Estimation of above-ground forest biomass in Amazonia with neural networks and remote sensing

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dc.citation.issue1pt_BR
dc.citation.spage27pt_BR
dc.citation.volume7pt_BR
dc.creatorALMEIDA, Arthur da Costa
dc.creatorBARROS, Paulo Luiz Contente
dc.creatorMONTEIRO, José Humberto Araujo
dc.creatorROCHA, Brigida Ramati Pereira da
dc.creator.Latteshttp://lattes.cnpq.br/2014957882626187pt_BR
dc.creator.Latteshttp://lattes.cnpq.br/5426644891558197pt_BR
dc.creator.Latteshttp://lattes.cnpq.br/7876237547372947pt_BR
dc.creator.Latteshttp://lattes.cnpq.br/9943372249006341pt_BR
dc.date.accessioned2019-12-02T13:33:32Z
dc.date.available2019-12-02T13:33:32Z
dc.date.issued2009-03
dc.description.abstractThis paper proposes an integrated methodology for estimating aboveground forest biomass in Amazon region. It is based on remote sensing, artificial neural networks and geographical information systems technologies for achieving confident results with a lesser cost than traditional methods of forest inventory. This methodology was tested and validated in Tucurui Reservoir, Brazil.en
dc.description.affiliationALMEIDA, A. C; MONTEIRO, J. H. A; ROCHA, B. R. P. Universidade Federal do Parápt_BR
dc.identifier.citationALMEIDA, Arthur da Costa et al. Estimation of above-ground forest biomass in Amazonia with neural networks and remote sensing. IEEE Latin American Transactions, [S. l.], v. 7, n. 1, p. 27-32, Mar. 2009. DOI 10.1109/TLA.2009.5173462. Disponível em: http://repositorio.ufpa.br/jspui/handle/2011/12104. Acesso em:.pt_BR
dc.identifier.doi10.1109/TLA.2009.5173462pt_BR
dc.identifier.issn1548-0992pt_BR
dc.identifier.urihttps://repositorio.ufpa.br/handle/2011/12104
dc.languageengpt_BR
dc.publisherUniversidade Federal do Parápt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.initialsUFPApt_BR
dc.relation.ispartofIEEE Latin America Transactionspt_BR
dc.rightsAcesso Abertopt_BR
dc.source.uriDisponível na internet via correio eletrônico: riufpabc@ufpa.brpt_BR
dc.subjectBiomass estimationen
dc.subjectNeural networksen
dc.subjectRemote sensingen
dc.titleEstimation of above-ground forest biomass in Amazonia with neural networks and remote sensingen
dc.typeArtigo de Periódicopt_BR
dcterms.citation.epage32pt_BR

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