# Satellite Monitoring of Italian Vineyards and Spatio-Temporal Variability Assessment
## 5 Conclusions  
Long-term monitoring through RS was conducted on an extended dataset of Italian vineyards. The VIs' behaviour was assessed based on manually measured structural and topographic features in each vineyard for six vintages, underlining the specific features of each VI. A temporal effect was always verified as relevant to the average VIs values and dispersion indices, underlining the importance of recording data from the same vintage.  
While vineyard location and shoot arrangement have been well established as factors affecting RS performance, this study revealed row orientation's critical yet often overlooked role. Specifically, a clear distinction was observed between the behaviour of NS and EW-oriented vineyards. NS-oriented vineyards consistently exhibited higher VIs values and less variability compared to EW-oriented ones, which experienced greater temporal and spatial fluctuations. These differences in spectral response are likely due to the variations in light interception and environmental stress factors, such as thermal and drought stress, that affect vineyards based on their orientation.  
This could emphasise the need to include the row's orientation when planning pre-vision agriculture based on RS. The impact of row orientation on VIs introduces a degree of variability and uncertainty that can influence the delineation of homogeneous zones within a vineyard and, subsequently, suboptimal management decisions. Some management items demonstrated a connection with the nugget computed among the experimental semivariogram. Again, row orientation, training system, and row spacing were found to be sources of random variability. In conclusion, the above-mentioned deductions suggest that some of the vineyard's structural features should be appraised and examined. Then, the vineyards should be clustered according to defined groups, avoiding inconclusive statistical analysis. Future studies can reduce random error and avoid inconclusive statistical outcomes. This approach will enable more targeted agricultural management practices, ultimately improving vineyard performance and sustainability in a PV context.  
Conceptualisation, F.M., M.S. and A.Z.; investigation, data curation and formal analysis, A.Z. and A.C.; writing--original draft preparation A.Z. and A.C.; supervision, writing--review and editing M.S., D.T. and F.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Italian Ministry of University and Research (MIUR), PRIN 2022 \"Farming Data Implementation: definition of smart solutions for the effective implementation of Agriculture 4.0 in winery production\" (Prot. 20229 ESL5Y) (CUP D53D23011620001).  
**Data Availability Statement:** Original data containing the vineyards' features are available and linked to the published article [[https://doi.org/10.1016/j.dib.2020.106589](https://doi.org/10.1016/j.dib.2020.106589)]([https://doi.org/10.1016/j.dib.2020.106589](https://doi.org/10.1016/j.dib.2020.106589)). Indices and statistics supporting the findings of this study are available from the corresponding author [PERSON], on request.  
**Conflicts of Interest:** The authors declare no conflicts of interest.