1. Identificação | |
Tipo de Referência | Artigo em Revista Científica (Journal Article) |
Site | mtc-m21c.sid.inpe.br |
Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identificador | 8JMKD3MGP3W34R/42SP22H |
Repositório | sid.inpe.br/mtc-m21c/2020/07.20.11.22 (acesso restrito) |
Última Atualização | 2020:07.20.11.22.02 (UTC) simone |
Repositório de Metadados | sid.inpe.br/mtc-m21c/2020/07.20.11.22.02 |
Última Atualização dos Metadados | 2022:01.04.01.35.15 (UTC) administrator |
DOI | 10.1007/s10668-019-00442-0 |
ISSN | 1387-585X |
Chave de Citação | SimioniGuaNasRuiBel:2020:InMuAn |
Título | Integration of multi‑sensor analysis and decision tree for evaluation of dual and quad‑Pol SAR in L‑ and C‑bands applied for marsh delineation |
Ano | 2020 |
Mês | Aug. |
Data de Acesso | 13 maio 2024 |
Tipo de Trabalho | journal article |
Tipo Secundário | PRE PI |
Número de Arquivos | 1 |
Tamanho | 2415 KiB |
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2. Contextualização | |
Autor | 1 Simioni, João Paulo Delapasse 2 Guasselli, Laurindo Antonio 3 Nascimento, Victor Fernandez 4 Ruiz, Luís Fernando Chimelo 5 Belloli, Tassia Fraga |
ORCID | 1 0000-0001-7426-4584 |
Grupo | 1 2 3 CST-CST-SESPG-INPE-MCTIC-GOV-BR |
Afiliação | 1 Universidade Federal do Rio Grande do Sul (UFRGS) 2 Universidade Federal do Rio Grande do Sul (UFRGS) 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Universidade Federal do Rio Grande do Sul (UFRGS) 5 Universidade Federal do Rio Grande do Sul (UFRGS) |
Endereço de e-Mail do Autor | 1 joao.delapasse@ufrgs.br 2 3 victorfnascimento@gmail.com |
Revista | Environment Development and Sustainability |
Volume | 22 |
Número | 6 |
Páginas | 5603-5620 |
Histórico (UTC) | 2020-07-20 11:22:34 :: simone -> administrator :: 2020 2022-01-04 01:35:15 :: administrator -> simone :: 2020 |
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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 | Data mining Hydromorphic soils Polarization Wetlands |
Resumo | Marsh is a wetland type characterized by hydromorphic soils, herbaceous vegetation, aquatic and emergent vegetation; usually, the apparent water surface does not exceed 25% of the area. Multi-polarized active remote sensors with different frequencies have characteristics that make them ideal for mapping and delineating marsh areas since they provide information on canopy roughness, vegetation moisture and amount of biomass. Therefore, the main objective of this study is to develop a method based on multi-frequency radar satellites images to delineate marsh areas using decision tree classification. In order to reach this objective, we sought to answer the following questions: (1) Are L-band SAR images more efficient for marshes delineation than C-band SAR images? (2) Is multi-sensor (L and C-band) integration more accurate for marsh areas delineation than a single sensor? and (3) What are the most efficient channels for marshes delineation? Our findings showed that L-band images present greater proportion correct (PC) for marshes delineation compared to C-band images. However, the greatest PC was found using integration of Alos Palsar 1 and Sentinel 1 satellites images, reaching more than 72% of correctness. Regarding the polarization importance to Alos Palsar 1 image, HVVH presented the highest importance, with 29%, followed by VH and HV polarizations, both with 28%. For Sentinel 1 image, the most important polarization was VH, with 22%, followed by VV + VH that presented 20%. HVVH polarization was the most important in Alos and Sentinel images integration, with 35%, followed by Alos Palsar HV and VH, with 34 and 33%, respectively. Thus, we concluded that the method based on SAR multi-frequency data integration used in this study can be easily applied by other researchers interested in marsh delineation since the radar images used are freely available and can be processed and manipulated in free GIS software. |
Área | CST |
Conteúdo da Pasta doc | acessar |
Conteúdo da Pasta source | não têm arquivos |
Conteúdo da Pasta agreement | |
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4. Condições de acesso e uso | |
Idioma | en |
Arquivo Alvo | Simioni2020_Article_IntegrationOfMulti-sensorAnaly.pdf |
Grupo de Usuários | simone |
Grupo de Leitores | administrator simone |
Visibilidade | shown |
Permissão de Leitura | deny from all and allow from 150.163 |
Permissão de Atualização | não transferida |
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5. Fontes relacionadas | |
Unidades Imediatamente Superiores | 8JMKD3MGPCW/449U4PL |
Lista de Itens Citando | sid.inpe.br/bibdigital/2021/03.06.05.18 3 |
Divulgação | WEBSCI; PORTALCAPES; SCOPUS. |
Acervo Hospedeiro | urlib.net/www/2017/11.22.19.04 |
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6. Notas | |
Campos Vazios | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url |
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7. Controle da descrição | |
e-Mail (login) | simone |
atualizar | |
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