Plant Species Identification with Phenological Visual Rhythms
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , , |
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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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 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
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) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
148-154 |
dc.publisher.none.fl_str_mv |
Ieee |
publisher.none.fl_str_mv |
Ieee |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128441747243008 |