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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3K5JKMH
Repositorysid.inpe.br/mtc-m21b/2015/08.25.13.28
Metadata Repositorysid.inpe.br/mtc-m21b/2015/08.25.13.28.26
Metadata Last Update2018:06.04.02.55.38 (UTC) administrator
Secondary KeyINPE--PRE/
Citation KeyCarvalhoKuxFlorSilv:2015:GeObIm
TitleGeographic object-based image analysis (GEOBIA) and data mining for urban land use classification by blocks using WorldView-2 images
Year2015
Access Date2024, May 27
Secondary TypePRE CI
2. Context
Author1 Carvalho, Marcus
2 Kux, Hermann Johann Heinrich
3 Florenzano, Teresa Galotti
4 Silva, Gabriella
Resume Identifier1
2 8JMKD3MGP5W/3C9JHCD
Group1
2 DSR-OBT-INPE-MCTI-GOV-BR
3 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1 Universidade Federal Fluminense (UFF)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Universidade Federal do Rio de Janeiro (UFRJ)
Author e-Mail Address1
2 hermann@ltid.inpe.br
3 teresa@ltid.inpe.br
Conference NameInternational Cartographic Conference, 27
Conference LocationRio de Janeiro, RJ
Date23-28 Aug.
History (UTC)2015-08-25 13:28:26 :: simone -> administrator ::
2018-06-04 02:55:38 :: administrator -> simone :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsGeographic object-based image analysis
Data mining
Urban land use by blocks
AbstractThe objective of this study is to develop and evaluate a methodology for the analysis of WorldView-2 images based on Geographic Object-Based Image Analysis (GEOBIA) and Data Mining, to classify urban land use per block. The area under study is a section at the western part of São Paulo Metropolitan Region. Mapping land use per urban block is an important information source for managers and decision makers in urban areas. Among the land cover classes considered in this work, seven were used by the São Paulo Municipality in the official maps. Objects located within the blocks are helpful to characterize these areas. So, in order to analyze the context and the relationship among classes for the elaboration of land use mapping per block, a classification procedure was adopted previously done with good accuracy considering a lower hierarchical level (sub-objects) at the level of blocks (super-objects). The steps followed were: selection and sample collection at the blocks to train the classifier, choice of attributes to be analyzed by the data mining algorithm, generation and implementation of a decision tree using the DEFINIENS Developer software, for the classification of the WorldView-2 image. It is concluded that the use of the OBIA paradigm and Data Mining techniques were helpful for mapping urban land use. The Kappa index was 0.7050 and the global precision 0.7556.
AreaSRE
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Geographic object-based image...
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Reader Groupadministrator
simone
Visibilityshown
Read Permissionallow from all
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3ER446E
Citing Item List
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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