You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72193
Full metadata record
DC FieldValueLanguage
dc.contributor.authorEstevam, Eliane A.-
dc.contributor.authorSilva, Erivaldo A.-
dc.date.accessioned2014-05-27T11:25:25Z-
dc.date.accessioned2016-10-25T18:33:15Z-
dc.date.available2014-05-27T11:25:25Z-
dc.date.available2016-10-25T18:33:15Z-
dc.date.issued2010-12-01-
dc.identifierhttp://www.ufrgs.br/igeo/pesquisas/37-2.html-
dc.identifier.citationPesquisas em Geociencias, v. 37, n. 2, p. 133-142, 2010.-
dc.identifier.issn1518-2398-
dc.identifier.issn1807-9806-
dc.identifier.urihttp://hdl.handle.net/11449/72193-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72193-
dc.description.abstractThe growth of large cities is usually accelerated and disorganized, which causes social, economical and infrastructural conflicts and frequently, occupation in illegal areas. For a better administration of these areas, the public manager needs information about their location. This information can be obtained through land utilization and land cover maps, where orbital images of remote sensing are used as one of the most traditional sources of data. In this context, the present work tested the applicability of the object-based classification to categorize two slum areas, taking into account the structure of the streets, size of the huts, distance between the houses, among other parameters. These area combinations of physical aspects were analyzed using the image IKONOS II and the software eCognition. Slum areas tend to be, to the contrary of the planned areas, disarranged, with narrow streets, small houses built with a variety of materials and without definition of blocks. The results of land cover classification for slum areas are encouraging because they are accurate and little ambiguous in the classification process. Thus, it would allow its utilization by urban managers.en
dc.format.extent133-142-
dc.language.isopor-
dc.sourceScopus-
dc.subjecteCognition-
dc.subjectIKONOS II images-
dc.subjectObject-based classification-
dc.subjectSlums-
dc.titleClassificação de áreas de favelas a partir de imagens IKONOS: Viabilidade de uso de uma abordagem orientada a objetopt
dc.title.alternativeClassification of slum areas using ikonos images: Viability of using the object-based classification approachen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationDepartamento de Cartografia Faculdade de Ciências e Tecnologia Universidade Estadual Paulista, Rua Roberto Simonsen, 305, CEP 19.060-900, Presidente Prudente, São Paulo-
dc.description.affiliationUnespDepartamento de Cartografia Faculdade de Ciências e Tecnologia Universidade Estadual Paulista, Rua Roberto Simonsen, 305, CEP 19.060-900, Presidente Prudente, São Paulo-
dc.rights.accessRightsAcesso aberto-
dc.identifier.file2-s2.0-79851498497.pdf-
dc.relation.ispartofPesquisas em Geociencias-
dc.identifier.scopus2-s2.0-79851498497-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

There are no files associated with this item.
 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.