Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1138479
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dc.contributor.authorANDRADE, R. G.
dc.contributor.authorHOTT, M. C.
dc.contributor.authorMAGALHAES JUNIOR, W. C. P. de
dc.contributor.authorPACIULLO, D. S. C.
dc.contributor.authorGOMIDE, C. A. de M.
dc.date.accessioned2021-12-29T02:02:03Z-
dc.date.available2021-12-29T02:02:03Z-
dc.date.created2021-12-28
dc.date.issued2021
dc.identifier.citationInternational Journal of Advanced Engineering Research and Science, v, 8, n. 12, p. 365-370, 2021.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1138479-
dc.descriptionTraditional procedures for biomass estimation usually use destructive methods with great demands on time, resources, and labor. The development of models for automated estimation of pasture biomass, particularly from images captured by Unmanned Aerial Vehicle (UAV), in addition to high spatiotemporal resolution combined with flexibility in image acquisition, provides agility, the economy of resources, and labor. The objective of this work was to establish a technical feasibility study for the use of multispectral sensors onboard an Unmanned Aerial Vehicle (UAV) to estimate the vigor classes of Brachiaria ruziziensis pastures. For this purpose, imaging cameras in the visible (RGB), near-infrared and red edge ranges were used for continuous monitoring of 20 pasture paddocks with an area of 1,350 m2 each, totaling 27,000 m2 of the experimental area. The indices performed well and were sensitive in class discrimination at intervals that range from soil exposure and stresses caused by pest and disease infestation (low vigor) to conditions in which the vegetation is in good development, in class intervals with high levels of vegetation and, consequently, pointing to high values of biomass.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectÍndice de vegetação
dc.subjectUAV
dc.titleEstimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform.
dc.typeArtigo de periódico
dc.subject.thesagroForragem
dc.subject.thesagroSensoriamento Remoto
dc.subject.nalthesaurusForage
dc.subject.nalthesaurusRemote sensing
dc.subject.nalthesaurusVegetation index
riaa.ainfo.id1138479
riaa.ainfo.lastupdate2021-12-28
dc.identifier.doihttps://dx.doi.org/10.22161/ijaers.812.37
dc.contributor.institutionRICARDO GUIMARAES ANDRADE, CNPGL; MARCOS CICARINI HOTT, CNPGL; WALTER COELHO P DE MAGALHAES JUNIOR, CNPGL; DOMINGOS SAVIO CAMPOS PACIULLO, CNPGL; CARLOS AUGUSTO DE MIRANDA GOMIDE, CNPGL.
Aparece nas coleções:Artigo em periódico indexado (CNPGL)

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