Display omitted •This study estimated aboveground and net aboveground biomass on sparse shrub communities with large surface fluctuations.•This study provides the most suitable RGB algorithm for calculating vegetation coverage in sandy areas.•The relationship between vegetation coverage and aboveground biomass of shrub communities in Mu Us sandy land was study.studied. Accurate detection of vegetation cover and biomass of shrub communities in sandy area is beneficial for evaluating ecosystem, improving remote sensing models, and assessing the accuracy of remote sensing. Unmanned aerial vehicles (UAVs) have replaced traditional measurement methods in biomass and fraction of vegetation coverage (FVC) detection owing to the high spatial resolution of their imagery, their high positioning accuracy, and their ease of use. The existing methods of detecting biomass via UAVs, however, are not suitable for surface fluctuations, dwarf shrubs, and herbs. Futhermore, the method of calculating FVC using UAV RGB images has not yet been tested in sandy areas. To accurately extract FVC data, aboveground biomass (ABS) and net aboveground biomass (NABS) of shrub communities in the desert regions, UAV RGB images of 87 sample plots in the Mu Us sandy land were collected and used to obtain the FVC and biomass information via the object-based classification method, single shrub canopy biomass model and vegetation index-based method. The results are as follows: (1) the method of calculating ABS and NABS based on shrub canopy width extraction can be used in desert shrub communities, and results show that the ABS and NABS of vegetation communities increases from 15 to 800 g/m2 and 10–250 g/m2, respectively, in the Mu Us sandy land; and (2) the lowest value of ABS (NABS) appeared in the mobile sandy dunes and the highest value appeared in the semi-fixed sandy dunes; (3) under fixed thresholds conditions, the FVC can be extracted accurately using the excess green method, visible atmospherically resistant index, vegetative index, green red vegetation index and red green blue vegetation index (RGBVI); and (4) the correlation between the FVC calculated by the five RGB vegetation indexes and NABS in this study is greater than that between FVC and ABS (e.g. R2NABS - RGBVI = 0.734, R2ABS - RGBVI = 0.666), and the FVC calculated by RGBVI can be used to estimate NABS in the Mu Us sandy land. This study will provide new insights for field investigations of the ABS, NABS, and FVC in sandy areas.