Influence of different vegetation indices and heights of UAVs on the accuracy of grassland coverage estimation

Unmanned aerial vehicles (UAVs) equipped with high-definition digital cameras have various advantages such as low cost, high mobility, and large observation range in the field of grassland resource surveys and have a developmental potential. In this study, small UAVs and mobile phone cameras were used to obtain grassland coverage data. The vegetative index (VEG), excess green index (ExG), excess green minus excess red index (ExGR), and green leaf index (GLI) were selected to extract the grassland coverage information based on the visible light vegetation index, and the applicability of each vegetation index was analyzed from the viewpoint of UAV flight height and grassland coverage level. The results showed that (1) VEG and ExG can effectively estimate grassland coverage, with an average accuracy of more than 93%. The estimation results of ExGR and GLI were poor, with an average accuracy of only 75%～80%. (2) The estimation accuracy of the four methods reduced with increasing coverage. VEG had the worst performance in terms of accuracy of grass coverage estimation, followed by ExG. ExGR and GLI were less effective in estimating high-coverage grasslands. (3) The optimal UAV heights for VEG were 100 m for the high and middle coverage levels and 40 m for the low coverage level. The optimal UAV heights for ExG and ExGR were 100 m for the high and middle coverage levels and 80 m for the low coverage level. The UAV optimum heights for GLI were 100 m for the high coverage level and 20 m for the middle and low coverage levels.