Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil)
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/S1982-21702016000200017 http://hdl.handle.net/11449/173158 |
Resumo: | The use of remote sensing focused on the determination of field samples is of great value to environmental studies, since the satellite images have attributes able to assess the spectral variability of water surface considering a wide area. Thus, this approach aims to define a stratified working method of selecting samples based on images variability in the visible and infrared wavelengths derived from Landsat-8/OLI sensor. The method relies on the use of raster data representing the standard deviation of a time series of images Landsat-8/OLI and then the automatic setting field points supported by the stratified random sampling. The choice of the image that yielded the selection of the samples was based on the greatest spectral variation component by means of Principal Component technique. As a result were obtained twenty representative points of a total of six spectrally similar classes created by using a Geographic Information System. |
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Repositório Institucional da UNESP |
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Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil)Sampling design in reservoirs based on landsat-8/OLI images: A case study in nova avanhandava reservoir (São Paulo state, Brazil)GeoprocessingRemote sensingSamplingThe use of remote sensing focused on the determination of field samples is of great value to environmental studies, since the satellite images have attributes able to assess the spectral variability of water surface considering a wide area. Thus, this approach aims to define a stratified working method of selecting samples based on images variability in the visible and infrared wavelengths derived from Landsat-8/OLI sensor. The method relies on the use of raster data representing the standard deviation of a time series of images Landsat-8/OLI and then the automatic setting field points supported by the stratified random sampling. The choice of the image that yielded the selection of the samples was based on the greatest spectral variation component by means of Principal Component technique. As a result were obtained twenty representative points of a total of six spectrally similar classes created by using a Geographic Information System.Faculdade de Ciências e Tecnologia Departamento de Cartografia Universidade Estadual Paulista - UNESP, Rua Roberto Simonsen, 305Sistema de Proteção da Amazônia Centro Regional de Belém - SIPAM/CR-BE, Av. Júlio César, 7060Faculdade de Ciências e Tecnologia Departamento de Cartografia Universidade Estadual Paulista - UNESP, Rua Roberto Simonsen, 305Universidade Estadual Paulista (Unesp)Centro Regional de Belém - SIPAM/CR-BERodrigues, Thanan Walesza Pequeno [UNESP]Guimarães, Ulisses Silva [UNESP]Rotta, Luiz Henrique Da Silva [UNESP]Watanabe, Fernanda Sayuri Yoshino [UNESP]Alcântara, Enner [UNESP]Imai, Nilton Nobuhiro [UNESP]2018-12-11T17:03:55Z2018-12-11T17:03:55Z2016-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article303-323application/pdfhttp://dx.doi.org/10.1590/S1982-21702016000200017Boletim de Ciencias Geodesicas, v. 22, n. 2, p. 303-323, 2016.1982-21701413-4853http://hdl.handle.net/11449/17315810.1590/S1982-21702016000200017S1982-217020160002003032-s2.0-84976646042S1982-21702016000200303.pdf298577110250533066913103944104900000-0003-0516-05670000-0002-8077-2865Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporBoletim de Ciencias Geodesicas0,188info:eu-repo/semantics/openAccess2024-06-18T15:01:26Zoai:repositorio.unesp.br:11449/173158Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462024-06-18T15:01:26Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil) Sampling design in reservoirs based on landsat-8/OLI images: A case study in nova avanhandava reservoir (São Paulo state, Brazil) |
title |
Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil) |
spellingShingle |
Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil) Rodrigues, Thanan Walesza Pequeno [UNESP] Geoprocessing Remote sensing Sampling |
title_short |
Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil) |
title_full |
Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil) |
title_fullStr |
Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil) |
title_full_unstemmed |
Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil) |
title_sort |
Delineamento amostral em reservatórios utilizando imagens landsat-8/OLI: Um estudo de caso no reservatório de nova avanhandava (estado de São Paulo, Brasil) |
author |
Rodrigues, Thanan Walesza Pequeno [UNESP] |
author_facet |
Rodrigues, Thanan Walesza Pequeno [UNESP] Guimarães, Ulisses Silva [UNESP] Rotta, Luiz Henrique Da Silva [UNESP] Watanabe, Fernanda Sayuri Yoshino [UNESP] Alcântara, Enner [UNESP] Imai, Nilton Nobuhiro [UNESP] |
author_role |
author |
author2 |
Guimarães, Ulisses Silva [UNESP] Rotta, Luiz Henrique Da Silva [UNESP] Watanabe, Fernanda Sayuri Yoshino [UNESP] Alcântara, Enner [UNESP] Imai, Nilton Nobuhiro [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Centro Regional de Belém - SIPAM/CR-BE |
dc.contributor.author.fl_str_mv |
Rodrigues, Thanan Walesza Pequeno [UNESP] Guimarães, Ulisses Silva [UNESP] Rotta, Luiz Henrique Da Silva [UNESP] Watanabe, Fernanda Sayuri Yoshino [UNESP] Alcântara, Enner [UNESP] Imai, Nilton Nobuhiro [UNESP] |
dc.subject.por.fl_str_mv |
Geoprocessing Remote sensing Sampling |
topic |
Geoprocessing Remote sensing Sampling |
description |
The use of remote sensing focused on the determination of field samples is of great value to environmental studies, since the satellite images have attributes able to assess the spectral variability of water surface considering a wide area. Thus, this approach aims to define a stratified working method of selecting samples based on images variability in the visible and infrared wavelengths derived from Landsat-8/OLI sensor. The method relies on the use of raster data representing the standard deviation of a time series of images Landsat-8/OLI and then the automatic setting field points supported by the stratified random sampling. The choice of the image that yielded the selection of the samples was based on the greatest spectral variation component by means of Principal Component technique. As a result were obtained twenty representative points of a total of six spectrally similar classes created by using a Geographic Information System. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01 2018-12-11T17:03:55Z 2018-12-11T17:03:55Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1590/S1982-21702016000200017 Boletim de Ciencias Geodesicas, v. 22, n. 2, p. 303-323, 2016. 1982-2170 1413-4853 http://hdl.handle.net/11449/173158 10.1590/S1982-21702016000200017 S1982-21702016000200303 2-s2.0-84976646042 S1982-21702016000200303.pdf 2985771102505330 6691310394410490 0000-0003-0516-0567 0000-0002-8077-2865 |
url |
http://dx.doi.org/10.1590/S1982-21702016000200017 http://hdl.handle.net/11449/173158 |
identifier_str_mv |
Boletim de Ciencias Geodesicas, v. 22, n. 2, p. 303-323, 2016. 1982-2170 1413-4853 10.1590/S1982-21702016000200017 S1982-21702016000200303 2-s2.0-84976646042 S1982-21702016000200303.pdf 2985771102505330 6691310394410490 0000-0003-0516-0567 0000-0002-8077-2865 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
Boletim de Ciencias Geodesicas 0,188 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
303-323 application/pdf |
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 |
repositoriounesp@unesp.br |
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1826303842464038912 |