light detection and ranging (LiDAR) sensors for predicting the LAI, several field trials were performed using a tractor-mounted LiDAR system. This system measured the crop in a transverse direction along the rows of vines and geometric and structural parameters were computed. The parameters evaluated were the height of the vines (H), the cross-sectional area (A), the canopy volume (V) and the tree area index (TAI). This last parameter was formulated as the ratio of the crop estimated area per unit ground area, using a local Poisson distribution to approximate the laser beam transmission probability within vines. In order to compare the calculated indexes with the actual values of LAI, the scanned vines were defoliated to obtain LAI values for different row sections. Linear regression analysis showed a good correlation (R 2 = 0.81) between canopy volume and the measured values of LAI for 1 m long sections. Nevertheless, the best estimation of the LAI was given by the TAI (R 2 = 0.92) for the same length, confirming LiDAR sensors as an interesting option for foliage characterization of grapevines. However, current limitations exist related to the complexity of data process and to the need to accumulate a sufficient number of scans to adequately estimate the LAI.This research was funded by ERDF (European Regional Development Fund) and the Spanish Ministry of Science and Education (Agreement No. AGL2002-04260-C04-02, and acronym PULVEXACT, and Agreement No. AGL2007-66093-C04-03, and acronym OPTIDOSA)Springer2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttps://doi.org/10.1007/s11119-012-9295-0http://hdl.handle.net/10459.1/49362reponame: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/MICYT//AGL2002‐04260‐C04‐02info:eu-repo/grantAgreement/MEC//AGL2007-66093-C04-03Versió prosprint del document publicat a https://doi.org/10.1007/s11119-012-9295-0Precision Agriculture, 2013, vol. 14, núm. 3, p. 290-306(c) Springer, 2013info:eu-repo/semantics/openAccessoai:recercat.cat:10459.1/493622026-05-29T05:05:01Z
dc.title.none.fl_str_mv Leaf area index estimation in vineyards using a ground-based LiDAR scanner
title Leaf area index estimation in vineyards using a ground-based LiDAR scanner
spellingShingle Leaf area index estimation in vineyards using a ground-based LiDAR scanner
Arnó Satorra, Jaume
LAI
Precision viticulture
Proximal sensing
Terrestrial laser scanner
Vinya
Lidar
Radar òptic
title_short Leaf area index estimation in vineyards using a ground-based LiDAR scanner
title_full Leaf area index estimation in vineyards using a ground-based LiDAR scanner
title_fullStr Leaf area index estimation in vineyards using a ground-based LiDAR scanner
title_full_unstemmed Leaf area index estimation in vineyards using a ground-based LiDAR scanner
title_sort Leaf area index estimation in vineyards using a ground-based LiDAR scanner
dc.creator.none.fl_str_mv Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
Vallès Petit, Josep Maria
Llorens Calveras, Jordi
Sanz Cortiella, Ricardo
Masip Vilalta, Joan
Palacín Roca, Jordi
Rosell Polo, Joan Ramon
author Arnó Satorra, Jaume
author_facet Arnó Satorra, Jaume
Escolà i Agustí, Alexandre
Vallès Petit, Josep Maria
Llorens Calveras, Jordi
Sanz Cortiella, Ricardo
Masip Vilalta, Joan
Palacín Roca, Jordi
Rosell Polo, Joan Ramon
author_role author
author2 Escolà i Agustí, Alexandre
Vallès Petit, Josep Maria
Llorens Calveras, Jordi
Sanz Cortiella, Ricardo
Masip Vilalta, Joan
Palacín Roca, Jordi
Rosell Polo, Joan Ramon
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv LAI
Precision viticulture
Proximal sensing
Terrestrial laser scanner
Vinya
Lidar
Radar òptic
topic LAI
Precision viticulture
Proximal sensing
Terrestrial laser scanner
Vinya
Lidar
Radar òptic
description Estimation of grapevine vigour using mobile proximal sensors can provide an indirect method for determining grape yield and quality. Of the various indexes related to the characteristics of grapevine foliage, the leaf area index (LAI) is probably the most widely used in viticulture. To assess the feasibility of using light detection and ranging (LiDAR) sensors for predicting the LAI, several field trials were performed using a tractor-mounted LiDAR system. This system measured the crop in a transverse direction along the rows of vines and geometric and structural parameters were computed. The parameters evaluated were the height of the vines (H), the cross-sectional area (A), the canopy volume (V) and the tree area index (TAI). This last parameter was formulated as the ratio of the crop estimated area per unit ground area, using a local Poisson distribution to approximate the laser beam transmission probability within vines. In order to compare the calculated indexes with the actual values of LAI, the scanned vines were defoliated to obtain LAI values for different row sections. Linear regression analysis showed a good correlation (R 2 = 0.81) between canopy volume and the measured values of LAI for 1 m long sections. Nevertheless, the best estimation of the LAI was given by the TAI (R 2 = 0.92) for the same length, confirming LiDAR sensors as an interesting option for foliage characterization of grapevines. However, current limitations exist related to the complexity of data process and to the need to accumulate a sufficient number of scans to adequately estimate the LAI.
publishDate 2013
dc.date.none.fl_str_mv 2013
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/s11119-012-9295-0
http://hdl.handle.net/10459.1/49362
url https://doi.org/10.1007/s11119-012-9295-0
http://hdl.handle.net/10459.1/49362
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MICYT//AGL2002‐04260‐C04‐02
info:eu-repo/grantAgreement/MEC//AGL2007-66093-C04-03
Versió prosprint del document publicat a https://doi.org/10.1007/s11119-012-9295-0
Precision Agriculture, 2013, vol. 14, núm. 3, p. 290-306
dc.rights.none.fl_str_mv (c) Springer, 2013
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Springer, 2013
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
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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score 15,811543

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