| 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 | 8JMKD3MGP3W/3KN34KE |
| Repositório | sid.inpe.br/plutao/2015/12.04.13.59 |
| Última Atualização | 2015:12.09.16.18.06 (UTC) administrator |
| Repositório de Metadados | sid.inpe.br/plutao/2015/12.04.13.59.31 |
| Última Atualização dos Metadados | 2018:06.04.23.25.52 (UTC) administrator |
| DOI | 10.3390/rs71114482 |
| ISSN | 2072-4292 |
| Rótulo | lattes: 2456184661855977 4 SchultzImFoSaLuAt:2015:SeSeCl |
| Chave de Citação | SchultzImFoSaLuAt:2015:SeSeCl |
| Título | Self-guided segmentation and classification of multi-temporal Landsat 8 images for crop type mapping in southeastern Brazil  |
| Ano | 2015 |
| Data de Acesso | 08 maio 2024 |
| Tipo de Trabalho | journal article |
| Tipo Secundário | PRE PI |
| Número de Arquivos | 1 |
| Tamanho | 5673 KiB |
| 2. Contextualização | |
| Autor | 1 Schultz, Bruno 2 Immitzer, Markus 3 Formaggio, Antônio Roberto 4 Sanches, Ieda Del Arco 5 Luiz, Alfredo José Barreto 6 Atzberger, Clement |
| Identificador de Curriculo | 1 2 3 8JMKD3MGP5W/3C9JGJQ |
| Grupo | 1 SER-SRE-SPG-INPE-MCTI-GOV-BR 2 3 DSR-OBT-INPE-MCTI-GOV-BR 4 DSR-OBT-INPE-MCTI-GOV-BR |
| Afiliação | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 University of Natural Resources and Life Sciences, Vienna (BOKU) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 Embrapa Meio Ambiente 6 University of Natural Resources and Life Sciences |
| Endereço de e-Mail do Autor | 1 2 markus.immitzer@boku.ac.at 3 formag@dsr.inpe.br 4 ieda@dsr.inpe.br 5 alfredo.luiz@embrapa.br 6 clement.atzberger@boku.ac.at |
| Revista | Remote Sensing |
| Volume | 7 |
| Número | 11 |
| Páginas | 14482-14508 |
| Nota Secundária | B3_GEOGRAFIA B3_ENGENHARIAS_I B4_GEOCIÊNCIAS B4_CIÊNCIAS_AMBIENTAIS B5_CIÊNCIAS_AGRÁRIAS_I |
| Histórico (UTC) | 2015-12-04 13:59:31 :: lattes -> administrator :: 2018-06-04 23:25:52 :: administrator -> simone :: 2015 |
| 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 | OBIA crop mapping Brazil multi-resolution segmentation OLI random forest |
| Resumo | Only well-chosen segmentation parameters ensure optimum results of object-based image analysis (OBIA). Manually defining suitable parameter sets can be a time-consuming approach, not necessarily leading to optimum results; the subjectivity of the manual approach is also obvious. For this reason, in supervised segmentation as proposed by Stefanski et al. (2013) one integrates the segmentation and classification tasks. The segmentation is optimized directly with respect to the subsequent classification. In this contribution, we build on this work and developed a fully autonomous workflow for supervised object-based classification, combining image segmentation and random forest (RF) classification. Starting from a fixed set of randomly selected and manually interpreted training samples, suitable segmentation parameters are automatically identified. A sub-tropical study site located in São Paulo State (Brazil) was used to evaluate the proposed approach. Two multi-temporal Landsat 8 image mosaics were used as input (from August 2013 and January 2014) together with training samples from field visits and VHR (RapidEye) photo-interpretation. Using four test sites of 15 × 15 km2 with manually interpreted crops as independent validation samples, we demonstrate that the approach leads to robust classification results. On these samples (pixel wise, n ≈ 1 million) an overall accuracy (OA) of 80% could be reached while classifying five classes: sugarcane, soybean, cassava, peanut and others. We found that the overall accuracy obtained from the four test sites was only marginally lower compared to the out-of-bag OA obtained from the training samples. Amongst the five classes, sugarcane and soybean were classified best, while cassava and peanut were often misclassified due to similarity in the spatio-temporal feature space and high within-class variabilities. Interestingly, misclassified pixels were in most cases correctly identified through the RF classification margin, which is produced as a by-product to the classification map. |
| Área | SRE |
| Arranjo 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Self-guided segmentation and... |
| Arranjo 2 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Self-guided segmentation and... |
| 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 | |
| URL dos dados | http://urlib.net/ibi/8JMKD3MGP3W/3KN34KE |
| URL dos dados zipados | http://urlib.net/zip/8JMKD3MGP3W/3KN34KE |
| Idioma | en |
| Arquivo Alvo | 1_schultz.pdf |
| Grupo de Usuários | administrator lattes simone |
| Grupo de Leitores | administrator simone |
| Visibilidade | shown |
| Política de Arquivamento | allowpublisher allowfinaldraft |
| Permissão de Atualização | não transferida |
| 5. Fontes relacionadas | |
| Repositório Espelho | urlib.net/www/2011/03.29.20.55 |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3ER446E 8JMKD3MGPCW/3F3NU5S |
| Lista de Itens Citando | sid.inpe.br/bibdigital/2013/10.18.22.34 2 sid.inpe.br/mtc-m21/2012/07.13.14.40.34 2 |
| Divulgação | WEBSCI; PORTALCAPES; COMPENDEX; SCOPUS. |
| Acervo Hospedeiro | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notas | |
| Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn lineage mark month nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readpermission rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Controle da descrição | |
| e-Mail (login) | simone |
| atualizar | |