A case study for a multitemporal segmentation approach in optical remote sensing images.

Detalhes bibliográficos
Autor(a) principal: COSTA, W.
Data de Publicação: 2018
Outros Autores: FONSECA, L., KÖRTING, T., SIMÕES, M., KUCHLER, P.
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1090733
Resumo: Continuous observations from remote sensors provide high temporal and spatial resolution imagery, and better remote sensing image segmentation techniques are mandatory for efficient analysis. Among them, one of the most applied segmentation techniques is the region growing algorithm. Within this context, this paper describes a study case for a multitemporal segmentation that adapts the traditional region growing technique. Our method aims to detect homogeneous regions in space and time observing a sequence of optical remote sensing images. Tests were conducted by considering the Dynamic Time Warping distance as the homogeneity criterion to grow regions. A case study on high temporal resolution for sequences of Landsat-8 vegetation indices products provided satisfactory outputs.
id EMBR_56da818f7da7fc8813cd9ac20a236cbd
oai_identifier_str oai:www.alice.cnptia.embrapa.br:doc/1090733
network_acronym_str EMBR
network_name_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository_id_str 2154
spelling A case study for a multitemporal segmentation approach in optical remote sensing images.Segmentação multitemporalDynamic Time WarpingProcessamento de imagemSistema de informação geográficaSensoriamento remotoContinuous observations from remote sensors provide high temporal and spatial resolution imagery, and better remote sensing image segmentation techniques are mandatory for efficient analysis. Among them, one of the most applied segmentation techniques is the region growing algorithm. Within this context, this paper describes a study case for a multitemporal segmentation that adapts the traditional region growing technique. Our method aims to detect homogeneous regions in space and time observing a sequence of optical remote sensing images. Tests were conducted by considering the Dynamic Time Warping distance as the homogeneity criterion to grow regions. A case study on high temporal resolution for sequences of Landsat-8 vegetation indices products provided satisfactory outputs.GEOProcessing 2018.WANDERSON COSTA, INPE; LEILA FONSECA, INPE; THALES KÖRTING, INPE; MARGARETH GONCALVES SIMOES, CNPS; PATRICK KUCHLER, UERJ; CIRAD.COSTA, W.FONSECA, L.KÖRTING, T.SIMÕES, M.KUCHLER, P.2018-04-20T01:10:39Z2018-04-20T01:10:39Z2018-04-1920182019-04-16T11:11:11ZArtigo em anais e proceedingsinfo:eu-repo/semantics/publishedVersionIn: INTERNATIONAL CONFERENCE ON ADVANCED GEOGRAPHIC INFORMATION SYSTEMS, APPLICATIONS, AND SERVICES, 10., 2018, Rome. Proceedings... Haifa: Israel Institute of Technology, 2018. p. 66-70.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1090733enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2018-04-20T01:10:46Zoai:www.alice.cnptia.embrapa.br:doc/1090733Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542018-04-20T01:10:46Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv A case study for a multitemporal segmentation approach in optical remote sensing images.
title A case study for a multitemporal segmentation approach in optical remote sensing images.
spellingShingle A case study for a multitemporal segmentation approach in optical remote sensing images.
COSTA, W.
Segmentação multitemporal
Dynamic Time Warping
Processamento de imagem
Sistema de informação geográfica
Sensoriamento remoto
title_short A case study for a multitemporal segmentation approach in optical remote sensing images.
title_full A case study for a multitemporal segmentation approach in optical remote sensing images.
title_fullStr A case study for a multitemporal segmentation approach in optical remote sensing images.
title_full_unstemmed A case study for a multitemporal segmentation approach in optical remote sensing images.
title_sort A case study for a multitemporal segmentation approach in optical remote sensing images.
author COSTA, W.
author_facet COSTA, W.
FONSECA, L.
KÖRTING, T.
SIMÕES, M.
KUCHLER, P.
author_role author
author2 FONSECA, L.
KÖRTING, T.
SIMÕES, M.
KUCHLER, P.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv WANDERSON COSTA, INPE; LEILA FONSECA, INPE; THALES KÖRTING, INPE; MARGARETH GONCALVES SIMOES, CNPS; PATRICK KUCHLER, UERJ; CIRAD.
dc.contributor.author.fl_str_mv COSTA, W.
FONSECA, L.
KÖRTING, T.
SIMÕES, M.
KUCHLER, P.
dc.subject.por.fl_str_mv Segmentação multitemporal
Dynamic Time Warping
Processamento de imagem
Sistema de informação geográfica
Sensoriamento remoto
topic Segmentação multitemporal
Dynamic Time Warping
Processamento de imagem
Sistema de informação geográfica
Sensoriamento remoto
description Continuous observations from remote sensors provide high temporal and spatial resolution imagery, and better remote sensing image segmentation techniques are mandatory for efficient analysis. Among them, one of the most applied segmentation techniques is the region growing algorithm. Within this context, this paper describes a study case for a multitemporal segmentation that adapts the traditional region growing technique. Our method aims to detect homogeneous regions in space and time observing a sequence of optical remote sensing images. Tests were conducted by considering the Dynamic Time Warping distance as the homogeneity criterion to grow regions. A case study on high temporal resolution for sequences of Landsat-8 vegetation indices products provided satisfactory outputs.
publishDate 2018
dc.date.none.fl_str_mv 2018-04-20T01:10:39Z
2018-04-20T01:10:39Z
2018-04-19
2018
2019-04-16T11:11:11Z
dc.type.driver.fl_str_mv Artigo em anais e proceedings
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv In: INTERNATIONAL CONFERENCE ON ADVANCED GEOGRAPHIC INFORMATION SYSTEMS, APPLICATIONS, AND SERVICES, 10., 2018, Rome. Proceedings... Haifa: Israel Institute of Technology, 2018. p. 66-70.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1090733
identifier_str_mv In: INTERNATIONAL CONFERENCE ON ADVANCED GEOGRAPHIC INFORMATION SYSTEMS, APPLICATIONS, AND SERVICES, 10., 2018, Rome. Proceedings... Haifa: Israel Institute of Technology, 2018. p. 66-70.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1090733
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
_version_ 1822721323154014208