Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data

Detalhes bibliográficos
Autor(a) principal: Nascimento Neto, Jose Nelson do
Data de Publicação: 2023
Outros Autores: Uchoa, Elenilton Bezerra
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/52684
Resumo: This work investigated the process of land use and land cover in the municipality of Itarema. It is located in the geographic coordinates of Latitude (S) 2º 55’ 13” and Longitude (W) 39º 54’ 54” in the northern region of the state of Ceará, with an area of 720.7 km² in the semi-arid region. The objective of this study was to analyze the changes in land use and land cover in the municipality of Itarema for the period from 2000 to 2020, from Landsat 5 and 8 series orbital remote sensing data to evaluate the evolutionary behavior of the landscape. The methodology used was the literary review in (Leite & Rosa 2012) and IBGE Land Use Technician Manual (2013). Technical procedures related to orbital images from the Landsat 5 and 8 series recorded respectively 2000 and 2020 were applied. Imaging treatment was performed with preprocessing and spectral bands, B5 - Medium infrared, B4 - Near infrared and B2 - Green was processed for Landsat 5 and B6 - SWIR-1, B5 - Near infrared and B4 - Red for Landsat 8 in ENVI 4.3. The classification supervised in the Semi-Automatic Plug-in was performed by the MAX-VER method and seven types of use were considered. The results point to a significant change in the typology of dense vegetation  from 52.84% in 2000 to a reduction of 25.71% in 2020, followed by the increase in degraded areas from 7.47% in 2000 to 16.03% in 2020. Final considerations, we highlight the importance of remote sensing in observations of landscape evolution and in the interpretation of the typology of use. We identified significant changes in the classes of degraded areas and dense vegetation, both associated supported by the change in the PIB  profile of the municipality.
id UFRJ-21_7fea3661e12a68d242fafa4ed3b86569
oai_identifier_str oai:ojs.pkp.sfu.ca:article/52684
network_acronym_str UFRJ-21
network_name_str Anuário do Instituto de Geociências (Online)
repository_id_str
spelling Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral DataRemote SensingSemiaridLandscapeThis work investigated the process of land use and land cover in the municipality of Itarema. It is located in the geographic coordinates of Latitude (S) 2º 55’ 13” and Longitude (W) 39º 54’ 54” in the northern region of the state of Ceará, with an area of 720.7 km² in the semi-arid region. The objective of this study was to analyze the changes in land use and land cover in the municipality of Itarema for the period from 2000 to 2020, from Landsat 5 and 8 series orbital remote sensing data to evaluate the evolutionary behavior of the landscape. The methodology used was the literary review in (Leite & Rosa 2012) and IBGE Land Use Technician Manual (2013). Technical procedures related to orbital images from the Landsat 5 and 8 series recorded respectively 2000 and 2020 were applied. Imaging treatment was performed with preprocessing and spectral bands, B5 - Medium infrared, B4 - Near infrared and B2 - Green was processed for Landsat 5 and B6 - SWIR-1, B5 - Near infrared and B4 - Red for Landsat 8 in ENVI 4.3. The classification supervised in the Semi-Automatic Plug-in was performed by the MAX-VER method and seven types of use were considered. The results point to a significant change in the typology of dense vegetation  from 52.84% in 2000 to a reduction of 25.71% in 2020, followed by the increase in degraded areas from 7.47% in 2000 to 16.03% in 2020. Final considerations, we highlight the importance of remote sensing in observations of landscape evolution and in the interpretation of the typology of use. We identified significant changes in the classes of degraded areas and dense vegetation, both associated supported by the change in the PIB  profile of the municipality.Universidade Federal do Rio de Janeiro2023-05-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/vnd.openxmlformats-officedocument.wordprocessingml.documenthttps://revistas.ufrj.br/index.php/aigeo/article/view/5268410.11137/1982-3908_2023_46_52684Anuário do Instituto de Geociências; v. 46 (2023)Anuário do Instituto de Geociências; Vol. 46 (2023)1982-39080101-9759reponame:Anuário do Instituto de Geociências (Online)instname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJenghttps://revistas.ufrj.br/index.php/aigeo/article/view/52684/pdfhttps://revistas.ufrj.br/index.php/aigeo/article/view/52684/38865https://revistas.ufrj.br/index.php/aigeo/article/view/52684/38893https://revistas.ufrj.br/index.php/aigeo/article/view/52684/39073Copyright (c) 2023 Anuário do Instituto de Geociênciasinfo:eu-repo/semantics/openAccessNascimento Neto, Jose Nelson doUchoa, Elenilton Bezerra2023-05-10T11:29:19Zoai:ojs.pkp.sfu.ca:article/52684Revistahttps://revistas.ufrj.br/index.php/aigeo/indexPUBhttps://revistas.ufrj.br/index.php/aigeo/oaianuario@igeo.ufrj.br||1982-39080101-9759opendoar:2023-05-10T11:29:19Anuário do Instituto de Geociências (Online) - Universidade Federal do Rio de Janeiro (UFRJ)false
dc.title.none.fl_str_mv Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data
title Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data
spellingShingle Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data
Nascimento Neto, Jose Nelson do
Remote Sensing
Semiarid
Landscape
title_short Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data
title_full Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data
title_fullStr Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data
title_full_unstemmed Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data
title_sort Analysis Land Use and Land Cover of the Municipality of Itarema-Ceará- Brazil based on Landsat Multispectral Data
author Nascimento Neto, Jose Nelson do
author_facet Nascimento Neto, Jose Nelson do
Uchoa, Elenilton Bezerra
author_role author
author2 Uchoa, Elenilton Bezerra
author2_role author
dc.contributor.author.fl_str_mv Nascimento Neto, Jose Nelson do
Uchoa, Elenilton Bezerra
dc.subject.por.fl_str_mv Remote Sensing
Semiarid
Landscape
topic Remote Sensing
Semiarid
Landscape
description This work investigated the process of land use and land cover in the municipality of Itarema. It is located in the geographic coordinates of Latitude (S) 2º 55’ 13” and Longitude (W) 39º 54’ 54” in the northern region of the state of Ceará, with an area of 720.7 km² in the semi-arid region. The objective of this study was to analyze the changes in land use and land cover in the municipality of Itarema for the period from 2000 to 2020, from Landsat 5 and 8 series orbital remote sensing data to evaluate the evolutionary behavior of the landscape. The methodology used was the literary review in (Leite & Rosa 2012) and IBGE Land Use Technician Manual (2013). Technical procedures related to orbital images from the Landsat 5 and 8 series recorded respectively 2000 and 2020 were applied. Imaging treatment was performed with preprocessing and spectral bands, B5 - Medium infrared, B4 - Near infrared and B2 - Green was processed for Landsat 5 and B6 - SWIR-1, B5 - Near infrared and B4 - Red for Landsat 8 in ENVI 4.3. The classification supervised in the Semi-Automatic Plug-in was performed by the MAX-VER method and seven types of use were considered. The results point to a significant change in the typology of dense vegetation  from 52.84% in 2000 to a reduction of 25.71% in 2020, followed by the increase in degraded areas from 7.47% in 2000 to 16.03% in 2020. Final considerations, we highlight the importance of remote sensing in observations of landscape evolution and in the interpretation of the typology of use. We identified significant changes in the classes of degraded areas and dense vegetation, both associated supported by the change in the PIB  profile of the municipality.
publishDate 2023
dc.date.none.fl_str_mv 2023-05-10
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://revistas.ufrj.br/index.php/aigeo/article/view/52684
10.11137/1982-3908_2023_46_52684
url https://revistas.ufrj.br/index.php/aigeo/article/view/52684
identifier_str_mv 10.11137/1982-3908_2023_46_52684
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.ufrj.br/index.php/aigeo/article/view/52684/pdf
https://revistas.ufrj.br/index.php/aigeo/article/view/52684/38865
https://revistas.ufrj.br/index.php/aigeo/article/view/52684/38893
https://revistas.ufrj.br/index.php/aigeo/article/view/52684/39073
dc.rights.driver.fl_str_mv Copyright (c) 2023 Anuário do Instituto de Geociências
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Anuário do Instituto de Geociências
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/vnd.openxmlformats-officedocument.wordprocessingml.document
application/vnd.openxmlformats-officedocument.wordprocessingml.document
application/vnd.openxmlformats-officedocument.wordprocessingml.document
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; v. 46 (2023)
Anuário do Instituto de Geociências; Vol. 46 (2023)
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||
_version_ 1797053535707201536