Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1017535
Registro completo de metadados
Campo DCValorIdioma
dc.contributor.authorLUZ, N. B. dapt_BR
dc.contributor.authorOLIVEIRA, Y. M. M. dept_BR
dc.contributor.authorROSOT, M. A. D.pt_BR
dc.contributor.authorGARRASTAZU, M. C.pt_BR
dc.contributor.authorFRANCISCON, L.pt_BR
dc.contributor.authorMESQUITA JÚNIOR, H. N. dept_BR
dc.contributor.authorFREITAS, J. V. dept_BR
dc.date.accessioned2016-05-10T11:50:03Z-
dc.date.available2016-05-10T11:50:03Z-
dc.date.created2015-06-12pt_BR
dc.date.issued2015pt_BR
dc.identifier.citationIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1017535pt_BR
dc.descriptionIn response to the growing demand for reliable information on forest and tree resources as well as for land use/land cover (LULC) maps at larger scales, the Brazilian National Forest Inventory (NFI-BR) is now being conducted. Besides the traditional approaches related to forest assessment, the NFI-BR includes a geospatial component to provide such information at landscape scale. Using a sampling grid of 20 km × 20 km, field registry sample units were established, and 100 km2 landscape sample units (LSU) were located on a 40 km × 40 km grid. LULC maps are being prepared for each LSU using RapidEye and Landsat-8 imagery. Different remote sensing techniques are being tested to characterize LULC in order to identify patterns in different themes using spatial analysis, such as forest fragmentation, state of conservation, production and forest health. The mapping approach uses a hybrid approach, here understood as the combination of automatic unsupervised pixel-by-pixel classification and object based image classification. Attributes from image objects such as spectral characteristics, texture, and context are also involved in process tree classification, as well as ancillary data such as roads, water bodies and digital terrain models. LULC maps are the basis for analyzing landscape-scale forest fragmentation analysis as well as for evaluating compliance of permanent preservation areas under recently approved environmental legislation.pt_BR
dc.formatDisponível online.pt_BR
dc.language.isoporpt_BR
dc.rightsopenAccesspt_BR
dc.subjectImagem de satélitept_BR
dc.subjectInventário Florestal Nacionalpt_BR
dc.subjectClassificação orientada a objetospt_BR
dc.subjectClassificação automática de imagenspt_BR
dc.subjectBrasilpt_BR
dc.subjectObject-based classificationpt_BR
dc.subjectAutomatic image classificationpt_BR
dc.subjectAncillary datapt_BR
dc.titleClassificação híbrida de imagens Landsat-8 e RapidEye para o mapeamento do uso e cobertura da terra nas Unidades Amostrais de Paisagem do Inventário Florestal Nacional do Brasil.pt_BR
dc.typeArtigo em anais e proceedingspt_BR
dc.date.updated2016-05-10T11:50:03Zpt_BR
dc.subject.thesagroSensoriamento Remotopt_BR
dc.format.extent2p. 7222-7230.pt_BR
riaa.ainfo.id1017535pt_BR
riaa.ainfo.lastupdate2016-05-09pt_BR
dc.contributor.institutionNaíssa Batista da Luz, ONU/FAO; YEDA MARIA MALHEIROS DE OLIVEIRA, CNPF; MARIA AUGUSTA DOETZER ROSOT, CNPF; MARILICE CORDEIRO GARRASTAZU, CNPF; LUZIANE FRANCISCON, CNPF; Humberto Navarro de Mesquita Júnior, Serviço Florestal Brasileiro; Joberto Veloso de Freitas, Serviço Florestal Brasileiro.pt_BR
Aparece nas coleções:Artigo em anais de congresso (CNPF)

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
2015MariliceClassificacaohibridadeimagensLandsat8eRapidEye.pdf1 MBAdobe PDFThumbnail
Visualizar/Abrir
Mostrar registro simples do item Visualizar estatísticas

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace