Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Detalles Bibliográficos
Autores: Andújar, Dionisio, Rueda-Ayala, Víctor, Moreno, Hugo, Rosell-Polo, Joan R., Escolà Agustí, Alexandre, Valero, Constantino, Gerhards, Roland, Fernández-Quintanilla, César, Dorado, José, Griepentrog, Hans-Werner
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2013
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/109044
Acceso en línea:http://hdl.handle.net/10261/109044
Access Level:acceso abierto
Palabra clave:Chemical control
Weed proximal-sensing
Site-specific weed control
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spelling Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensorAndújar, DionisioRueda-Ayala, VíctorMoreno, HugoRosell-Polo, Joan R.Escolà Agustí, AlexandreValero, ConstantinoGerhards, RolandFernández-Quintanilla, CésarDorado, JoséGriepentrog, Hans-WernerChemical controlWeed proximal-sensingSite-specific weed controlThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12-14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying. © 2013 by the authors; licensee MDPI, Basel, Switzerland.Peer ReviewedMultidisciplinary Digital Publishing InstituteConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2014201420132014info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/109044reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttp://dx.doi.org/10.3390/s131114662Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1090442026-05-22T06:33:51Z
dc.title.none.fl_str_mv Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor
title Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor
spellingShingle Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor
Andújar, Dionisio
Chemical control
Weed proximal-sensing
Site-specific weed control
title_short Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor
title_full Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor
title_fullStr Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor
title_full_unstemmed Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor
title_sort Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor
dc.creator.none.fl_str_mv Andújar, Dionisio
Rueda-Ayala, Víctor
Moreno, Hugo
Rosell-Polo, Joan R.
Escolà Agustí, Alexandre
Valero, Constantino
Gerhards, Roland
Fernández-Quintanilla, César
Dorado, José
Griepentrog, Hans-Werner
author Andújar, Dionisio
author_facet Andújar, Dionisio
Rueda-Ayala, Víctor
Moreno, Hugo
Rosell-Polo, Joan R.
Escolà Agustí, Alexandre
Valero, Constantino
Gerhards, Roland
Fernández-Quintanilla, César
Dorado, José
Griepentrog, Hans-Werner
author_role author
author2 Rueda-Ayala, Víctor
Moreno, Hugo
Rosell-Polo, Joan R.
Escolà Agustí, Alexandre
Valero, Constantino
Gerhards, Roland
Fernández-Quintanilla, César
Dorado, José
Griepentrog, Hans-Werner
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Chemical control
Weed proximal-sensing
Site-specific weed control
topic Chemical control
Weed proximal-sensing
Site-specific weed control
description This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
publishDate 2013
dc.date.none.fl_str_mv 2013
2014
2014
2014
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/109044
url http://hdl.handle.net/10261/109044
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://dx.doi.org/10.3390/s131114662
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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