Estimation of cork production using aerial imagery

Detalhes bibliográficos
Autor(a) principal: Surovy, Peter
Data de Publicação: 2015
Outros Autores: Ribeiro, Nuno de Almeida, Pereira, João Santos, Yoshimoto, Atsushi
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.5/10597
Resumo: and organize harvest logistics (transport, storage, etc.). Common field inventory methods including the stem density, diameter and height structure are costly and generally point (plot) based. Furthermore, the irregular horizontal structure of cork oak stands makes it difficult, if not impossible, to interpolate between points. We propose a new method to estimate cork production using digital multispectral aerial imagery. We study the spectral response of individual trees in visible and near infrared spectra and then correlate that response with cork production prior to harvest. We use ground measurements of individual trees production to evaluate the model’s predictive capacity. We propose 14 candidate variables to predict cork production based on crown size in combination with different NDVI index derivates. We use Akaike Information Criteria to choose the best among them. The best model is composed of combinations of different NDVI derivates that include red, green, and blue channels. The proposed model is 15% more accurate than a model that includes only a crown projection without any spectral information
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spelling Estimation of cork production using aerial imageryEstimação da produção de cortiça usando imagens digitais aéreasNDVIremote sensingAkaike information criteriaand organize harvest logistics (transport, storage, etc.). Common field inventory methods including the stem density, diameter and height structure are costly and generally point (plot) based. Furthermore, the irregular horizontal structure of cork oak stands makes it difficult, if not impossible, to interpolate between points. We propose a new method to estimate cork production using digital multispectral aerial imagery. We study the spectral response of individual trees in visible and near infrared spectra and then correlate that response with cork production prior to harvest. We use ground measurements of individual trees production to evaluate the model’s predictive capacity. We propose 14 candidate variables to predict cork production based on crown size in combination with different NDVI index derivates. We use Akaike Information Criteria to choose the best among them. The best model is composed of combinations of different NDVI derivates that include red, green, and blue channels. The proposed model is 15% more accurate than a model that includes only a crown projection without any spectral informationSociedade de Investigações FlorestaisRepositório da Universidade de LisboaSurovy, PeterRibeiro, Nuno de AlmeidaPereira, João SantosYoshimoto, Atsushi2016-01-07T15:58:06Z20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/10597eng"Revista Árvore". ISSN 1806-9088. 39 (5) (2015) p. 853-861http://dx.doi.org/10.1590/0100-67622015000500008info: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:RCAAP2023-03-06T14:40:54Zoai:www.repository.utl.pt:10400.5/10597Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:57:02.200872Repositório 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 Estimation of cork production using aerial imagery
Estimação da produção de cortiça usando imagens digitais aéreas
title Estimation of cork production using aerial imagery
spellingShingle Estimation of cork production using aerial imagery
Surovy, Peter
NDVI
remote sensing
Akaike information criteria
title_short Estimation of cork production using aerial imagery
title_full Estimation of cork production using aerial imagery
title_fullStr Estimation of cork production using aerial imagery
title_full_unstemmed Estimation of cork production using aerial imagery
title_sort Estimation of cork production using aerial imagery
author Surovy, Peter
author_facet Surovy, Peter
Ribeiro, Nuno de Almeida
Pereira, João Santos
Yoshimoto, Atsushi
author_role author
author2 Ribeiro, Nuno de Almeida
Pereira, João Santos
Yoshimoto, Atsushi
author2_role author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Surovy, Peter
Ribeiro, Nuno de Almeida
Pereira, João Santos
Yoshimoto, Atsushi
dc.subject.por.fl_str_mv NDVI
remote sensing
Akaike information criteria
topic NDVI
remote sensing
Akaike information criteria
description and organize harvest logistics (transport, storage, etc.). Common field inventory methods including the stem density, diameter and height structure are costly and generally point (plot) based. Furthermore, the irregular horizontal structure of cork oak stands makes it difficult, if not impossible, to interpolate between points. We propose a new method to estimate cork production using digital multispectral aerial imagery. We study the spectral response of individual trees in visible and near infrared spectra and then correlate that response with cork production prior to harvest. We use ground measurements of individual trees production to evaluate the model’s predictive capacity. We propose 14 candidate variables to predict cork production based on crown size in combination with different NDVI index derivates. We use Akaike Information Criteria to choose the best among them. The best model is composed of combinations of different NDVI derivates that include red, green, and blue channels. The proposed model is 15% more accurate than a model that includes only a crown projection without any spectral information
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-01-01T00:00:00Z
2016-01-07T15:58:06Z
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 http://hdl.handle.net/10400.5/10597
url http://hdl.handle.net/10400.5/10597
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv "Revista Árvore". ISSN 1806-9088. 39 (5) (2015) p. 853-861
http://dx.doi.org/10.1590/0100-67622015000500008
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Sociedade de Investigações Florestais
publisher.none.fl_str_mv Sociedade de Investigações Florestais
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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