| 1. Identificação | |
| Tipo de Referência | Artigo em Revista Científica (Journal Article) |
| Site | plutao.sid.inpe.br |
| Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identificador | J8LNKAN8RW/3C63QEE |
| Repositório | dpi.inpe.br/plutao/2012/06.21.19.23 (acesso restrito) |
| Última Atualização | 2012:08.10.12.43.11 (UTC) administrator |
| Repositório de Metadados | dpi.inpe.br/plutao/2012/06.21.19.23.57 |
| Última Atualização dos Metadados | 2018:06.05.00.01.46 (UTC) administrator |
| DOI | 10.1080/01431161.2012.675451 |
| ISSN | 0143-1161 |
| Rótulo | lattes: 3233696672067020 5 PinhoFonKorAlmKux:2012:LaClIn |
| Chave de Citação | PinhoFonKörAlmKux:2012:LaClIn |
| Título | Land-cover classification of an intra-urban environment using high-resolution images and object-based image analysis  |
| Ano | 2012 |
| Mês | Oct. |
| Data de Acesso | 25 abr. 2024 |
| Tipo Secundário | PRE PI |
| Número de Arquivos | 1 |
| Tamanho | 3073 KiB |
| 2. Contextualização | |
| Autor | 1 Pinho, Carolina Moutinho Duque 2 Fonseca, Leila Maria Garcia 3 Körting, Thales Sehn 4 Almeida, Cláudia Maria de 5 Kux, Hermann Johann Heinrich |
| Identificador de Curriculo | 1 2 8JMKD3MGP5W/3C9JHLD 3 4 8JMKD3MGP5W/3C9JGS3 5 8JMKD3MGP5W/3C9JHCD |
| Grupo | 1 DPI-OBT-INPE-MCTI-GOV-BR 2 DPI-OBT-INPE-MCTI-GOV-BR 3 DPI-OBT-INPE-MCTI-GOV-BR 4 DSR-OBT-INPE-MCTI-GOV-BR 5 DSR-OBT-INPE-MCTI-GOV-BR |
| Afiliação | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Instituto Nacional de Pesquisas Espaciais (INPE) |
| Endereço de e-Mail do Autor | 1 2 3 4 almeida@dsr.inpe.br 5 hermann@ltid.inpe.br |
| Endereço de e-Mail | hermann@ltid.inpe.br |
| Revista | International Journal of Remote Sensing |
| Volume | 33 |
| Número | 19 |
| Páginas | 5973-5995 |
| Nota Secundária | B3_BIOTECNOLOGIA A1_CIÊNCIA_DA_COMPUTAÇÃO A2_CIÊNCIAS_AGRÁRIAS_I B2_CIÊNCIAS_BIOLÓGICAS_I B1_ECOLOGIA_E_MEIO_AMBIENTE B1_ENGENHARIAS_I B2_ENGENHARIAS_II B1_ENGENHARIAS_III A2_ENGENHARIAS_IV B1_GEOCIÊNCIAS A1_GEOGRAFIA A2_INTERDISCIPLINAR B1_ODONTOLOGIA A1_PLANEJAMENTO_URBANO_E_REGIONAL_/_DEMOGRAFIA A2_SAÚDE_COLETIVA |
| Histórico (UTC) | 2012-06-22 00:11:00 :: lattes -> administrator :: 2012 2012-07-19 18:01:58 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012 2012-08-10 12:43:11 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012 2012-10-06 09:16:07 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012 2013-01-18 14:31:20 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012 2018-06-05 00:01:46 :: administrator -> marciana :: 2012 |
| 3. Conteúdo e estrutura | |
| É a matriz ou uma cópia? | é a matriz |
| Estágio do Conteúdo | concluido |
| Transferível | 1 |
| Tipo do Conteúdo | External Contribution |
| Tipo de Versão | publisher |
| Palavras-Chave | Análise de imagens orientada a objeto - OBIA Classificação de imagens baseada em conhecimento IKONOS QUICKBIRD Planejamento Urbano São José dos Campos-SP |
| Resumo | Detailed, up-to-date information on intra-urban land cover is important for urban planning and management. Differentiation between permeable and impermeable land, for instance, provides data for surface run-off estimates and flood prevention, whereas identification of vegetated areas enables studies of urban micro-climates. In place of maps, high-resolution images, such as those from the satellites IKONOS II, Quickbird, Orbview and WorldView II, can be used after processing. Object-based image analysis (OBIA) is a well-established method for classifying high-resolution images of urban areas. Despite the large number of previous studies of OBIA in the context of intra-urban analysis, there are many issues in this area that are still open to discussion and resolution. Intra-urban analysis using OBIA can be lengthy and complex because of the processing difficulties related to image segmentation, the large number of object attributes to be resolved and the many different methods needed to classify various image objects. To overcome these issues, we performed an experiment consisting of land-cover mapping based on an OBIA approach using an IKONOS II image of a southern sector of São José dos Campos city (covering an area of 12 km2 with 50 neighbourhoods), which is located in São Paulo State in south-eastern Brazil. This area contains various occupation and land-use patterns, and it therefore contains a wide range of intra-urban targets. To generate the land-cover map, we proposed an OBIA-based processing framework that combines multi-resolution segmentation, data mining and hierarchical network techniques. The intra-urban land-cover map was then evaluated through an object-based error matrix, and classification accuracy indices were obtained. The final classification, with 11 classes, achieved a global accuracy of 71.91%. |
| Área | SRE |
| Arranjo 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Land-cover classification of... |
| Arranjo 2 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Land-cover classification of... |
| Conteúdo da Pasta doc | acessar |
| Conteúdo da Pasta source | não têm arquivos |
| Conteúdo da Pasta agreement | não têm arquivos |
| 4. Condições de acesso e uso | |
| Idioma | en |
| Arquivo Alvo | Pinho_CMD.pdf |
| Grupo de Usuários | administrator lattes secretaria.cpa@dir.inpe.br |
| Visibilidade | shown |
| Política de Arquivamento | denypublisher denyfinaldraft12 |
| Permissão de Leitura | deny from all and allow from 150.163 |
| Permissão de Atualização | não transferida |
| 5. Fontes relacionadas | |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3EQCCU5 8JMKD3MGPCW/3ER446E |
| Divulgação | WEBSCI; PORTALCAPES; MGA; COMPENDEX. |
| Acervo Hospedeiro | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notas | |
| Notas | Informações Adicionais: Detailed, up-to-date information on intra-urban land cover is important for urban planning and management. Differentiation between permeable and impermeable land, for instance, provides data for surface run-off and flood prevention, whereas identification of vegetated areas enables studies of urban micro-climates. In place of maps, high-resolution images, such as those from IKONOS II, Quickbird-2, OrbView and WorldView-2, can be used after processing. Object-based image analysis (OBIA) is a well-established method for classifying high-resolution images of urban areas. Despite the large number of previous studies of OBIA in the context of intra-urban analysis, there are many issues in this area that are still open to discussion and solution. Intra-urban analysis using OBIA can be lengthy and complex because of the processing difficulties related to image segmentation, the large number of object attributes to be resolved and the many different methods needed to classify various image objects. To overcome these issues, we performed an experiment consisting of land cover mapping based on an OBIA approach, using an IKONOS II image of a southern sector of São José dos Campos city (covering an area of 12 km2 with 50 neighbourhoods), which is located in São Paulo State, in SE Brazil. This area contains various occupation and land-use patterns, and it therefore contains a wide range of intra-urban targets. To generate the land-cover map, we proposed an OBIA-based processing framework that combines multi-resolution segmentation, data mining and hierarchical network techniques. The intra-urban land-cover map was then evaluated through an object-based error matrix, and classification accuracy indices were obtained. The final classification, with 11 classes, achieved a global accuracy of 71.91%.. |
| Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark mirrorrepository nextedition orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url |
| 7. Controle da descrição | |
| e-Mail (login) | marciana |
| atualizar | |