Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Revista Geama |
Texto Completo: | https://www.journals.ufrpe.br/index.php/geama/article/view/1369 |
Resumo: | Through the use of geotechnologies many surveys can be performed with data processing as geographical and environmental variables, resulting in new information and products and providing a detailed study about an specific area. This paper’s objective is present a case study example where visual classification appears as an opportunity for mapping heterogeneous areas, especially in agricultural zones occupied by small rural properties classified as family. This mapping type presents advantages to the automatic classifiers, since the heterogeneity of small areas can cause pixels miscellany, damaging the classification results. This study was performed in Salto do Lontra’s watershed, located in Paraná’s southwestern, Brazil. Images from Google Earth, obtained in 2014, were used for a visual classification, with 8 regions of interest (ROIs). For a supervised classification Landsat-8 images were used, path/row 223/78, acquired in 02/12/2013. The classifier applied was Spectral Angle Mapper (SAM) with 5 ROIs. Using such type of technologies, what is expected is that these can provide a broader view over environmental reality, allowing the recognition of different surface features and enabling a correct land management based on adequate information. |
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Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícolageographical areageoreferenced informationland usemanagement toolsThrough the use of geotechnologies many surveys can be performed with data processing as geographical and environmental variables, resulting in new information and products and providing a detailed study about an specific area. This paper’s objective is present a case study example where visual classification appears as an opportunity for mapping heterogeneous areas, especially in agricultural zones occupied by small rural properties classified as family. This mapping type presents advantages to the automatic classifiers, since the heterogeneity of small areas can cause pixels miscellany, damaging the classification results. This study was performed in Salto do Lontra’s watershed, located in Paraná’s southwestern, Brazil. Images from Google Earth, obtained in 2014, were used for a visual classification, with 8 regions of interest (ROIs). For a supervised classification Landsat-8 images were used, path/row 223/78, acquired in 02/12/2013. The classifier applied was Spectral Angle Mapper (SAM) with 5 ROIs. Using such type of technologies, what is expected is that these can provide a broader view over environmental reality, allowing the recognition of different surface features and enabling a correct land management based on adequate information.Geama Journal - Environmental SciencesRevista Geama2017-06-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.journals.ufrpe.br/index.php/geama/article/view/1369Geama Journal - Environmental Sciences; Volume 3, Número 1 (2017): Revista Geama; 5-9Revista Geama; Volume 3, Número 1 (2017): Revista Geama; 5-92447-0740reponame:Revista Geamainstname:Universidade Federal Rural de Pernambuco (UFRPE)instacron:UFRPEporhttps://www.journals.ufrpe.br/index.php/geama/article/view/1369/1300Copyright (c) 2017 Revista Geamainfo:eu-repo/semantics/openAccessWrublack, Suzana CostaMercante, EriveltoCorrea, Marcus MetriPrudente, Victor Hugo RohdenSilva, Jefferson Luiz GonçalvesVilas Boas, Marcio Antonio2017-07-31T10:46:08Zoai:ojs.10.0.7.8:article/1369Revistahttps://www.journals.ufrpe.br/index.php/geamaPUBhttps://www.journals.ufrpe.br/index.php/geama/oaijosemachado@ufrpe.br2447-07402447-0740opendoar:2017-07-31T10:46:08Revista Geama - Universidade Federal Rural de Pernambuco (UFRPE)false |
dc.title.none.fl_str_mv |
Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola |
title |
Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola |
spellingShingle |
Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola Wrublack, Suzana Costa geographical area georeferenced information land use management tools |
title_short |
Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola |
title_full |
Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola |
title_fullStr |
Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola |
title_full_unstemmed |
Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola |
title_sort |
Geotechnologies in mapping on land use and cover in agricultural watershed | Geotecnologias no mapeamento do uso da terra e cobertura na bacia hidrográfica agrícola |
author |
Wrublack, Suzana Costa |
author_facet |
Wrublack, Suzana Costa Mercante, Erivelto Correa, Marcus Metri Prudente, Victor Hugo Rohden Silva, Jefferson Luiz Gonçalves Vilas Boas, Marcio Antonio |
author_role |
author |
author2 |
Mercante, Erivelto Correa, Marcus Metri Prudente, Victor Hugo Rohden Silva, Jefferson Luiz Gonçalves Vilas Boas, Marcio Antonio |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Wrublack, Suzana Costa Mercante, Erivelto Correa, Marcus Metri Prudente, Victor Hugo Rohden Silva, Jefferson Luiz Gonçalves Vilas Boas, Marcio Antonio |
dc.subject.por.fl_str_mv |
geographical area georeferenced information land use management tools |
topic |
geographical area georeferenced information land use management tools |
description |
Through the use of geotechnologies many surveys can be performed with data processing as geographical and environmental variables, resulting in new information and products and providing a detailed study about an specific area. This paper’s objective is present a case study example where visual classification appears as an opportunity for mapping heterogeneous areas, especially in agricultural zones occupied by small rural properties classified as family. This mapping type presents advantages to the automatic classifiers, since the heterogeneity of small areas can cause pixels miscellany, damaging the classification results. This study was performed in Salto do Lontra’s watershed, located in Paraná’s southwestern, Brazil. Images from Google Earth, obtained in 2014, were used for a visual classification, with 8 regions of interest (ROIs). For a supervised classification Landsat-8 images were used, path/row 223/78, acquired in 02/12/2013. The classifier applied was Spectral Angle Mapper (SAM) with 5 ROIs. Using such type of technologies, what is expected is that these can provide a broader view over environmental reality, allowing the recognition of different surface features and enabling a correct land management based on adequate information. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-06-10 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.journals.ufrpe.br/index.php/geama/article/view/1369 |
url |
https://www.journals.ufrpe.br/index.php/geama/article/view/1369 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://www.journals.ufrpe.br/index.php/geama/article/view/1369/1300 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2017 Revista Geama info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2017 Revista Geama |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Geama Journal - Environmental Sciences Revista Geama |
publisher.none.fl_str_mv |
Geama Journal - Environmental Sciences Revista Geama |
dc.source.none.fl_str_mv |
Geama Journal - Environmental Sciences; Volume 3, Número 1 (2017): Revista Geama; 5-9 Revista Geama; Volume 3, Número 1 (2017): Revista Geama; 5-9 2447-0740 reponame:Revista Geama instname:Universidade Federal Rural de Pernambuco (UFRPE) instacron:UFRPE |
instname_str |
Universidade Federal Rural de Pernambuco (UFRPE) |
instacron_str |
UFRPE |
institution |
UFRPE |
reponame_str |
Revista Geama |
collection |
Revista Geama |
repository.name.fl_str_mv |
Revista Geama - Universidade Federal Rural de Pernambuco (UFRPE) |
repository.mail.fl_str_mv |
josemachado@ufrpe.br |
_version_ |
1809218600057176064 |