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 differentiate 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 differentiated the complete series of VGC densities when the cover interval range was 30% (p < 0.001 and p < 0.05).

The olive groves’ relevance has historically been ingrained in Mediterranean cultures. Spain stands out as a leading producer worldwide, where olive trees are extensively grown in the Andalusian region. However, despite the importance of this strategic agricultural sector, cultivation through the years has given rise to various crop management practices that have led to disruptive erosion processes. The objective is to measure land erosion in over 100-year-old olive groves considering the 3D reconstructed recent relief of olive tree mounds. A time-of-flight depth sensor, namely, Kinect v2, was employed to 3D model the target areas, i.e., trunk and exposed roots, to determine the height as a surrogate of the difference between the historical and recent relief. In three plots in southern Spain, the height of relic tree mounds was measured in olive trees at the upper and bottom parts to determine soil profile truncation. The results were compared and validated with manual measurements (ground truth values). Olive trees were grouped into high, moderate, and low slope gradient classes. The results showed, in all cases, high consistency in the correlation equations (Pearson’s coefficients over 0.95) between the estimated values in the models and the actual values measured in the olive trees. Consequently, these excellent results indicate the potential of this low-budget system for the study of historical erosion. Notably, the Kinect v2 can generate 3D reconstructions of tree mounds at microtopographic scales in outdoor situations that would be challenging for other depth cameras under variable lighting conditions, as found outdoors.

Análise sobre o conhecimento dos professores em relação as unidades de conservação em Novo Airão-AM .