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/3C63Q7P |
Repositório | dpi.inpe.br/plutao/2012/06.21.19.20 (acesso restrito) |
Última Atualização | 2012:08.10.14.20.44 (UTC) administrator |
Repositório de Metadados | dpi.inpe.br/plutao/2012/06.21.19.20.17 |
Última Atualização dos Metadados | 2018:06.05.00.01.46 (UTC) administrator |
DOI | 10.1016/j.rse.2012.04.011 |
ISSN | 0034-4257 |
Rótulo | lattes: 1958394372634693 5 VieiraFoReAtAgMe:2012:ObBaIm |
Chave de Citação | VieiraFoReAtAgMe:2012:ObBaIm |
Título | Object Based Image Analysis and Data Mining applied to a remotely sensed Landsat time-series to map sugarcane over large areas |
Projeto | CNPq 153208/2010-2, 142845/2011-6 and 304928/2011/9, FAPESP 2009/02037-3 |
Ano | 2012 |
Mês | Aug. |
Data de Acesso | 09 maio 2024 |
Tipo Secundário | PRE PI |
Número de Arquivos | 1 |
Tamanho | 1122 KiB |
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2. Contextualização | |
Autor | 1 Vieira, Matheus Alves 2 Formaggio, Antonio Roberto 3 Rennó, Camilo Daleles 4 Atzberger, Clement 5 Aguiar, Daniel Alves de 6 Mello, Marcio Pupin |
Identificador de Curriculo | 1 2 8JMKD3MGP5W/3C9JGJQ 3 8JMKD3MGP5W/3C9JGN2 |
Grupo | 1 DSR-OBT-INPE-MCTI-GOV-BR 2 DSR-OBT-INPE-MCTI-GOV-BR 3 DPI-OBT-INPE-MCTI-GOV-BR 4 5 DSR-OBT-INPE-MCTI-GOV-BR 6 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 University of Natural Resources and Life Sciences (BOKU), Institute of Surveying, Remote Sensing and Land Information (IVFL), Peter Jordan Strasse 82, Vienna, 1190, Austria 5 Instituto Nacional de Pesquisas Espaciais (INPE) 6 Instituto Nacional de Pesquisas Espaciais (INPE) |
Endereço de e-Mail do Autor | 1 2 formag@dsr.inpe.br 3 camilo@dpi.inpe.br 4 5 daniel@dsr.inpe.br |
Endereço de e-Mail | daniel@dsr.inpe.br |
Revista | Remote Sensing of Environment |
Volume | 123 |
Páginas | 553-562 |
Nota Secundária | A1_CIÊNCIAS_AGRÁRIAS_I A2_CIÊNCIAS_BIOLÓGICAS_I A1_ECOLOGIA_E_MEIO_AMBIENTE A2_ENGENHARIAS_I A1_GEOCIÊNCIAS A1_INTERDISCIPLINAR |
Histórico (UTC) | 2012-06-22 00:11:00 :: lattes -> administrator :: 2012 2012-07-19 19:23:01 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012 2012-08-14 17:39:34 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012 2012-08-20 11:29:15 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012 2012-08-30 12:27:17 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012 2012-09-28 22:35:16 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012 2012-12-21 18:30:04 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012 2018-06-05 00:01:46 :: administrator -> marciana :: 2012 |
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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 | Object Based Image Analysis (OBIA) Data Mining (DM) Sugarcane Time-series imagery Landsat Image segmentation |
Resumo | The aim of this research was to develop a methodology for contributing in the automation of sugarcane mapping over large areas, with time-series of remotely sensed imagery. To this end, two major techniques were combined: Object Based Image Analysis (OBIA) and Data Mining (DM). OBIA was used to represent the knowledge needed to map sugarcane, whereas DM was applied to generate the knowledge model. To derive the image objects, the segmentation algorithm implemented in Definiens Developer® was used. The data mining algorithm used was J48, which generates decision trees (DT) from a previously prepared training set. The study area comprises three municipalities located in the northwest of São Paulo state, all of which are good representatives of the agricultural conditions in the Southern and Southeastern regions of Brazil. A time series of Landsat TM and ETM+ images was acquired in order to represent the wide range of pattern variation along the sugarcane crop cycle. After training, the DT was applied to the Landsat time series, thus generating the desired thematic map with sugarcane ready to harvest. Classification accuracy was calculated over a set of 500 points not previously used during the training stage. Using error matrix analysis and Kappa statistics, tests for statistical significance were derived. The statistics indicated that the classification achieved an overall accuracy of 94% and a Kappa coefficient of 0.87. Results show that the combination of OBIA and DM techniques is very efficient and promising for the sugarcane classification process. |
Área | SRE |
Arranjo 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Object Based Image... |
Arranjo 2 | urlib.net > Fonds > Produção anterior à 2021 > DIDSR > Object Based Image... |
Conteúdo da Pasta doc | acessar |
Conteúdo da Pasta source | não têm arquivos |
Conteúdo da Pasta agreement | não têm arquivos |
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4. Condições de acesso e uso | |
Idioma | en |
Arquivo Alvo | Vieira_MA.pdf |
Grupo de Usuários | administrator lattes secretaria.cpa@dir.inpe.br |
Grupo de Leitores | administrator secretaria.cpa@dir.inpe.br |
Visibilidade | shown |
Política de Arquivamento | denypublisher allowfinaldraft24 |
Permissão de Leitura | deny from all and allow from 150.163 |
Permissão de Atualização | não transferida |
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5. Fontes relacionadas | |
Vinculação | Trabalho Vinculado à Tese/Dissertação |
Unidades Imediatamente Superiores | 8JMKD3MGPCW/3EQCCU5 8JMKD3MGPCW/3ER446E |
Lista de Itens Citando | sid.inpe.br/bibdigital/2013/09.09.15.05 2 |
Divulgação | WEBSCI; PORTALCAPES; MGA; COMPENDEX. |
Acervo Hospedeiro | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
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6. Notas | |
Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark mirrorrepository nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarytype typeofwork url |
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7. Controle da descrição | |
e-Mail (login) | marciana |
atualizar | |
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