The Use of Remote Sensing Indices for Land Cover Change Detection
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Anuário do Instituto de Geociências (Online) |
Texto Completo: | https://revistas.ufrj.br/index.php/aigeo/article/view/30051 |
Resumo: | Remote sensing technology has been applied to monitor anthropogenic changes in the landscape that produce impacts on natural resources, such as environmental degradation, changes in the hydrological cycle and in ecosystems structure and functioning. As digital change detection may be a difficult task to perform, this study proposes a simple and logical technique to display land cover changes using Landsat imagery. Open source geoprocessing tools were used to acquire information for mapping changes on the land surface. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) derived from satellite images of four dates between 1984 and 2016 were used in RGB composites. The method was used to map gains and losses of vegetation cover and liquid water content in a spatiotemporal scale. The results indicate that this change detection method can effectively reflect the variations occurred over the years. Although both indices have similar responses, NDWI may provide opposite information to NDVI in certain areas, such as in wetlands and riparian zones, presenting wetness losses even in places that exhibit gains in vegetation. This method has applicability to other regions for deriving historical changes. |
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Anuário do Instituto de Geociências (Online) |
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The Use of Remote Sensing Indices for Land Cover Change DetectionLandsat; Multi-temporal; NDVI; NDWI; QGIS; Time-seriesRemote sensing technology has been applied to monitor anthropogenic changes in the landscape that produce impacts on natural resources, such as environmental degradation, changes in the hydrological cycle and in ecosystems structure and functioning. As digital change detection may be a difficult task to perform, this study proposes a simple and logical technique to display land cover changes using Landsat imagery. Open source geoprocessing tools were used to acquire information for mapping changes on the land surface. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) derived from satellite images of four dates between 1984 and 2016 were used in RGB composites. The method was used to map gains and losses of vegetation cover and liquid water content in a spatiotemporal scale. The results indicate that this change detection method can effectively reflect the variations occurred over the years. Although both indices have similar responses, NDWI may provide opposite information to NDVI in certain areas, such as in wetlands and riparian zones, presenting wetness losses even in places that exhibit gains in vegetation. This method has applicability to other regions for deriving historical changes.Universidade Federal do Rio de JaneiroDourado, Gustavo FacincaniMotta, Jaíza SantosFilho, Antonio Conceição ParanhosScott, David FindlayGabas, Sandra Garcia2019-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufrj.br/index.php/aigeo/article/view/3005110.11137/2019_2_72_85Anuário do Instituto de Geociências; Vol 42, No 2 (2019); 72-85Anuário do Instituto de Geociências; Vol 42, No 2 (2019); 72-851982-39080101-9759reponame:Anuário do Instituto de Geociências (Online)instname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJenghttps://revistas.ufrj.br/index.php/aigeo/article/view/30051/16959Copyright (c) 2019 Anuário do Instituto de Geociênciashttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccess2019-12-10T15:04:16Zoai:www.revistas.ufrj.br:article/30051Revistahttps://revistas.ufrj.br/index.php/aigeo/indexPUBhttps://revistas.ufrj.br/index.php/aigeo/oaianuario@igeo.ufrj.br||1982-39080101-9759opendoar:2019-12-10T15:04:16Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)false |
dc.title.none.fl_str_mv |
The Use of Remote Sensing Indices for Land Cover Change Detection |
title |
The Use of Remote Sensing Indices for Land Cover Change Detection |
spellingShingle |
The Use of Remote Sensing Indices for Land Cover Change Detection Dourado, Gustavo Facincani Landsat; Multi-temporal; NDVI; NDWI; QGIS; Time-series |
title_short |
The Use of Remote Sensing Indices for Land Cover Change Detection |
title_full |
The Use of Remote Sensing Indices for Land Cover Change Detection |
title_fullStr |
The Use of Remote Sensing Indices for Land Cover Change Detection |
title_full_unstemmed |
The Use of Remote Sensing Indices for Land Cover Change Detection |
title_sort |
The Use of Remote Sensing Indices for Land Cover Change Detection |
author |
Dourado, Gustavo Facincani |
author_facet |
Dourado, Gustavo Facincani Motta, Jaíza Santos Filho, Antonio Conceição Paranhos Scott, David Findlay Gabas, Sandra Garcia |
author_role |
author |
author2 |
Motta, Jaíza Santos Filho, Antonio Conceição Paranhos Scott, David Findlay Gabas, Sandra Garcia |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
|
dc.contributor.author.fl_str_mv |
Dourado, Gustavo Facincani Motta, Jaíza Santos Filho, Antonio Conceição Paranhos Scott, David Findlay Gabas, Sandra Garcia |
dc.subject.none.fl_str_mv |
|
dc.subject.por.fl_str_mv |
Landsat; Multi-temporal; NDVI; NDWI; QGIS; Time-series |
topic |
Landsat; Multi-temporal; NDVI; NDWI; QGIS; Time-series |
description |
Remote sensing technology has been applied to monitor anthropogenic changes in the landscape that produce impacts on natural resources, such as environmental degradation, changes in the hydrological cycle and in ecosystems structure and functioning. As digital change detection may be a difficult task to perform, this study proposes a simple and logical technique to display land cover changes using Landsat imagery. Open source geoprocessing tools were used to acquire information for mapping changes on the land surface. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) derived from satellite images of four dates between 1984 and 2016 were used in RGB composites. The method was used to map gains and losses of vegetation cover and liquid water content in a spatiotemporal scale. The results indicate that this change detection method can effectively reflect the variations occurred over the years. Although both indices have similar responses, NDWI may provide opposite information to NDVI in certain areas, such as in wetlands and riparian zones, presenting wetness losses even in places that exhibit gains in vegetation. This method has applicability to other regions for deriving historical changes. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-01 |
dc.type.none.fl_str_mv |
|
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://revistas.ufrj.br/index.php/aigeo/article/view/30051 10.11137/2019_2_72_85 |
url |
https://revistas.ufrj.br/index.php/aigeo/article/view/30051 |
identifier_str_mv |
10.11137/2019_2_72_85 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.ufrj.br/index.php/aigeo/article/view/30051/16959 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2019 Anuário do Instituto de Geociências http://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2019 Anuário do Instituto de Geociências http://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal do Rio de Janeiro |
publisher.none.fl_str_mv |
Universidade Federal do Rio de Janeiro |
dc.source.none.fl_str_mv |
Anuário do Instituto de Geociências; Vol 42, No 2 (2019); 72-85 Anuário do Instituto de Geociências; Vol 42, No 2 (2019); 72-85 1982-3908 0101-9759 reponame:Anuário do Instituto de Geociências (Online) instname:Universidade Federal do Rio de Janeiro (UFRJ) instacron:UFRJ |
instname_str |
Universidade Federal do Rio de Janeiro (UFRJ) |
instacron_str |
UFRJ |
institution |
UFRJ |
reponame_str |
Anuário do Instituto de Geociências (Online) |
collection |
Anuário do Instituto de Geociências (Online) |
repository.name.fl_str_mv |
Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ) |
repository.mail.fl_str_mv |
anuario@igeo.ufrj.br|| |
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1797053543944814592 |