# Satellite Monitoring of Italian Vineyards and Spatio-Temporal Variability Assessment
## 4 Discussion
### Spectral Indices Behaviour  
An introductive critical evaluation of the RS technique used in this research work is needed before the results are debated and the conclusions are stated. First, atmospheric interferences can impact the temporal analysis of RS data despite applying atmospheric correction techniques. Variations in atmospheric composition, such as differing concentrations of gases and particulate matter across locations, years, and seasons, can affect reflectance in a nonuniform manner across all wavelengths due to Rayleigh scattering and also influence the scattering direction (Mie scattering). This variability introduces complexity in accurately interpreting temporal changes in the Earth's surface characteristics observed through RS imagery [40]. Second, in vineyard RS, the geometric characteristics of vines, shaped by the trellis system employed, significantly influence the spectral response. This variation arises due to the different perspectives from which the S2 MSI sensor captures spectral signatures, varying with the amount of vine canopy visible. Such variability introduces a degree of  
Figure 19: The boxplots describe the seasonal CI (%) retrieved by the experimental semivariogram for all vineyards through the six-year monitoring according to the cardinal direction classes used in this paper. Boxplot (**a**) refers to NDVI and boxplot (**b**) refers to NDRE. Figure 20: The boxplots describe the seasonal CI (%) retrieved by the experimental semivariogram for all vineyards through the six-year monitoring according to the topography and training system classification used in this paper. In (**a,b**), data are grouped according to topography, while in (**c,d**), data are grouped according to the training system. Finally, (**a,c**) refer to NDVI, while (**b,d**) refer to NDRE. inconsistency in the analysis, as the sensor's viewpoint can alter the perceived spectral signature by capturing different proportions of vine canopy and background elements [41]. In general, NDVI and NDAE development followed the same trend that was found by other authors [42; 43]. At the beginning of the monitoring, both VIs retrieved the lowest values and increased in May (DOY 130-150 Figure 7). In June, the values were quite unstable, which was mainly due to the farming operations such as grass mowing and canopy trimming. Usually, in the second half of the growing season (DOY 160 Figure 7), the development assumed a decreasing trend explained by drought and grapevine leaves ageing. The regression line slope aimed to describe the VIs evolution across the temporal window. The NDVI's slope values ranged from \(-0.0684\) to \(0.09837\), while the NDAE's slope values ranged from \(-0.0598\) to \(0.0760\). In some cases, the VIs showed a reverse development compared to the standard. The fact was usually verified along the vineyard's border, which is clearly represented in Figure 6. Spontaneous vegetation, shadows, and environmental factors could retrieve a negative trend along the field's border. A severe drought could have jeopardised ordinary grapevine or grass-cover development in other cases. Compared to the NDVI, the NDAE usually retrieved lower values, as depicted in Table 4 and among the several boxplots in the Results section. For this reason, the NDAE is a useful alternative in case other VIs reach the saturation value (1 for the NDVI). Moreover, the vegetation red edge band of S2 has a 20 m ground resolution compared to the red and NIR bands, which measure 10 m. Hence, GEE resamples the 20 m resolution into 10 m for computing the NDAE. Despite information loss due to the resampling, no substantial divergence emerged from the VIs comparison. In all the PCA plots, both vectors were almost aligned. Almost all the ANOVAs reported the same outputs for the NDVI and NDRE except for the analysis performed in Tables 5 and 6, in which the NDRE CV and the NDRE slope CV results were not significant from the analysis on topography and location, respectively, even though both were relevant for the NDVI.