| 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/3MTP6AL |
| Repositório | sid.inpe.br/plutao/2016/12.06.01.24 (acesso restrito) |
| Última Atualização | 2016:12.12.12.03.03 (UTC) lattes |
| Repositório de Metadados | sid.inpe.br/plutao/2016/12.06.01.24.52 |
| Última Atualização dos Metadados | 2018:06.04.23.26.30 (UTC) administrator |
| DOI | 10.1109/JSTARS.2016.2594133 |
| ISSN | 1939-1404 2151-1535 |
| Rótulo | lattes: 9840759640842299 2 NegriDutrFreiLu:2016:ExCaAL |
| Chave de Citação | NegriDutrFreiLu:2016:ExCaAL |
| Título | Exploring the capability of ALOS PALSAR L-band fully polarimetric data for land cover classification in tropical environments  |
| Ano | 2016 |
| Mês | Dec. |
| Data de Acesso | 26 abr. 2024 |
| Tipo de Trabalho | journal article |
| Tipo Secundário | PRE PI |
| Número de Arquivos | 1 |
| Tamanho | 2561 KiB |
| 2. Contextualização | |
| Autor | 1 Negri, Rogerio Galante 2 Dutra, Luciano Vieira 3 Freitas, Corina da Costa 4 Lu, Dengsheng |
| Identificador de Curriculo | 1 2 8JMKD3MGP5W/3C9JHMA |
| Grupo | 1 2 DPI-OBT-INPE-MCTI-GOV-BR 3 DPI-OBT-INPE-MCTI-GOV-BR |
| Afiliação | 1 Universidade Estadual Paulista (UNESP) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Michigan State University |
| Endereço de e-Mail do Autor | 1 rogerio.negri@ict.unesp.br 2 luciano.dutra@inpe.br 3 corina@dpi.inpe.br 4 ludengsh@msu.edu |
| Revista | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Volume | 9 |
| Número | 12 |
| Páginas | 5369-5384 |
| Histórico (UTC) | 2016-12-06 01:24:52 :: lattes -> administrator :: 2016-12-12 11:59:31 :: administrator -> lattes :: 2016 2016-12-12 12:03:04 :: lattes -> administrator :: 2016 2018-06-04 23:26:30 :: administrator -> simone :: 2016 |
| 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 | Analise de Imagens Radar de Abertura Sintética Amazonia Amazon assessment image classification polarimetric synthetic aperture radar (PolSAR) scenarios synthetic aperture radar (SAR) |
| Resumo | Among different applications using synthetic aperture radar (SAR) data, land cover classification of rain forest areas has been investigated. Previous results showed that L-band is more appropriate for such applications. However, SAR images have limited discriminability for mapping large sets of classes compared with optical imagery. The objective of this study was to carry out an analysis about the discriminative capability of an L-band fully polarimetric SAR complex image, compared to the possible subsets of polarizations in amplitude/intensity, for mapping land cover classes in Amazon regions. Two case studies using ALOS PALSAR L-band fully polarimetric images over Brazilian Amazon regions were considered. Several thematic classes, organized into scenarios, were considered for each case study. These scenarios represent distinct classification tasks with variated complexities. Performing a simultaneous analysis of different scenarios is a distinct way to assess the discriminative capability offered by a particular image. A methodology to organize thematic classes into scenarios is proposed in this study. The maximum likelihood classifier (MLC), with specific distributions for SAR data, and support vector machine were considered in this study. The iterated conditional modes algorithm was adopted to incorporate the contextual information in both methods. Considering a kappa coefficient equal to 0.8 as an acceptable minimum, the experiments show that none subset of polarization or fully polarimetric image allows performing discrimination between forest and regeneration types; single-polarized HV data provide acceptable results when the classification problem deals with the discrimination of a few classes; depending on the classification scenario, the dual-polarized HH+HV image produces similar results when compared to multipolarized (i.e., HH+HV+VV) data; in turn, if the MLC method is adopted, multipolarized data may produce close or statistically indifferent classification results compared to those produced with the use of fully polarimetric data. |
| Área | SRE |
| Arranjo | Exploring the capability... |
| 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 | pt |
| Arquivo Alvo | negri_exploring.pdf |
| Grupo de Usuários | lattes |
| Grupo de Leitores | administrator lattes |
| Visibilidade | shown |
| Política de Arquivamento | denypublisher allowfinaldraft |
| Permissão de Leitura | deny from all and allow from 150.163 |
| Permissão de Atualização | não transferida |
| 5. Fontes relacionadas | |
| Repositório Espelho | urlib.net/www/2011/03.29.20.55 |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3EQCCU5 |
| Lista de Itens Citando | sid.inpe.br/bibdigital/2013/09.09.15.05 1 |
| Divulgação | WEBSCI; IEEEXplore. |
| Acervo Hospedeiro | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notas | |
| Notas | Setores de Atividade: Pesquisa e desenvolvimento científico. |
| Campos Vazios | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn lineage mark nextedition orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Controle da descrição | |
| e-Mail (login) | simone |
| atualizar | |
