Plant Species Identification with Phenological Visual Rhythms

Detalhes bibliográficos
Autor(a) principal: Almeida, Jurandy
Data de Publicação: 2013
Outros Autores: Santos, Jefersson A. dos, Alberton, Bruna [UNESP], Morellato, Leonor Patricia C. [UNESP], Torres, Ricardo da S., IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/eScience.2013.43
http://hdl.handle.net/11449/196055
Resumo: Plant phenology studies recurrent plant life cycles events and is a key component of climate change research. To increase accuracy of observations, new technologies have been applied for phenological observation, and one of the most successful are digital cameras, used as multi-channel imaging sensors to estimate color changes that are related to phenological events. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. We extract individual plant color information and correlated with leaf phenological changes. To do so, time series associated with plant species were obtained, raising the need of using appropriate tools for mining patterns of interest. In this paper, we present a novel approach for representing phenological patterns of plant species derived from digital images. The proposed method is based on encoding time series as a visual rhythm, which is characterized by image description algorithms. A comparative analysis of different descriptors is conducted and discussed. Experimental results show that our approach presents high accuracy on identifying plant species.
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spelling Plant Species Identification with Phenological Visual Rhythmsremote phenologydigital camerasimage analysistime seriesvisual rhythmPlant phenology studies recurrent plant life cycles events and is a key component of climate change research. To increase accuracy of observations, new technologies have been applied for phenological observation, and one of the most successful are digital cameras, used as multi-channel imaging sensors to estimate color changes that are related to phenological events. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. We extract individual plant color information and correlated with leaf phenological changes. To do so, time series associated with plant species were obtained, raising the need of using appropriate tools for mining patterns of interest. In this paper, we present a novel approach for representing phenological patterns of plant species derived from digital images. The proposed method is based on encoding time series as a visual rhythm, which is characterized by image description algorithms. A comparative analysis of different descriptors is conducted and discussed. Experimental results show that our approach presents high accuracy on identifying plant species.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ Campinas UNICAMP, Inst Comp, RECOD Lab, BR-13083852 Campinas, SP, BrazilUniv Sao Paulo UNESP, Dept Bot, Phenot Lab, BR-13506900 Rio Claro, SP, BrazilUniv Sao Paulo UNESP, Dept Bot, Phenot Lab, BR-13506900 Rio Claro, SP, BrazilFAPESP: 2010/52113-5,FAPESP: 2011/11171-5FAPESP: 2012/18768-0FAPESP: 2012/16253-2FAPESP: 2013/50155-0CNPq: 306243/2010-5CNPq: 484254/2012-0CNPq: 306580/2012-8IeeeUniversidade Estadual de Campinas (UNICAMP)Universidade Estadual Paulista (Unesp)Almeida, JurandySantos, Jefersson A. dosAlberton, Bruna [UNESP]Morellato, Leonor Patricia C. [UNESP]Torres, Ricardo da S.IEEE2020-12-10T19:31:49Z2020-12-10T19:31:49Z2013-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject148-154http://dx.doi.org/10.1109/eScience.2013.432013 Ieee 9th International Conference On E-science (e-science). New York: Ieee, p. 148-154, 2013.2325-372Xhttp://hdl.handle.net/11449/19605510.1109/eScience.2013.43WOS:000330195500018Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2013 Ieee 9th International Conference On E-science (e-science)info:eu-repo/semantics/openAccess2021-10-23T03:03:55Zoai:repositorio.unesp.br:11449/196055Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:57:38.448317Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Plant Species Identification with Phenological Visual Rhythms
title Plant Species Identification with Phenological Visual Rhythms
spellingShingle Plant Species Identification with Phenological Visual Rhythms
Almeida, Jurandy
remote phenology
digital cameras
image analysis
time series
visual rhythm
title_short Plant Species Identification with Phenological Visual Rhythms
title_full Plant Species Identification with Phenological Visual Rhythms
title_fullStr Plant Species Identification with Phenological Visual Rhythms
title_full_unstemmed Plant Species Identification with Phenological Visual Rhythms
title_sort Plant Species Identification with Phenological Visual Rhythms
author Almeida, Jurandy
author_facet Almeida, Jurandy
Santos, Jefersson A. dos
Alberton, Bruna [UNESP]
Morellato, Leonor Patricia C. [UNESP]
Torres, Ricardo da S.
IEEE
author_role author
author2 Santos, Jefersson A. dos
Alberton, Bruna [UNESP]
Morellato, Leonor Patricia C. [UNESP]
Torres, Ricardo da S.
IEEE
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual de Campinas (UNICAMP)
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Almeida, Jurandy
Santos, Jefersson A. dos
Alberton, Bruna [UNESP]
Morellato, Leonor Patricia C. [UNESP]
Torres, Ricardo da S.
IEEE
dc.subject.por.fl_str_mv remote phenology
digital cameras
image analysis
time series
visual rhythm
topic remote phenology
digital cameras
image analysis
time series
visual rhythm
description Plant phenology studies recurrent plant life cycles events and is a key component of climate change research. To increase accuracy of observations, new technologies have been applied for phenological observation, and one of the most successful are digital cameras, used as multi-channel imaging sensors to estimate color changes that are related to phenological events. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. We extract individual plant color information and correlated with leaf phenological changes. To do so, time series associated with plant species were obtained, raising the need of using appropriate tools for mining patterns of interest. In this paper, we present a novel approach for representing phenological patterns of plant species derived from digital images. The proposed method is based on encoding time series as a visual rhythm, which is characterized by image description algorithms. A comparative analysis of different descriptors is conducted and discussed. Experimental results show that our approach presents high accuracy on identifying plant species.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01
2020-12-10T19:31:49Z
2020-12-10T19:31:49Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/eScience.2013.43
2013 Ieee 9th International Conference On E-science (e-science). New York: Ieee, p. 148-154, 2013.
2325-372X
http://hdl.handle.net/11449/196055
10.1109/eScience.2013.43
WOS:000330195500018
url http://dx.doi.org/10.1109/eScience.2013.43
http://hdl.handle.net/11449/196055
identifier_str_mv 2013 Ieee 9th International Conference On E-science (e-science). New York: Ieee, p. 148-154, 2013.
2325-372X
10.1109/eScience.2013.43
WOS:000330195500018
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2013 Ieee 9th International Conference On E-science (e-science)
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publisher.none.fl_str_mv Ieee
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reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
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reponame_str Repositório Institucional da UNESP
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repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
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