River sediment yield classification using remote sensing imagery

Detalhes bibliográficos
Autor(a) principal: R. Pisani
Data de Publicação: 2017
Outros Autores: K. Costa, G. Rosa, D. Pereira, J. Papa, J. M. R. S. Tavares
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://repositorio-aberto.up.pt/handle/10216/102591
Resumo: The monitoring of water quality is essencial to the mankind, since we strongly depend on such resource for living and working. The presence of sediments in rivers usually indicates changes in the land use, which can affect the quality of water and the lifetime of hydroelectric power plants. In countries like Brazil, where more than 70% of the energy comes from the water, it is crucial to keep monitoring the sediment yield in rivers and lakes. In this work, we evaluate some stateof- the-art supervised pattern recognition techniques to classify different levels of sediments in Brazilian rivers using satellite images, as well as we make available an annotated dataset composed of two images to foster the related research.
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spelling River sediment yield classification using remote sensing imageryCiências Tecnológicas, Ciências da engenharia e tecnologiasTechnological sciences, Engineering and technologyThe monitoring of water quality is essencial to the mankind, since we strongly depend on such resource for living and working. The presence of sediments in rivers usually indicates changes in the land use, which can affect the quality of water and the lifetime of hydroelectric power plants. In countries like Brazil, where more than 70% of the energy comes from the water, it is crucial to keep monitoring the sediment yield in rivers and lakes. In this work, we evaluate some stateof- the-art supervised pattern recognition techniques to classify different levels of sediments in Brazilian rivers using satellite images, as well as we make available an annotated dataset composed of two images to foster the related research.2017-032017-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://repositorio-aberto.up.pt/handle/10216/102591eng10.1109/PRRS.2016.7867014R. PisaniK. CostaG. RosaD. PereiraJ. PapaJ. M. R. S. Tavaresinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T13:26:01Zoai:repositorio-aberto.up.pt:10216/102591Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:40:21.573173Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv River sediment yield classification using remote sensing imagery
title River sediment yield classification using remote sensing imagery
spellingShingle River sediment yield classification using remote sensing imagery
R. Pisani
Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
title_short River sediment yield classification using remote sensing imagery
title_full River sediment yield classification using remote sensing imagery
title_fullStr River sediment yield classification using remote sensing imagery
title_full_unstemmed River sediment yield classification using remote sensing imagery
title_sort River sediment yield classification using remote sensing imagery
author R. Pisani
author_facet R. Pisani
K. Costa
G. Rosa
D. Pereira
J. Papa
J. M. R. S. Tavares
author_role author
author2 K. Costa
G. Rosa
D. Pereira
J. Papa
J. M. R. S. Tavares
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv R. Pisani
K. Costa
G. Rosa
D. Pereira
J. Papa
J. M. R. S. Tavares
dc.subject.por.fl_str_mv Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
topic Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
description The monitoring of water quality is essencial to the mankind, since we strongly depend on such resource for living and working. The presence of sediments in rivers usually indicates changes in the land use, which can affect the quality of water and the lifetime of hydroelectric power plants. In countries like Brazil, where more than 70% of the energy comes from the water, it is crucial to keep monitoring the sediment yield in rivers and lakes. In this work, we evaluate some stateof- the-art supervised pattern recognition techniques to classify different levels of sediments in Brazilian rivers using satellite images, as well as we make available an annotated dataset composed of two images to foster the related research.
publishDate 2017
dc.date.none.fl_str_mv 2017-03
2017-03-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
format book
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://repositorio-aberto.up.pt/handle/10216/102591
url https://repositorio-aberto.up.pt/handle/10216/102591
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1109/PRRS.2016.7867014
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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