Pixelwise Time Series Retrieval in Phenological Studies

Detalhes bibliográficos
Autor(a) principal: Santos, Elisangela Silva
Data de Publicação: 2019
Outros Autores: Alberton, Bruna [UNESP], Morellato, Leonor Patricia [UNESP], Da Silva Torres, Ricardo
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/IGARSS.2019.8898112
http://hdl.handle.net/11449/232954
Resumo: The support of time series similarity searches might be crucial in phenology studies, in which long-term time series analysis based on the identification of similar and different phenological patterns shared by individuals belonging to different species is a widely common task. In this paper, we introduce the use of well-established Information Retrieval (IR) technologies in the search of time series. The solution comprises four main steps: extraction of an image-based time series representation; image content description to encode time series properties and patterns; textual signature extraction based on image content descriptions; and textual signature indexing using off-the-shelf IR approaches. In this paper, we demonstrate both the effectiveness and the efficiency of the proposed solution in time series retrieval problems related to the management of phenological data associated with near-surface vegetation images.
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spelling Pixelwise Time Series Retrieval in Phenological Studiesinformation retrievalphenologyrecurrence plottime series retrievalThe support of time series similarity searches might be crucial in phenology studies, in which long-term time series analysis based on the identification of similar and different phenological patterns shared by individuals belonging to different species is a widely common task. In this paper, we introduce the use of well-established Information Retrieval (IR) technologies in the search of time series. The solution comprises four main steps: extraction of an image-based time series representation; image content description to encode time series properties and patterns; textual signature extraction based on image content descriptions; and textual signature indexing using off-the-shelf IR approaches. In this paper, we demonstrate both the effectiveness and the efficiency of the proposed solution in time series retrieval problems related to the management of phenological data associated with near-surface vegetation images.University of Campinas Institute of ComputingUniversidade Estadual PaulistaUniversidade Estadual PaulistaUniversidade Estadual de Campinas (UNICAMP)Universidade Estadual Paulista (UNESP)Santos, Elisangela SilvaAlberton, Bruna [UNESP]Morellato, Leonor Patricia [UNESP]Da Silva Torres, Ricardo2022-04-30T22:28:33Z2022-04-30T22:28:33Z2019-07-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject6586-6589http://dx.doi.org/10.1109/IGARSS.2019.8898112International Geoscience and Remote Sensing Symposium (IGARSS), p. 6586-6589.http://hdl.handle.net/11449/23295410.1109/IGARSS.2019.88981122-s2.0-85077688255Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Geoscience and Remote Sensing Symposium (IGARSS)info:eu-repo/semantics/openAccess2022-04-30T22:28:33Zoai:repositorio.unesp.br:11449/232954Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:37:57.048590Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Pixelwise Time Series Retrieval in Phenological Studies
title Pixelwise Time Series Retrieval in Phenological Studies
spellingShingle Pixelwise Time Series Retrieval in Phenological Studies
Santos, Elisangela Silva
information retrieval
phenology
recurrence plot
time series retrieval
title_short Pixelwise Time Series Retrieval in Phenological Studies
title_full Pixelwise Time Series Retrieval in Phenological Studies
title_fullStr Pixelwise Time Series Retrieval in Phenological Studies
title_full_unstemmed Pixelwise Time Series Retrieval in Phenological Studies
title_sort Pixelwise Time Series Retrieval in Phenological Studies
author Santos, Elisangela Silva
author_facet Santos, Elisangela Silva
Alberton, Bruna [UNESP]
Morellato, Leonor Patricia [UNESP]
Da Silva Torres, Ricardo
author_role author
author2 Alberton, Bruna [UNESP]
Morellato, Leonor Patricia [UNESP]
Da Silva Torres, Ricardo
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual de Campinas (UNICAMP)
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Santos, Elisangela Silva
Alberton, Bruna [UNESP]
Morellato, Leonor Patricia [UNESP]
Da Silva Torres, Ricardo
dc.subject.por.fl_str_mv information retrieval
phenology
recurrence plot
time series retrieval
topic information retrieval
phenology
recurrence plot
time series retrieval
description The support of time series similarity searches might be crucial in phenology studies, in which long-term time series analysis based on the identification of similar and different phenological patterns shared by individuals belonging to different species is a widely common task. In this paper, we introduce the use of well-established Information Retrieval (IR) technologies in the search of time series. The solution comprises four main steps: extraction of an image-based time series representation; image content description to encode time series properties and patterns; textual signature extraction based on image content descriptions; and textual signature indexing using off-the-shelf IR approaches. In this paper, we demonstrate both the effectiveness and the efficiency of the proposed solution in time series retrieval problems related to the management of phenological data associated with near-surface vegetation images.
publishDate 2019
dc.date.none.fl_str_mv 2019-07-01
2022-04-30T22:28:33Z
2022-04-30T22:28:33Z
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/IGARSS.2019.8898112
International Geoscience and Remote Sensing Symposium (IGARSS), p. 6586-6589.
http://hdl.handle.net/11449/232954
10.1109/IGARSS.2019.8898112
2-s2.0-85077688255
url http://dx.doi.org/10.1109/IGARSS.2019.8898112
http://hdl.handle.net/11449/232954
identifier_str_mv International Geoscience and Remote Sensing Symposium (IGARSS), p. 6586-6589.
10.1109/IGARSS.2019.8898112
2-s2.0-85077688255
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv International Geoscience and Remote Sensing Symposium (IGARSS)
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 6586-6589
dc.source.none.fl_str_mv Scopus
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
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