# Satellite Monitoring of Italian Vineyards and Spatio-Temporal Variability Assessment
## 3 Results
### General Variability
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Item** & **VI** & **Direction** & **Location** & **Topography** & **Training** & **Vintage** \\ \hline Mean & NDRE & *** & *** & *** & *** & *** \\ Mean & NDVI & *** & *** & *** & *** & *** \\ CV & NDRE & *** & *** & ** & *** & *** \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Outputs were retrieved from the multifactorial ANOVA performed on the categorical features (factors) and the VIs mean and CV (dependent variables). “***” indicates a \(p\) value \(<\) 0.001, \"***\" indicates a \(p\) value \(<\) 0.01, while “NS” indicates nonsignificant. Finally, data are clustered according to the topography classification in Figure 11. Those vineyards planted on a flatland usually showed higher VIs' average values than those planted on a sloped side. However, each vintage did not verify the trend (2018 and 2021). Moreover, a discrepancy in the number of items was found between the topography classes, in which the flat class counted 10,526 vineyards compared to 2567 owned by the sloped class. The item discrepancy could explain the large variability of the boxplots referred to as the flat class in Figure 11a,b. Exception for the vintage 2018, the sloped vineyards always showed higher CV values than those planted on a flatland (Figure 11c,d). The interaction between location and topography showed a valuable influence (\(p\)-value \(<\) 0.001). As a result, even though the vineyard is sloped, if it is in a flat landscape, the NDVI and NDE values are much lower. The sloped vineyards in a hilly landscape retrieved the  
Figure 10: The boxplots describe seasonal mean and CV computed per each VI through the six vintages according to the location classes used in this paper. Boxplots (**a**,**b**) display the seasonal average VIs: (**a**) refers to NDVI, and (**b**) refers to NDE. The boxplots (**c**,**d**) display the values of the seasonal CV: boxplot (**c**) refers to NDVI and boxplot (**d**) refers to NDE. Figure 9: The boxplots describe seasonal mean and CV computed per each VI through the six vintages according to the cardinal direction classes used in this paper. Boxplots (**a**,**b**) display seasonal VIs: boxplot (**a**) refers to NDVI and boxplot (**b**) refers to NDE. The boxplots (**c**,**d**) display the seasonal CV: boxplot. (**c**) refers to NDVI, and boxplot (**d**) refers to NDRE. highest VIs values, while the sloped vineyards in a plain landscape showed the lowest ones. On the other hand, the CV trend was opposite to the average values. Finally, the training system effect is presented in Figure 12. In this case, the trend is repeated yearly in each chart. According to the VIs' average value (Figure 12a,b), the training system followed the order HS, VS, and AS (0.610, 0.551, and 0.425, overall mean values, respectively, for NDVI and 0.395, 0.355, and 0.268, overall mean values, respectively, for NDRE). Also, in this case, the VI average and CV followed an opposite trend with the feature's classes, which reached the lowest average value and the highest CV. Hence, the training system followed the AS, VS, and HS order in the boxplots shown in Figure 12c,d.