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The atmospheric components interfere in imaging sensors reflectance values. This study aimed to estimate the Leaf Area Index (LAI) of sugarcane based on the normalized vegetation index (NDVI) with atmospheric correction. For this, was 1 Pós-graduandos em Agronomia, Solo e Água, na Escola de Agronomia da Universidade Federal de Goiás UFG/EA.Campus Samambaia. e-mail: rodrigomoura@agricola.eng.br, joaomfsouza@gmail.com, deborahlidyasales@gmail.com; Goiânia / Nova Veneza, Km 0 Caixa Postal 131, CEP 74690-900, Goiânia, GO, Brasil Telefone: (62) 3521 1676; Fax: (62) 3521 1600 2 Eng. Agr. Professor Doutor, Escola de Agronomia, da Universidade Federal de Goiás. Rodovia; E-mail: derblai@ufg.br, josealvesufg@yahoo.com.br, awpego@bol.com.br R. M. Pereira et al. 1110 collected data from real IAF at field, and satellite orbital data Landsat-8, at the same acreage. These data were correlated in time in ten dates of passage of the Landsat-8 / OLI. NDVI was obtained from satellite sensor reflectance data, where was applied the FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercube) algorithm for minimizing the atmospheric effects. The model with atmospheric correction presented values of d = 0,95, and MAE = 0,44 m m, while without atmospheric correction model determined d = 0,87 and MAE = 0,65 m m. It is recommended to estimate the IAF of sugarcane as a function of NDVI with atmospheric correction

ESTIMATIVA DO ÍNDICE DE ÁREA FOLIAR DA CANA-DE-AÇÚCAR EM FUNÇÃO DO NDVI CORRIGIDO