Variability in understory structure is an important problem in estimating tree canopy cover (TCC) with satellite imagery. Differences between understory structure due to the composition and configuration of herbaceous/shrub species often produce different vegetation index values despite these areas having the same TCC. This study offers a linear transformation approach to minimizing the influence of variability in the understory to accurately estimate percent TCC from RapidEye satellite data. TCC was modeled as a function of the Normalized Difference Vegetation Index (NDVI), Normalized Difference Red-Edge Index (NDRE), adjusted (linear transformed) NDVI (NDVIadj), and adjusted NDRE (NDREadj) using simple linear regression. The coefficient of determination of validation (R-vld(2)) of the models using NDVI, NDRE, NDVIadj, and NDREadj as explanatory variables were, respectively, 0.50 (RMSEvld = 9.64%), 0.38 (RMSEvld = 10.7%), 0.78 (RMSEvld = 6.61%), and 0.73 (RMSEvld = 7.23%). These results showed that the linear transformation used for standardizing the vegetation index values of understory was an effective approach for estimating TCC.