| 1. Identificação | |
| Tipo de Referência | Artigo em Revista Científica (Journal Article) |
| Site | mtc-m16d.sid.inpe.br |
| Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identificador | 8JMKD3MGP7W/3E9KQ65 |
| Repositório | sid.inpe.br/mtc-m19/2013/06.11.01.17 (acesso restrito) |
| Última Atualização | 2013:07.12.14.19.39 (UTC) administrator |
| Repositório de Metadados | sid.inpe.br/mtc-m19/2013/06.11.01.17.17 |
| Última Atualização dos Metadados | 2020:10.01.15.58.04 (UTC) administrator |
| DOI | 10.1016/j.rse.2012.10.035 |
| ISSN | 0034-4257 |
| Rótulo | isi |
| Chave de Citação | ArnesenSiHeNoRuChMc:2013:MoFlEx |
| Título | Monitoring flood extent in the lower Amazon River floodplain using ALOS/PALSAR ScanSAR images  |
| Ano | 2013 |
| Mês | Mar. |
| Data de Acesso | 05 maio 2024 |
| Tipo de Trabalho | journal article |
| Tipo Secundário | PRE PI |
| Número de Arquivos | 1 |
| Tamanho | 1446 KiB |
| 2. Contextualização | |
| Autor | 1 Arnesen, Allan Saddi 2 Silva, Thiago Sanna Freire 3 Hess, Laura L. 4 Novo, Evlyn Márcia Leão de Moraes 5 Rudorff, Conrado M. 6 Chapman, Bruce D. 7 McDonald, Kyle C. |
| Identificador de Curriculo | 1 2 3 4 8JMKD3MGP5W/3C9JH39 |
| Grupo | 1 2 DSR-OBT-INPE-MCTI-GOV-BR 3 4 DSR-OBT-INPE-MCTI-GOV-BR |
| Afiliação | 1 Inst Nacl Pesquisas Espaciais, Div Sensoriamento Remoto, BR-12201970 Sao Jose Dos Campos, Brazil. 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Univ Calif Santa Barbara, Earth Res Inst, Santa Barbara, CA 93106 USA. 4 Inst Nacl Pesquisas Espaciais, Div Sensoriamento Remoto, BR-12201970 Sao Jose Dos Campos, Brazil. 5 Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA 93106 USA. 6 CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA. 7 CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA.; CUNY City Coll, Dept Earth & Atmospher Sci, CUNY Environm Crossrd Initiat, New York, NY 10031 USA.; CUNY City Coll, CUNY CREST Inst, New York, NY 10031 USA. |
| Endereço de e-Mail do Autor | 1 2 thiago@ltid.inpe.br 3 4 evlyn@ltid.inpe.br |
| Endereço de e-Mail | marcelo.pazos@inpe.br |
| Revista | Remote Sensing of Environment |
| Volume | 130 |
| Páginas | 51-61 |
| Nota Secundária | A1 A1 A1 A1 A1 A1 A1 |
| Histórico (UTC) | 2020-10-01 15:58:04 :: administrator -> marcelo.pazos@inpe.br :: 2013 |
| 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 Multi-temporal analysis Incidence angle Wetlands Synthetic aperture radar Kyoto & Carbon Initiative |
| Resumo | The Amazon River floodplain is subject to large seasonal variations in water level and flood extent, due to the large size and low relief of the basin, and the large amount of precipitation in the region. Synthetic Aperture Radar (SAR) data can be used to map flooded area in these wetlands, given its ability to provide continuous information without being heavily affected by cloud cover. As part of JAXA's Kyoto & Carbon Initiative, extensive wide-swath, multi-temporal SAR coverage of the Amazon basin has been obtained using the ScanSAR mode of ALOS PALSAR This study presents a method for monitoring flood extent variation using ALOS ScanSAR images, tested at the Curuai Lake floodplain, in the lower Amazon River, Brazil. Twelve ScanSAR scenes were acquired between 2006 and 2010, including seven during the 2007 hydrological year. Water level records, field photographs, optical images (Landsat-5/TM and MODIS/Ferra and Aqua) and topographic data were used as auxiliary information. A data mining algorithm allowed the implementation of a hierarchical, object-based classification algorithm, able to map land cover types and flooding status in the study area for all available dates. land cover based on the entire time series (classification levels 1 and 2) had overall accuracies of 90\\% and 83\\%, respectively. Level 3 classifications (one map per image date) were validated only for the lowest and highest water stages, with overall accuracies of 76\\% and 78\\%, respectively. Total flood extent (Level 4) was mapped with 84\\% and 94\\% accuracies, for the low and high water stages, respectively. Regression models were fitted between mapped flooded area and water levels at the Curuai gauge to predict flood extent. A polynomial model had R-2=0.95 (p<0.05) and an overall root mean square error (RMSE) of 241 km(2), while a logistic model had R-2=0.98 (p<0.05) and RMSE = 127 km(2). (C) 2012 Elsevier Inc. All rights reserved. |
| Área | SRE |
| Arranjo | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Monitoring flood extent... |
| 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 | 1-s2.0-S0034425712004257-main.pdf |
| Grupo de Usuários | administrator marcelo.pazos@inpe.br marciana self-uploading-INPE-MCTI-GOV-BR |
| Grupo de Leitores | administrator marcelo.pazos@inpe.br marciana |
| Visibilidade | shown |
| Política de Arquivamento | denypublisher allowfinaldraft24 |
| Permissão de Leitura | deny from all and allow from 150.163 |
| Permissão de Atualização | não transferida |
| 5. Fontes relacionadas | |
| Repositório Espelho | iconet.com.br/banon/2006/11.26.21.31 |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3ER446E |
| Lista de Itens Citando | sid.inpe.br/mtc-m21/2012/07.13.14.45.43 1 |
| Divulgação | WEBSCI; PORTALCAPES; COMPENDEX; SCOPUS. |
| Acervo Hospedeiro | sid.inpe.br/mtc-m19@80/2009/08.21.17.02 |
| 6. Notas | |
| Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Controle da descrição | |
| e-Mail (login) | marcelo.pazos@inpe.br |
| atualizar | |