Discovering spatio-temporal patterns in precision agriculture based on triclustering

Detalhes bibliográficos
Autor(a) principal: Melgar-Garcia, Laura
Data de Publicação: 2020
Outros Autores: Godinho, Maria Teresa, Espada, Rita, Gutiérrez-Avilés, David, Martínez-Álvarez, Francisco, Troncoso, Alicia, Rubio-Escudero, Cristina, Brito, Isabel Sofia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/20.500.12207/6015
Resumo: Agriculture has undergone some very important changes over the last few decades. The emergence and evolution of precision agriculture has allowed to move from the uniform site management to the site-specific management, with both economic and environmental advantages. However, to be implemented effectively, site-specific management requires within-field spatial variability to be well-known and characterized. In this paper, an algorithm that delineates within-field management zones in a maize plantation is introduced. The algorithm, based on triclustering, mines clusters from temporal remote sensing data. Data frommaize crops in Alentejo, Portugal, have been used to assess the suitability of applying triclustering to discover patterns over time, that may eventually help farmers to improve their harvests.
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spelling Discovering spatio-temporal patterns in precision agriculture based on triclusteringTriclusteringSpatio-temporal patternsPrecision agricultureRemote sensingAgricultura de precisãoSensoriamento remotoAgriculture has undergone some very important changes over the last few decades. The emergence and evolution of precision agriculture has allowed to move from the uniform site management to the site-specific management, with both economic and environmental advantages. However, to be implemented effectively, site-specific management requires within-field spatial variability to be well-known and characterized. In this paper, an algorithm that delineates within-field management zones in a maize plantation is introduced. The algorithm, based on triclustering, mines clusters from temporal remote sensing data. Data frommaize crops in Alentejo, Portugal, have been used to assess the suitability of applying triclustering to discover patterns over time, that may eventually help farmers to improve their harvests.Springer2023-11-04T02:46:08Z2020-08-01T00:00:00Z2020-08info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://hdl.handle.net/20.500.12207/6015eng978-3-030-57801-5https://doi.org/10.1007/978-3-030-57802-2_22Melgar-Garcia, LauraGodinho, Maria TeresaEspada, RitaGutiérrez-Avilés, DavidMartínez-Álvarez, FranciscoTroncoso, AliciaRubio-Escudero, CristinaBrito, Isabel Sofiainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T08:17:17Zoai:repositorio.ipbeja.pt:20.500.12207/6015Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:10:06.486739Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Discovering spatio-temporal patterns in precision agriculture based on triclustering
title Discovering spatio-temporal patterns in precision agriculture based on triclustering
spellingShingle Discovering spatio-temporal patterns in precision agriculture based on triclustering
Melgar-Garcia, Laura
Triclustering
Spatio-temporal patterns
Precision agriculture
Remote sensing
Agricultura de precisão
Sensoriamento remoto
title_short Discovering spatio-temporal patterns in precision agriculture based on triclustering
title_full Discovering spatio-temporal patterns in precision agriculture based on triclustering
title_fullStr Discovering spatio-temporal patterns in precision agriculture based on triclustering
title_full_unstemmed Discovering spatio-temporal patterns in precision agriculture based on triclustering
title_sort Discovering spatio-temporal patterns in precision agriculture based on triclustering
author Melgar-Garcia, Laura
author_facet Melgar-Garcia, Laura
Godinho, Maria Teresa
Espada, Rita
Gutiérrez-Avilés, David
Martínez-Álvarez, Francisco
Troncoso, Alicia
Rubio-Escudero, Cristina
Brito, Isabel Sofia
author_role author
author2 Godinho, Maria Teresa
Espada, Rita
Gutiérrez-Avilés, David
Martínez-Álvarez, Francisco
Troncoso, Alicia
Rubio-Escudero, Cristina
Brito, Isabel Sofia
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Melgar-Garcia, Laura
Godinho, Maria Teresa
Espada, Rita
Gutiérrez-Avilés, David
Martínez-Álvarez, Francisco
Troncoso, Alicia
Rubio-Escudero, Cristina
Brito, Isabel Sofia
dc.subject.por.fl_str_mv Triclustering
Spatio-temporal patterns
Precision agriculture
Remote sensing
Agricultura de precisão
Sensoriamento remoto
topic Triclustering
Spatio-temporal patterns
Precision agriculture
Remote sensing
Agricultura de precisão
Sensoriamento remoto
description Agriculture has undergone some very important changes over the last few decades. The emergence and evolution of precision agriculture has allowed to move from the uniform site management to the site-specific management, with both economic and environmental advantages. However, to be implemented effectively, site-specific management requires within-field spatial variability to be well-known and characterized. In this paper, an algorithm that delineates within-field management zones in a maize plantation is introduced. The algorithm, based on triclustering, mines clusters from temporal remote sensing data. Data frommaize crops in Alentejo, Portugal, have been used to assess the suitability of applying triclustering to discover patterns over time, that may eventually help farmers to improve their harvests.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-01T00:00:00Z
2020-08
2023-11-04T02:46:08Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/20.500.12207/6015
url https://hdl.handle.net/20.500.12207/6015
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-3-030-57801-5
https://doi.org/10.1007/978-3-030-57802-2_22
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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