Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1140126
Title: Mapping key indicators of forest restoration in the Amazon using a low-cost drone and artificial intelligence.
Authors: ALBUQUERQUE, R. W.
VIEIRA, D. L. M.
FERREIRA, M. E.
SOARES, L. P.
OLSEN, S. I.
ARAUJO, L. S. de
VICENTE, L. E.
TYMUS, J. R. C.
BALIEIRO, C. P.
MATSUMOTO, M. H.
GROHMANN, C. H.
Affiliation: RAFAEL 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.
Date Issued: 2022
Citation: Remote Sensing, v. 14, n. 4, 830, 2022.
Thesagro: Cecropia
NAL Thesaurus: Photogrammetry
Species diversity
Vismia
Keywords: Deep learning
Drones
Remotely piloted aircraft
RGB
Tree crown heterogeneity index
Tree species
DOI: https://doi.org/10.3390/rs14040830
Notes: Na publicação: Luciana Spinelli Araujo.
Type of Material: Artigo de periódico
Access: openAccess
Appears in Collections:Artigo em periódico indexado (CENARGEN)

Files in This Item:
File Description SizeFormat 
remotesensing-14-00830.pdf13,16 MBAdobe PDFThumbnail
View/Open

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace