Enhanced gap fraction extraction from hemispherical photography

Autores
Díaz, Gastón Mauro; Lencinas, José Daniel
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Canopy structure can be estimated using gap fraction (GF) data, which can be directly measured with hemispherical photography. However, GF data accuracy is affected by sunlit canopy, multiple scattering, vignetting, blooming, and chromatic aberration. Here, we present an algorithm to classify hemispherical photography, whose aim is to reduce errors in the extraction of GF data. The algorithm, which was implemented in free software, uses color transformations, fuzzy logic, and object-based image analysis. The results suggest that color and texture, rather that only brightness, can be used to extract GF data.
Fil: Díaz, Gastón Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lencinas, José Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Forestry
Fuzzy Logic
Fisheye Photography
Image Classification
Image Texture Analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/21201
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/21201
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Enhanced gap fraction extraction from hemispherical photographyDíaz, Gastón MauroLencinas, José DanielForestryFuzzy LogicFisheye PhotographyImage ClassificationImage Texture Analysishttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Canopy structure can be estimated using gap fraction (GF) data, which can be directly measured with hemispherical photography. However, GF data accuracy is affected by sunlit canopy, multiple scattering, vignetting, blooming, and chromatic aberration. Here, we present an algorithm to classify hemispherical photography, whose aim is to reduce errors in the extraction of GF data. The algorithm, which was implemented in free software, uses color transformations, fuzzy logic, and object-based image analysis. The results suggest that color and texture, rather that only brightness, can be used to extract GF data.Fil: Díaz, Gastón Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lencinas, José Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaInstitute of Electrical and Electronics Engineers2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/21201Díaz, Gastón Mauro; Lencinas, José Daniel; Enhanced gap fraction extraction from hemispherical photography; Institute of Electrical and Electronics Engineers; Ieee Geoscience and Remote Sensing Letters; 12; 8; 3-2015; 1785-17891545-598X1558-0571CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/document/7103294/info:eu-repo/semantics/altIdentifier/doi/10.1109/LGRS.2015.2425931info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:45:53Zoai:ri.conicet.gov.ar:11336/21201instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:45:53.818CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Enhanced gap fraction extraction from hemispherical photography
title Enhanced gap fraction extraction from hemispherical photography
spellingShingle Enhanced gap fraction extraction from hemispherical photography
Díaz, Gastón Mauro
Forestry
Fuzzy Logic
Fisheye Photography
Image Classification
Image Texture Analysis
title_short Enhanced gap fraction extraction from hemispherical photography
title_full Enhanced gap fraction extraction from hemispherical photography
title_fullStr Enhanced gap fraction extraction from hemispherical photography
title_full_unstemmed Enhanced gap fraction extraction from hemispherical photography
title_sort Enhanced gap fraction extraction from hemispherical photography
dc.creator.none.fl_str_mv Díaz, Gastón Mauro
Lencinas, José Daniel
author Díaz, Gastón Mauro
author_facet Díaz, Gastón Mauro
Lencinas, José Daniel
author_role author
author2 Lencinas, José Daniel
author2_role author
dc.subject.none.fl_str_mv Forestry
Fuzzy Logic
Fisheye Photography
Image Classification
Image Texture Analysis
topic Forestry
Fuzzy Logic
Fisheye Photography
Image Classification
Image Texture Analysis
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Canopy structure can be estimated using gap fraction (GF) data, which can be directly measured with hemispherical photography. However, GF data accuracy is affected by sunlit canopy, multiple scattering, vignetting, blooming, and chromatic aberration. Here, we present an algorithm to classify hemispherical photography, whose aim is to reduce errors in the extraction of GF data. The algorithm, which was implemented in free software, uses color transformations, fuzzy logic, and object-based image analysis. The results suggest that color and texture, rather that only brightness, can be used to extract GF data.
Fil: Díaz, Gastón Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lencinas, José Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Canopy structure can be estimated using gap fraction (GF) data, which can be directly measured with hemispherical photography. However, GF data accuracy is affected by sunlit canopy, multiple scattering, vignetting, blooming, and chromatic aberration. Here, we present an algorithm to classify hemispherical photography, whose aim is to reduce errors in the extraction of GF data. The algorithm, which was implemented in free software, uses color transformations, fuzzy logic, and object-based image analysis. The results suggest that color and texture, rather that only brightness, can be used to extract GF data.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/21201
Díaz, Gastón Mauro; Lencinas, José Daniel; Enhanced gap fraction extraction from hemispherical photography; Institute of Electrical and Electronics Engineers; Ieee Geoscience and Remote Sensing Letters; 12; 8; 3-2015; 1785-1789
1545-598X
1558-0571
CONICET Digital
CONICET
url http://hdl.handle.net/11336/21201
identifier_str_mv Díaz, Gastón Mauro; Lencinas, José Daniel; Enhanced gap fraction extraction from hemispherical photography; Institute of Electrical and Electronics Engineers; Ieee Geoscience and Remote Sensing Letters; 12; 8; 3-2015; 1785-1789
1545-598X
1558-0571
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://ieeexplore.ieee.org/document/7103294/
info:eu-repo/semantics/altIdentifier/doi/10.1109/LGRS.2015.2425931
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844613434891567104
score 13.070432

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