You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72802
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPisani, R.-
dc.contributor.authorRiedel, P.-
dc.contributor.authorFerreira, M.-
dc.contributor.authorMarques, M.-
dc.contributor.authorMizobe, R.-
dc.contributor.authorPapa, J.-
dc.date.accessioned2014-05-27T11:26:07Z-
dc.date.accessioned2016-10-25T18:35:28Z-
dc.date.available2014-05-27T11:26:07Z-
dc.date.available2016-10-25T18:35:28Z-
dc.date.issued2011-11-16-
dc.identifierhttp://dx.doi.org/10.1109/IGARSS.2011.6049258-
dc.identifier.citationInternational Geoscience and Remote Sensing Symposium (IGARSS), p. 826-829.-
dc.identifier.urihttp://hdl.handle.net/11449/72802-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72802-
dc.description.abstractLand use classification has been paramount in the last years, since we can identify illegal land use and also to monitor deforesting areas. Although one can find several research works in the literature that address this problem, we propose here the land use recognition by means of Optimum-Path Forest Clustering (OPF), which has never been applied to this context up to date. Experiments among Optimum-Path Forest, Mean Shift and K-Means demonstrated the robustness of OPF for automatic land use classification of images obtained by CBERS-2B and Ikonos-2 satellites. © 2011 IEEE.en
dc.format.extent826-829-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectLand use-
dc.subjectmean shift-
dc.subjectoptimum-path forest-
dc.subjectunsupervised classification-
dc.subjectK-means-
dc.subjectLanduse classifications-
dc.subjectMean shift-
dc.subjectUnsupervised classification-
dc.subjectGeology-
dc.subjectRemote sensing-
dc.titleLand use image classification through optimum-path forest clusteringen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationUNESP - Univ. Estadual Paulista Geosciences and Exact Sciences Institute-
dc.description.affiliationUNESP - Univ. Estadual Paulista Department of Computing-
dc.description.affiliationUnespUNESP - Univ. Estadual Paulista Geosciences and Exact Sciences Institute-
dc.description.affiliationUnespUNESP - Univ. Estadual Paulista Department of Computing-
dc.identifier.doi10.1109/IGARSS.2011.6049258-
dc.identifier.wosWOS:000297496300199-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofInternational Geoscience and Remote Sensing Symposium (IGARSS)-
dc.identifier.scopus2-s2.0-80955164075-
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.