Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy

Detalhes bibliográficos
Autor(a) principal: Campos, Sérgio [UNESP]
Data de Publicação: 2007
Outros Autores: Piroli, Edson Luís [UNESP], Zimback, Célia Regina Lopes [UNESP], Rodrigues, João Batista Tolentino [UNESP]
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://200.145.140.50/ojs1/viewarticle.php?id=233&layout=abstract
http://hdl.handle.net/11449/69584
Resumo: Informatics evolution presently offers the possibility of new technique and methodology development for studies in all human knowledge areas. In addition, the present personal computer capacity of handling a large volume of data makes the creation and application of new analysis tools easy. This paper aimed the application of a fuzzy partition matrix to analyze data obtained from the Landsat 5 TMN sensor, in order to elaborate the supervised classification of land use in Arroio das Pombas microbasin in Botucatu, SP, Brazil. It was possible that one single training area present input in more than one covering class due to weight attribution at the signature creation moment. A change in the classification result was also observed when compared to maximum likelihood classification, mainly when related to bigger uniformity and better class edges classification.
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spelling Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzyAnalysis of soil use in a microbasin using a fuzzy partition matrixFuzzy partition matrixSatellite imageSupervised classificationData reductionFuzzy systemsLand useMaximum likelihoodPersonal computingSatellite imagerySoilsfuzzy mathematicsimage analysisland useLandsat thematic mappermaximum likelihood analysissatellite dataBotucatuBrazilSao Paulo [Brazil]South AmericaInformatics evolution presently offers the possibility of new technique and methodology development for studies in all human knowledge areas. In addition, the present personal computer capacity of handling a large volume of data makes the creation and application of new analysis tools easy. This paper aimed the application of a fuzzy partition matrix to analyze data obtained from the Landsat 5 TMN sensor, in order to elaborate the supervised classification of land use in Arroio das Pombas microbasin in Botucatu, SP, Brazil. It was possible that one single training area present input in more than one covering class due to weight attribution at the signature creation moment. A change in the classification result was also observed when compared to maximum likelihood classification, mainly when related to bigger uniformity and better class edges classification.Departamento de Engenharia Rural Faculdade de Ciências Agronômicas Universidade Estadual Paulista, Botucatu, SPCampus Experimental de Rosana Universidade Estadual Paulista, Rosana, SPDepartamento de Ciências do Solo Faculdade de Ciências Agronômicas Universidade Estadual Paulista, Botucatu, SPDepartamento de Engenharia Rural Faculdade de Ciências Agronômicas Universidade Estadual Paulista, Botucatu, SPCampus Experimental de Rosana Universidade Estadual Paulista, Rosana, SPDepartamento de Ciências do Solo Faculdade de Ciências Agronômicas Universidade Estadual Paulista, Botucatu, SPUniversidade Estadual Paulista (Unesp)Campos, Sérgio [UNESP]Piroli, Edson Luís [UNESP]Zimback, Célia Regina Lopes [UNESP]Rodrigues, João Batista Tolentino [UNESP]2014-05-27T11:22:26Z2014-05-27T11:22:26Z2007-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article216-224application/pdfhttp://200.145.140.50/ojs1/viewarticle.php?id=233&layout=abstractIrriga, v. 12, n. 2, p. 216-224, 2007.1413-78951808-3765http://hdl.handle.net/11449/695842-s2.0-345481422662-s2.0-34548142266.pdf31602026256885600000-0002-3350-2651Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporIrriga0,283info:eu-repo/semantics/openAccess2024-04-30T19:29:53Zoai:repositorio.unesp.br:11449/69584Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:55:29.184643Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy
Analysis of soil use in a microbasin using a fuzzy partition matrix
title Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy
spellingShingle Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy
Campos, Sérgio [UNESP]
Fuzzy partition matrix
Satellite image
Supervised classification
Data reduction
Fuzzy systems
Land use
Maximum likelihood
Personal computing
Satellite imagery
Soils
fuzzy mathematics
image analysis
land use
Landsat thematic mapper
maximum likelihood analysis
satellite data
Botucatu
Brazil
Sao Paulo [Brazil]
South America
title_short Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy
title_full Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy
title_fullStr Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy
title_full_unstemmed Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy
title_sort Avaliação do uso da terra em micro̧bacia utilizando uma matriz de partição fuzzy
author Campos, Sérgio [UNESP]
author_facet Campos, Sérgio [UNESP]
Piroli, Edson Luís [UNESP]
Zimback, Célia Regina Lopes [UNESP]
Rodrigues, João Batista Tolentino [UNESP]
author_role author
author2 Piroli, Edson Luís [UNESP]
Zimback, Célia Regina Lopes [UNESP]
Rodrigues, João Batista Tolentino [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Campos, Sérgio [UNESP]
Piroli, Edson Luís [UNESP]
Zimback, Célia Regina Lopes [UNESP]
Rodrigues, João Batista Tolentino [UNESP]
dc.subject.por.fl_str_mv Fuzzy partition matrix
Satellite image
Supervised classification
Data reduction
Fuzzy systems
Land use
Maximum likelihood
Personal computing
Satellite imagery
Soils
fuzzy mathematics
image analysis
land use
Landsat thematic mapper
maximum likelihood analysis
satellite data
Botucatu
Brazil
Sao Paulo [Brazil]
South America
topic Fuzzy partition matrix
Satellite image
Supervised classification
Data reduction
Fuzzy systems
Land use
Maximum likelihood
Personal computing
Satellite imagery
Soils
fuzzy mathematics
image analysis
land use
Landsat thematic mapper
maximum likelihood analysis
satellite data
Botucatu
Brazil
Sao Paulo [Brazil]
South America
description Informatics evolution presently offers the possibility of new technique and methodology development for studies in all human knowledge areas. In addition, the present personal computer capacity of handling a large volume of data makes the creation and application of new analysis tools easy. This paper aimed the application of a fuzzy partition matrix to analyze data obtained from the Landsat 5 TMN sensor, in order to elaborate the supervised classification of land use in Arroio das Pombas microbasin in Botucatu, SP, Brazil. It was possible that one single training area present input in more than one covering class due to weight attribution at the signature creation moment. A change in the classification result was also observed when compared to maximum likelihood classification, mainly when related to bigger uniformity and better class edges classification.
publishDate 2007
dc.date.none.fl_str_mv 2007-04-01
2014-05-27T11:22:26Z
2014-05-27T11:22:26Z
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://200.145.140.50/ojs1/viewarticle.php?id=233&layout=abstract
Irriga, v. 12, n. 2, p. 216-224, 2007.
1413-7895
1808-3765
http://hdl.handle.net/11449/69584
2-s2.0-34548142266
2-s2.0-34548142266.pdf
3160202625688560
0000-0002-3350-2651
url http://200.145.140.50/ojs1/viewarticle.php?id=233&layout=abstract
http://hdl.handle.net/11449/69584
identifier_str_mv Irriga, v. 12, n. 2, p. 216-224, 2007.
1413-7895
1808-3765
2-s2.0-34548142266
2-s2.0-34548142266.pdf
3160202625688560
0000-0002-3350-2651
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv Irriga
0,283
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 216-224
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
_version_ 1808129473860599808

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