The growing trend in the world population causes an increment in the demand for food as fruits like oranges. In this context, crop grass coverage becomes essential to reduce the resources in tree maintenance and improve the harvest. In this paper, we propose the use of remote sensing for monitoring the grass coverage. To do so, we have compared in times between plots with and without initial coverage. In our work, we present image-processing techniques that consist of using different bands of Sentinel-2 images for different periods of the year, of obtaining reliable information for changes in the grass-coverage of the selected plots. The pixels of the selected images have a resolution of 10 m × 10 m wherein our experiment represents information about orange trees plus grass coverage or soil. In addition, we present the results of the study, demonstrating the best behaviour of the presented technique. For this experiment, we use five different brands of the satellite: red band, green band, blue band, near-infrared band, and water vapour band. As well as normalised vegetation index using combinations of red and infrared bands. The significance values are obtained applying Single Analysis of Variance, a Statistical analysis. In this case, the higher results are located in WVP band with F- Reason of 42.56 and P-Value of 0.000 blue bands with F-Reason of 38.61 and P-Value of 0.000.