Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1140126
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dc.contributor.authorALBUQUERQUE, R. W.
dc.contributor.authorVIEIRA, D. L. M.
dc.contributor.authorFERREIRA, M. E.
dc.contributor.authorSOARES, L. P.
dc.contributor.authorOLSEN, S. I.
dc.contributor.authorARAUJO, L. S. de
dc.contributor.authorVICENTE, L. E.
dc.contributor.authorTYMUS, J. R. C.
dc.contributor.authorBALIEIRO, C. P.
dc.contributor.authorMATSUMOTO, M. H.
dc.contributor.authorGROHMANN, C. H.
dc.date.accessioned2022-06-12T04:02:01Z-
dc.date.available2022-06-12T04:02:01Z-
dc.date.created2022-02-16
dc.date.issued2022
dc.identifier.citationRemote Sensing, v. 14, n. 4, 830, 2022.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1140126-
dc.language.isoeng
dc.rightsopenAccess
dc.subjectDeep learning
dc.subjectDrones
dc.subjectRemotely piloted aircraft
dc.subjectRGB
dc.subjectTree crown heterogeneity index
dc.subjectTree species
dc.titleMapping key indicators of forest restoration in the Amazon using a low-cost drone and artificial intelligence.
dc.typeArtigo de periódico
dc.subject.thesagroCecropia
dc.subject.nalthesaurusPhotogrammetry
dc.subject.nalthesaurusSpecies diversity
dc.subject.nalthesaurusVismia
dc.description.notesNa publicação: Luciana Spinelli Araujo.
riaa.ainfo.id1140126
riaa.ainfo.lastupdate2022-06-10
dc.identifier.doihttps://doi.org/10.3390/rs14040830
dc.contributor.institutionRAFAEL WALTER ALBUQUERQUE, UNB; DANIEL LUIS MASCIA VIEIRA, Cenargen; MANUEL EDUARDO FERREIRA, UFG; LUCAS PEDROSA SOARES, UNB; SØREN INGVOR OLSEN, University of Copenhagen, Denmark; LUCIANA SPINELLI DE ARAUJO, CNPMA; LUIZ EDUARDO VICENTE, CNPMA; JULIO RICARDO CAETANO TYMUS, The Nature Conservancy Brasil-TNC; CINTIA PALHETA BALIEIRO, The Nature Conservancy Brasil-TNC; MARCELO HIROMITI MATSUMOTO, ESALQ/USP; CARLOS HENRIQUE GROHMANN, USP.
Appears in Collections:Artigo em periódico indexado (CENARGEN)

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