VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES
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://hdl.handle.net/11449/196071 |
Resumo: | Plant phenology has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. In this context, digital cameras have been successfully used as multi-channel imaging sensors, providing measures to estimate changes on phenological events, such as leaf flushing and senescence. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. For that, we extract leaf color information and correlated with phenological changes. In this way, time series associated with plant species are 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. The proposed method is based on encoding time series as a visual rhythm, which is characterized by color 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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Repositório Institucional da UNESP |
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VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIESremote phenologydigital camerasimage analysistime seriesvisual rhythmPlant phenology has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. In this context, digital cameras have been successfully used as multi-channel imaging sensors, providing measures to estimate changes on phenological events, such as leaf flushing and senescence. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. For that, we extract leaf color information and correlated with phenological changes. In this way, time series associated with plant species are 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. The proposed method is based on encoding time series as a visual rhythm, which is characterized by color 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.Univ Estadual Campinas, UNICAMP, Inst Comp, RECOD Lab, BR-13083852 Campinas, SP, BrazilSao Paulo State Univ, UNESP, Dept Bot, Phenol Lab, BR-13506900 Rio Claro, SP, BrazilSao Paulo State Univ, UNESP, Dept Bot, Phenol Lab, BR-13506900 Rio Claro, SP, BrazilIeeeUniversidade Estadual de Campinas (UNICAMP)Universidade Estadual Paulista (Unesp)Almeida, JurandySantos, Jefersson A. dosAlberton, Bruna C. [UNESP]Morellato, Leonor Patricia C. [UNESP]Torres, Ricardo da S.IEEE2020-12-10T19:32:21Z2020-12-10T19:32:21Z2013-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject4412-44162013 20th Ieee International Conference On Image Processing (icip 2013). New York: Ieee, p. 4412-4416, 2013.1522-4880http://hdl.handle.net/11449/196071WOS:000351597604095Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2013 20th Ieee International Conference On Image Processing (icip 2013)info:eu-repo/semantics/openAccess2021-10-23T03:12:27Zoai:repositorio.unesp.br:11449/196071Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T03:12:27Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES |
title |
VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES |
spellingShingle |
VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES Almeida, Jurandy remote phenology digital cameras image analysis time series visual rhythm |
title_short |
VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES |
title_full |
VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES |
title_fullStr |
VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES |
title_full_unstemmed |
VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES |
title_sort |
VISUAL RHYTHM-BASED TIME SERIES ANALYSIS FOR PHENOLOGY STUDIES |
author |
Almeida, Jurandy |
author_facet |
Almeida, Jurandy Santos, Jefersson A. dos Alberton, Bruna C. [UNESP] Morellato, Leonor Patricia C. [UNESP] Torres, Ricardo da S. IEEE |
author_role |
author |
author2 |
Santos, Jefersson A. dos Alberton, Bruna C. [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 C. [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 has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. In this context, digital cameras have been successfully used as multi-channel imaging sensors, providing measures to estimate changes on phenological events, such as leaf flushing and senescence. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. For that, we extract leaf color information and correlated with phenological changes. In this way, time series associated with plant species are 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. The proposed method is based on encoding time series as a visual rhythm, which is characterized by color 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 2020-12-10T19:32:21Z 2020-12-10T19:32:21Z |
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 |
2013 20th Ieee International Conference On Image Processing (icip 2013). New York: Ieee, p. 4412-4416, 2013. 1522-4880 http://hdl.handle.net/11449/196071 WOS:000351597604095 |
identifier_str_mv |
2013 20th Ieee International Conference On Image Processing (icip 2013). New York: Ieee, p. 4412-4416, 2013. 1522-4880 WOS:000351597604095 |
url |
http://hdl.handle.net/11449/196071 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2013 20th Ieee International Conference On Image Processing (icip 2013) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
4412-4416 |
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_ |
1803046727004979200 |