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Predictive models of species distributions use occurrence records and environmental data to produce a model of the species requirements and a map of its potential geographical distribution. This work analyses the contribution of remote sensing data, specifically the NDVI, for species distribution models, based on the taxonomic revision of the Neotropical genus Coccocypselum. GARP were use inside the OpenModeller to develop species distribution maps of five Coccocypselum species in the Brazilian territory. We generated two sets of models: using climate and topographic raster grids as environmental data, and a second one adding NDVI values. Presence and absence sample points statically evaluated the models, and for all species, Kappa values were higher than 0.5, indicating a good fit of the models. The sample size influenced the Mann-Whitney test, but it proved that species distribution models including NDVI were slightly better than models without NDVI. Despite this work is not conclusive, it contributes to generate better environmental data for ecological modeling.