Traditionally, planting sugarcane is due to the imposition of the width of the gauge of agricultural machines, which are limited to some already established technologies that require innovation. The use of wider spacing facilitates mechanization, avoids damages caused by trampling and conditioning the culture to the machines characteristics. However, the reduction in the distance between the lines and between plants increases the population of sugarcane plants by area, and probably, the crop yield. Several factors contribute to yield increase, such as greater leaf area, greater use of nutrients and soil water by roots, better control of weeds by greater soil shading, greater soil protection against erosion due to the impact of raindrops, more tillers per hectare, among others. The easiest way of measuring canopy closure is through leaf area index (LAI). To indirect obtain the LAI, new instruments and techniques have been developed, presenting speed and facility for the data collection. Unmanned aerial vehicles (UAVs) can be used as a low-cost tool for obtaining high resolution remote data. In order to measure leaf area or canopy closure, several studies have used some methodologies using UAV, but none of them for sugarcane. The objective of this paper was to use UAV images to detect canopy closure at different spacing of sugarcane planting in experimental plots. The ANOVA test shown that the Green-Red Vegetation Index (GRVI) index was able to detect canopy closure.