Mapping key indicators of forest restoration in the Amazon using a low-cost drone and artificial intelligence.

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dc.contributorRAFAEL 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.
dc.creatorALBUQUERQUE, R. W.
dc.creatorVIEIRA, D. L. M.
dc.creatorFERREIRA, M. E.
dc.creatorSOARES, L. P.
dc.creatorOLSEN, S. I.
dc.creatorARAUJO, L. S. de
dc.creatorVICENTE, L. E.
dc.creatorTYMUS, J. R. C.
dc.creatorBALIEIRO, C. P.
dc.creatorMATSUMOTO, M. H.
dc.creatorGROHMANN, C. H.
dc.date2022-06-12T04:02:01Z
dc.date2022-06-12T04:02:01Z
dc.date2022-02-16
dc.date2022
dc.date.accessioned2026-07-07T11:53:33Z
dc.descriptionNa publicação: Luciana Spinelli Araujo.
dc.identifierRemote Sensing, v. 14, n. 4, 830, 2022.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1140126
dc.identifierhttps://doi.org/10.3390/rs14040830
dc.identifier.urihttp://hdl.handle.net/123456789/516530
dc.languageeng
dc.rightsopenAccess
dc.subjectDeep learning
dc.subjectDrones
dc.subjectRemotely piloted aircraft
dc.subjectRGB
dc.subjectTree crown heterogeneity index
dc.subjectTree species
dc.subjectCecropia
dc.subjectPhotogrammetry
dc.subjectSpecies diversity
dc.subjectVismia
dc.titleMapping key indicators of forest restoration in the Amazon using a low-cost drone and artificial intelligence.
dc.typeArtigo de periódico

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