Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field

[EN] BACKGROUND: The common vole (Microtus arvalis) is a very destructive agricultural pest. Particularly in Europe, its monitoring is essential not only for adequate management and outbreak forecasting, but also for accurately determining the vole's impact on affected fields. In this study, se...

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Detalhes bibliográficos
Autores: Plaza Martín, Javier, Sánchez Martín, Nilda, García Ariza, Carmen, Pérez Sánchez, Rodrigo, Charfolé de Juan, José Francisco, Caminero Saldaña, Constantino
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Recursos:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/163119
Acesso em linha:http://hdl.handle.net/10366/163119
Access Level:acceso abierto
Palavra-chave:Alfalfa
Classification
Microtus arvalis Pallas
Multispectral
NDVI
UAS
Drones
Topillo campesino
Clasificación
2506.16 Teledetección (Geología)
3103.06 Cultivos de Campo
3308.08 Tecnología del Control de Roedores
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oai_identifier_str oai:gredos.usal.es:10366/163119
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spelling Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural fieldPlaza Martín, JavierSánchez Martín, NildaGarcía Ariza, CarmenPérez Sánchez, RodrigoCharfolé de Juan, José FranciscoCaminero Saldaña, ConstantinoAlfalfaClassificationMicrotus arvalis PallasMultispectralNDVIUASDronesTopillo campesinoClasificación2506.16 Teledetección (Geología)3103.06 Cultivos de Campo3308.08 Tecnología del Control de Roedores[EN] BACKGROUND: The common vole (Microtus arvalis) is a very destructive agricultural pest. Particularly in Europe, its monitoring is essential not only for adequate management and outbreak forecasting, but also for accurately determining the vole's impact on affected fields. In this study, several alternatives for estimating the damage to alfalfa fields by voles through unmanned vehicle systems (UASs) and multispectral cameras are presented. Currently, both the farmers and agencies involved in the integrated pest management (IPM) programs of voles do not have sufficiently precise methods for accurate assessments of the real impact to crops. RESULTS: Overall, the four multispectral classification methods presented showed similar performances. However, the normalized difference vegetation index (NDVI)-based segmentation exhibited the most accurate and reliable appraisal of the affected areas. Nevertheless, it must be noted that the simplest method, which was based on an automatic classification, provided results similar to those obtained by more complex methods. In addition, a significant direct relationship was found between the number of active burrows and damage to the alfalfa canopy. CONCLUSION: Unmanned vehicle systems, combined with multispectral imagery classification, are an effective and easily transferable methodology for the assessment and monitoring of common vole damage to agricultural plots. This combination of methods facilitates decision-making processes for IPM control strategies against this pest.Technological Agricultural Institute of Castilla y León (ITACyL) Diputaciones Provinciales of Palencia and ValladolidWiley202520252022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10366/163119reponame:GREDOS. Repositorio Institucional de la Universidad de Salamancainstname:Universidad de Salamanca (USAL)InglésGESINTTOPAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:gredos.usal.es:10366/1631192026-06-07T06:28:51Z
dc.title.none.fl_str_mv Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field
title Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field
spellingShingle Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field
Plaza Martín, Javier
Alfalfa
Classification
Microtus arvalis Pallas
Multispectral
NDVI
UAS
Drones
Topillo campesino
Clasificación
2506.16 Teledetección (Geología)
3103.06 Cultivos de Campo
3308.08 Tecnología del Control de Roedores
title_short Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field
title_full Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field
title_fullStr Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field
title_full_unstemmed Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field
title_sort Classification of airborne multispectral imagery to quantify common vole impacts on an agricultural field
dc.creator.none.fl_str_mv Plaza Martín, Javier
Sánchez Martín, Nilda
García Ariza, Carmen
Pérez Sánchez, Rodrigo
Charfolé de Juan, José Francisco
Caminero Saldaña, Constantino
author Plaza Martín, Javier
author_facet Plaza Martín, Javier
Sánchez Martín, Nilda
García Ariza, Carmen
Pérez Sánchez, Rodrigo
Charfolé de Juan, José Francisco
Caminero Saldaña, Constantino
author_role author
author2 Sánchez Martín, Nilda
García Ariza, Carmen
Pérez Sánchez, Rodrigo
Charfolé de Juan, José Francisco
Caminero Saldaña, Constantino
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Alfalfa
Classification
Microtus arvalis Pallas
Multispectral
NDVI
UAS
Drones
Topillo campesino
Clasificación
2506.16 Teledetección (Geología)
3103.06 Cultivos de Campo
3308.08 Tecnología del Control de Roedores
topic Alfalfa
Classification
Microtus arvalis Pallas
Multispectral
NDVI
UAS
Drones
Topillo campesino
Clasificación
2506.16 Teledetección (Geología)
3103.06 Cultivos de Campo
3308.08 Tecnología del Control de Roedores
description [EN] BACKGROUND: The common vole (Microtus arvalis) is a very destructive agricultural pest. Particularly in Europe, its monitoring is essential not only for adequate management and outbreak forecasting, but also for accurately determining the vole's impact on affected fields. In this study, several alternatives for estimating the damage to alfalfa fields by voles through unmanned vehicle systems (UASs) and multispectral cameras are presented. Currently, both the farmers and agencies involved in the integrated pest management (IPM) programs of voles do not have sufficiently precise methods for accurate assessments of the real impact to crops. RESULTS: Overall, the four multispectral classification methods presented showed similar performances. However, the normalized difference vegetation index (NDVI)-based segmentation exhibited the most accurate and reliable appraisal of the affected areas. Nevertheless, it must be noted that the simplest method, which was based on an automatic classification, provided results similar to those obtained by more complex methods. In addition, a significant direct relationship was found between the number of active burrows and damage to the alfalfa canopy. CONCLUSION: Unmanned vehicle systems, combined with multispectral imagery classification, are an effective and easily transferable methodology for the assessment and monitoring of common vole damage to agricultural plots. This combination of methods facilitates decision-making processes for IPM control strategies against this pest.
publishDate 2022
dc.date.none.fl_str_mv 2022
2025
2025
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 http://hdl.handle.net/10366/163119
url http://hdl.handle.net/10366/163119
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv GESINTTOP
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname:Universidad de Salamanca (USAL)
instname_str Universidad de Salamanca (USAL)
reponame_str GREDOS. Repositorio Institucional de la Universidad de Salamanca
collection GREDOS. Repositorio Institucional de la Universidad de Salamanca
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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