CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/218341 |
Resumo: | The knowledge of the dynamics of a landscape in a region is an important factor in regional and local planning. The classification and analysis of images from remote orbital sensors became an important tool in the acquisition of information for land use mapping. The objective of this research was to evaluate changes in land use in the buffer zone of State Forest Edmundo Navarro de Andrade (FEENA), located in Rio Claro / SP, taking the years 1995, 2005 and 2015 as the time frame. Classifications of different types of land uses were carried out based on the remote sensing image transfer method. It was found that FEENA's buffer zone has undergone major changes over the years, mainly due to the presence of sugarcane monoculture, in addition to the creation and expansion of neighborhoods in the municipality. Finally, the adopted methods were obtained from the error matrix and the calculation of the Kappa index, which presented the result of 80% accuracy in the classification, provided within the level established by the consulted theoretical references. The result is considered a performance with strong agreement, proving the accuracy of the maps produced. |
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CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHODLand UseGeoprocessingState Forest Edmundo Navarro De AndradeThe knowledge of the dynamics of a landscape in a region is an important factor in regional and local planning. The classification and analysis of images from remote orbital sensors became an important tool in the acquisition of information for land use mapping. The objective of this research was to evaluate changes in land use in the buffer zone of State Forest Edmundo Navarro de Andrade (FEENA), located in Rio Claro / SP, taking the years 1995, 2005 and 2015 as the time frame. Classifications of different types of land uses were carried out based on the remote sensing image transfer method. It was found that FEENA's buffer zone has undergone major changes over the years, mainly due to the presence of sugarcane monoculture, in addition to the creation and expansion of neighborhoods in the municipality. Finally, the adopted methods were obtained from the error matrix and the calculation of the Kappa index, which presented the result of 80% accuracy in the classification, provided within the level established by the consulted theoretical references. The result is considered a performance with strong agreement, proving the accuracy of the maps produced.Univ Estadual Paulista UNESP, Inst Geociencias & Ciencias Exatas, Geog, Sao Paulo, SP, BrazilUniv Estado Minas Gerais, Unidade Frutal, Dept Ciencias Exatas & Terra, Belo Horizonte, MG, BrazilUniv Estadual Paulista UNESP, Inst Geociencias & Ciencias Exatas, Geog, Sao Paulo, SP, BrazilUniv Federal Mato GrossoUniversidade Estadual Paulista (UNESP)Universidade Federal de Minas Gerais (UFMG)Diotto, Marina Gama [UNESP]Silva Fuzzo, Daniela Fernanda da2022-04-28T17:20:31Z2022-04-28T17:20:31Z2021-08-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article132-148Revista Geoaraguaia. Barra Do Garcas: Univ Federal Mato Grosso, v. 11, p. 132-148, 2021.1809-094Xhttp://hdl.handle.net/11449/218341WOS:000692191900007Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporRevista Geoaraguaiainfo:eu-repo/semantics/openAccess2022-04-28T17:20:31Zoai:repositorio.unesp.br:11449/218341Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:43:58.903706Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD |
title |
CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD |
spellingShingle |
CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD Diotto, Marina Gama [UNESP] Land Use Geoprocessing State Forest Edmundo Navarro De Andrade |
title_short |
CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD |
title_full |
CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD |
title_fullStr |
CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD |
title_full_unstemmed |
CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD |
title_sort |
CONTRIBUTIONS TO THE MAPPING AND CLASSIFICATION OF LAND USE THROUGH SEGMENTATION METHOD |
author |
Diotto, Marina Gama [UNESP] |
author_facet |
Diotto, Marina Gama [UNESP] Silva Fuzzo, Daniela Fernanda da |
author_role |
author |
author2 |
Silva Fuzzo, Daniela Fernanda da |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Universidade Federal de Minas Gerais (UFMG) |
dc.contributor.author.fl_str_mv |
Diotto, Marina Gama [UNESP] Silva Fuzzo, Daniela Fernanda da |
dc.subject.por.fl_str_mv |
Land Use Geoprocessing State Forest Edmundo Navarro De Andrade |
topic |
Land Use Geoprocessing State Forest Edmundo Navarro De Andrade |
description |
The knowledge of the dynamics of a landscape in a region is an important factor in regional and local planning. The classification and analysis of images from remote orbital sensors became an important tool in the acquisition of information for land use mapping. The objective of this research was to evaluate changes in land use in the buffer zone of State Forest Edmundo Navarro de Andrade (FEENA), located in Rio Claro / SP, taking the years 1995, 2005 and 2015 as the time frame. Classifications of different types of land uses were carried out based on the remote sensing image transfer method. It was found that FEENA's buffer zone has undergone major changes over the years, mainly due to the presence of sugarcane monoculture, in addition to the creation and expansion of neighborhoods in the municipality. Finally, the adopted methods were obtained from the error matrix and the calculation of the Kappa index, which presented the result of 80% accuracy in the classification, provided within the level established by the consulted theoretical references. The result is considered a performance with strong agreement, proving the accuracy of the maps produced. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-08-01 2022-04-28T17:20:31Z 2022-04-28T17:20:31Z |
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 |
Revista Geoaraguaia. Barra Do Garcas: Univ Federal Mato Grosso, v. 11, p. 132-148, 2021. 1809-094X http://hdl.handle.net/11449/218341 WOS:000692191900007 |
identifier_str_mv |
Revista Geoaraguaia. Barra Do Garcas: Univ Federal Mato Grosso, v. 11, p. 132-148, 2021. 1809-094X WOS:000692191900007 |
url |
http://hdl.handle.net/11449/218341 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
Revista Geoaraguaia |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
132-148 |
dc.publisher.none.fl_str_mv |
Univ Federal Mato Grosso |
publisher.none.fl_str_mv |
Univ Federal Mato Grosso |
dc.source.none.fl_str_mv |
Web of Science 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 |
|
_version_ |
1808129110233317376 |