Land use image classification through optimum-path forest clustering
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/IGARSS.2011.6049258 http://hdl.handle.net/11449/72802 |
Resumo: | Land 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. |
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Repositório Institucional da UNESP |
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Land use image classification through optimum-path forest clusteringLand usemean shiftoptimum-path forestunsupervised classificationK-meansLanduse classificationsMean shiftUnsupervised classificationGeologyRemote sensingLand 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.UNESP - Univ. Estadual Paulista Geosciences and Exact Sciences InstituteUNESP - Univ. Estadual Paulista Department of ComputingUNESP - Univ. Estadual Paulista Geosciences and Exact Sciences InstituteUNESP - Univ. Estadual Paulista Department of ComputingUniversidade Estadual Paulista (Unesp)Pisani, R. [UNESP]Riedel, P. [UNESP]Ferreira, M. [UNESP]Marques, M. [UNESP]Mizobe, R. [UNESP]Papa, J. [UNESP]2014-05-27T11:26:07Z2014-05-27T11:26:07Z2011-11-16info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject826-829http://dx.doi.org/10.1109/IGARSS.2011.6049258International Geoscience and Remote Sensing Symposium (IGARSS), p. 826-829.http://hdl.handle.net/11449/7280210.1109/IGARSS.2011.6049258WOS:0002974963001992-s2.0-80955164075Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Geoscience and Remote Sensing Symposium (IGARSS)info:eu-repo/semantics/openAccess2024-06-06T13:44:23Zoai:repositorio.unesp.br:11449/72802Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:04:45.817582Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Land use image classification through optimum-path forest clustering |
title |
Land use image classification through optimum-path forest clustering |
spellingShingle |
Land use image classification through optimum-path forest clustering Pisani, R. [UNESP] Land use mean shift optimum-path forest unsupervised classification K-means Landuse classifications Mean shift Unsupervised classification Geology Remote sensing |
title_short |
Land use image classification through optimum-path forest clustering |
title_full |
Land use image classification through optimum-path forest clustering |
title_fullStr |
Land use image classification through optimum-path forest clustering |
title_full_unstemmed |
Land use image classification through optimum-path forest clustering |
title_sort |
Land use image classification through optimum-path forest clustering |
author |
Pisani, R. [UNESP] |
author_facet |
Pisani, R. [UNESP] Riedel, P. [UNESP] Ferreira, M. [UNESP] Marques, M. [UNESP] Mizobe, R. [UNESP] Papa, J. [UNESP] |
author_role |
author |
author2 |
Riedel, P. [UNESP] Ferreira, M. [UNESP] Marques, M. [UNESP] Mizobe, R. [UNESP] Papa, J. [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Pisani, R. [UNESP] Riedel, P. [UNESP] Ferreira, M. [UNESP] Marques, M. [UNESP] Mizobe, R. [UNESP] Papa, J. [UNESP] |
dc.subject.por.fl_str_mv |
Land use mean shift optimum-path forest unsupervised classification K-means Landuse classifications Mean shift Unsupervised classification Geology Remote sensing |
topic |
Land use mean shift optimum-path forest unsupervised classification K-means Landuse classifications Mean shift Unsupervised classification Geology Remote sensing |
description |
Land 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. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-11-16 2014-05-27T11:26:07Z 2014-05-27T11:26:07Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/IGARSS.2011.6049258 International Geoscience and Remote Sensing Symposium (IGARSS), p. 826-829. http://hdl.handle.net/11449/72802 10.1109/IGARSS.2011.6049258 WOS:000297496300199 2-s2.0-80955164075 |
url |
http://dx.doi.org/10.1109/IGARSS.2011.6049258 http://hdl.handle.net/11449/72802 |
identifier_str_mv |
International Geoscience and Remote Sensing Symposium (IGARSS), p. 826-829. 10.1109/IGARSS.2011.6049258 WOS:000297496300199 2-s2.0-80955164075 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Geoscience and Remote Sensing Symposium (IGARSS) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
826-829 |
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_ |
1808129390234566656 |