ArticleIn developing countries such as Brazil, research on low-cost remote sensing and
computational techniques become essential for the development of precision agriculture (PA),
and improving the quality of the agricultural products. Faced with the scenario of increasing
production of emerald grass (Zoysia Japônica) in Brazil, and the value added the quality of this
agricultural product. The objective of this work was to evaluate the performance of RGB (IV)
vegetation indices in the identification of exposed soil and vegetation. The study was developed
in an irrigated area of 58 ha cultivated with emerald grass at Bom Sucesso, Minas Gerais, Brazil.
The images were obtained by a RGB digital camera coupled to an remotely piloted aircraft. The
flight plan was setup to take overlapping images of 70% and the aircraft speed was 10 m s
-1
. Six
RGB Vegetation index (MGVRI, GLI, RGBVI, MPRI, VEG, ExG) were evaluated in a mosaic
resulting from the images of the study area. All of the VIs evaluated were affected by the
variability of lighting conditions in the area but MPRI and MGVRI were the ones that presented
the best results in a qualitative evaluation regarding the discrimination of vegetation and soil
