In olive groves, vegetation ground cover (VGC) plays an important ecological role. The EU
Common Agricultural Policy, through cross-compliance, acknowledges the importance of this factor,
but, to determine the real impact of VGC, it must first be quantified. Accordingly, in the present
study, eleven vegetation indices (VIs) were applied to quantify the density of VGC in olive groves
(Olea europaea L.), according to high spatial resolution (10–12 cm) multispectral images obtained by an
unmanned aerial vehicle (UAV). The fieldwork was conducted in early spring, in a Mediterranean
mountain olive grove in southern Spain presenting various VGC densities. A five-step method was
applied: (1) generate image mosaics using UAV technology; (2) apply the VIs; (3) quantify VGC
density by means of sampling plots (ground-truth); (4) calculate the mean reflectance of the spectral
bands and of the VIs in each sampling plot; and (5) quantify VGC density according to the VIs.
The most sensitive index was IRVI, which accounted for 82% (p < 0.001) of the variability of VGC
density. The capability of the VIs to di erentiate VGC densities increased in line with the cover
interval range. RVI most accurately distinguished VGC densities > 80% in a cover interval range
of 10% (p < 0.001), while IRVI was most accurate for VGC densities < 30% in a cover interval range
of 15% (p < 0.01). IRVI, NRVI, NDVI, GNDVI and SAVI di erentiated the complete series of VGC
densities when the cover interval range was 30% (p < 0.001 and p < 0.05).
