Estimate of vigor classes of Brachiaria ruziziensis using sensors boarded on UAV plataform.

Traditional 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 spatiotempora...

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Detalles Bibliográficos
Autores: ANDRADE, R. G., HOTT, M. C., MAGALHAES JUNIOR, W. C. P. de, PACIULLO, D. S. C., GOMIDE, C. A. de M.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:Brasil
Institución:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
Repositorio:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Idioma:inglés
OAI Identifier:oai:www.alice.cnptia.embrapa.br:doc/1138479
Acceso en línea:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1138479
https://dx.doi.org/10.22161/ijaers.812.37
Access Level:acceso abierto
Palabra clave:Índice de vegetação
UAV
Forragem
Sensoriamento Remoto
Forage
Remote sensing
Vegetation index
Descripción
Sumario:Traditional 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.