## 3 Results and Discussion
### Variable Rate Nitrogen Application Profitability  
Relative prices of the NDVI images were compared to the economic benefits delivered by variable rate nitrogen application, which is a well-known and relatively widespread  
Figure 5: Loading plot of the first and the second principal components of satellites features obtained from PCA. Figure 6: Linear model of price per hectare based on data volume per hectare. practice. Final prices of the NDVI images were composed of prices per hectare (considering minimum order area and take-off cost), processing, and elaboration costs. The price of a single NDVI image was then compared to the economic benefits provided by variable rate nitrogen application, as one NDVI image is the minimum required for nitrogen application spatial management. The economic benefits of the variable rate application were extracted from a recent meta-analysis [52], considering all items of the meta-analysis. This meta-analysis analyzed 58 studies applying a N-rich strip approach and sensor-based site-specific N management in grains. Figure 7 shows price trends concerning area variation for UAVs, planes, and VHR, HR and MR satellites. In the same graph, the variation in precision nitrogen management profitability according to area variation is plotted. The intersection between the price trend and the variation in profitability represents the break-even point of this technology. Areas greater than the break-even point represent a profitable use of the specific technology for variable rate nitrogen application. On the other hand, on areas lower than the break-even point, variable rate nitrogen application may not generate economic advantages. Lines are plotted with halos which represent data distribution with a confidence interval of 95%. The equation results from the regression are reported in Table 4. \begin{table}
\begin{tabular}{c c} \hline \hline
**Services** & **Equations** \\ \hline UAV & \(Value_{\xi}=43.6\times\text{ha}+75\) \\ \hline Plane & \(Value_{\xi}=1.75\times\text{ha}+2075\) \\ \hline VHR & \(Value_{\xi}=-6\times 10^{-16}\times\text{ha}+2536\) \\ \hline HR & \(Value_{\xi}=-8\times 10^{-17}\times\text{ha}+434\) \\ \hline MR & \(Value_{\xi}=-2\times 10^{-17}\times\text{ha}+83.1\) \\ \hline Profitability & \(Value_{\xi}=33\times\text{ha}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Equation of value of service according to hectare variation. Figure 7: Break-even point of different sensor platforms used for site-specific nitrogen application (halo represents data distribution with a confidence interval of 95%; data are in logarithmic scale). Table 5 shows that medium-resolution satellites (free of charge satellites) are profitable in fields whose minimum size is 2.52 hectares. For high-resolution satellites, the profitability starts from 13.2 hectares, while very-high-resolution satellite profitability starts from 76.8 hectares. Plane acquired NDVI is profitable on blocks larger than 66.4 hectares (Table 5). The analysis allowed us to assess that the average price of UAV-acquired NDVI images was 43.36 EUR/ha. The average economic benefit provided by variable nitrogen application was 33 EUR/ha. As such, UAV NDVI images were not affordable for variable rate nitrogen application. Nevertheless, Figure 7 shows an overlap of price line halos within the 95% confidence intervals. This result means that some UAV image providers can offer profitable data for variable rate nitrogen application when this technique supplies above-average benefits. Values of profitability obtained considering the 95% confidence interval take into account the varying profitability of variable rate nitrogen application on fields with different spatial variability.