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Tipo de ReferênciaJournal Article
Sitemtc-m21b.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34P/3MB5SR5
Repositóriosid.inpe.br/mtc-m21b/2016/08.25.17.11   (acesso restrito)
Última Atualização2017:01.16.15.07.35 simone
Metadadossid.inpe.br/mtc-m21b/2016/08.25.17.11.18
Última Atualização dos Metadados2018:06.04.02.41.04 administrator
DOI10.5194/isprsarchives-XLI-B7-883-2016
ISSN1682-1750
Chave de CitaçãoBrum-BastosRibPinKörFon:2016:ImEvCe
TítuloImprovement evaluation on ceramic roof extraction using WorldView-2 imagery and geographic data mining approach
Ano2016
MêsJuly
Data de Acesso23 abr. 2021
Tipo de Trabalhoconference paper
Número de Arquivos1
Tamanho1423 KiB
Área de contextualização
Autor1 Brum-Bastos, V. S.
2 Ribeiro, B. M. G.
3 Pinheiro, C. M. D.
4 Körting, Thales Sehn
5 Fonseca, Leila Maria Garcia
Identificador de Curriculo1
2
3
4
5 8JMKD3MGP5W/3C9JHLD
Grupo1
2
3
4 DPI-OBT-INPE-MCTI-GOV-BR
5 OBT-OBT-INPE-MCTI-GOV-BR
Afiliação1 University of St. Andrews
2 Universidade Federal do Rio Grande do Sul (UFRGS)
3 Universidade Federal do ABC (UFABC)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1
2
3
4 thales.korting@inpe.br
5 leila.fonseca@inpe.br
RevistaInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume41
Páginas883-889
Tipo SecundárioPRE PI
Histórico2016-08-25 17:12:05 :: simone -> administrator :: 2016
2016-08-26 19:42:25 :: administrator -> simone :: 2016
2016-12-22 16:44:18 :: simone -> administrator :: 2016
2017-01-09 13:59:30 :: administrator -> simone :: 2016
2017-01-16 15:07:35 :: simone -> administrator :: 2016
2018-06-04 02:41:04 :: administrator -> simone :: 2016
Área de conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteudoExternal Contribution
Tipo de Versãopublisher
Palavras-ChaveC4.5, Ceramic roof, Classification accuracy, Decision tree, GEOBIA, Geographical data mining, WorldView-2.
ResumoAdvances in geotechnologies and in remote sensing have improved analysis of urban environments. The new sensors are increasingly suited to urban studies, due to the enhancement in spatial, spectral and radiometric resolutions. Urban environments present high heterogeneity, which cannot be tackled using pixel-based approaches on high resolution images. Geographic Object-Based Image Analysis (GEOBIA) has been consolidated as a methodology for urban land use and cover monitoring; however, classification of high resolution images is still troublesome. This study aims to assess the improvement on ceramic roof classification using WorldView-2 images due to the increase of 4 new bands besides the standard "Blue-Green-Red-Near Infrared" bands. Our methodology combines GEOBIA, C4.5 classification tree algorithm, Monte Carlo simulation and statistical tests for classification accuracy. Two samples groups were considered: 1) eight multispectral and panchromatic bands, and 2) four multispectral and panchromatic bands, representing previous high-resolution sensors. The C4.5 algorithm generates a decision tree that can be used for classification; smaller decision trees are closer to the semantic networks produced by experts on GEOBIA, while bigger trees, are not straightforward to implement manually, but are more accurate. The choice for a big or small tree relies on the user's skills to implement it. This study aims to determine for what kind of user the addition of the 4 new bands might be beneficial: 1) the common user (smaller trees) or 2) a more skilled user with coding and/or data mining abilities (bigger trees). In overall the classification was improved by the addition of the four new bands for both types of users.
AreaSRE
Arranjo 1BDMCI > Fonds > Produção > DIDPI > Improvement evaluation on...
Arranjo 2BDMCI > Fonds > Produção > CGOBT > Improvement evaluation on...
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Grupo de Usuáriossimone
Grupo de Leitoresadministrator
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Visibilidadeshown
Permissão de Leituradeny from all and allow from 150.163
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Unidades Imediatamente Superiores8JMKD3MGPCW/3EQCCU5
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DivulgaçãoWEBSCI; PORTALCAPES; COMPENDEX.
Acervo Hospedeirosid.inpe.br/mtc-m21b/2013/09.26.14.25.20
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Notas3rd International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Congress, ISPRS 2016; Prague; Czech Republic; 12 -19 July 2016.
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