## 3 Results  
Overall, Figure 7 shows that suitable regions for PV plants were found using the maps of PV power output per capacity per hour (unit of h) obtained using the method in [11], using a geo-spatial analysis of the GIS. In particular, this map (Figure 7a) represents the distribution of the predicted PV outputs in March 2017, classifying them into five quantile-based classes, with a range of 0 h to 154,492 h. In addition, the national map of the PV power output (unit of h, Figure 7a) was restricted to regions 200 m from the highway networks, using a buffer function (Figure 7b). The constrained map of the PV power output is sorted into suitable regions through a geo-spatial analysis (Section 2.2) at a national scale (Figure 7c). Figure 6: Plan view of the PV plant installation from the north (**left**) and the top (**right**). Figure 7b,c show that relatively lower PV output regions were excluded by the geo-spatial analysis. In addition, the sorted PV outputs in suitable regions at a national scale were zoomed in to the case area (i.e., district of Ucheon-myeon in South Korea, Figure 7d). Figure 7d shows that the range of PV output values (133,009 h to 133,215 h) at a regional scale is unchanged in comparison with the range of the PV output (0 h to 142,163 h) at a national scale (Figure 7c). To determine the amount of power that can be generated in the candidate regions, the solar PV power output (MWh) is evaluated by multiplying the PV power per capacity per hour (Figure 7) with the power-generation capacity (Section 2.3). The evaluated solar PV power output is represented in the distribution plots through spatial analysis and different map scales. Specifically, the distribution plots (Table 2) display the range and distribution of the evaluated solar PV power output producible in each 30 \(\times\) 30 m\({}^{2}\) area within a 200-m radius from the highway network. The potential production of the PV output within a 200-m radius from the highway networks, without progressing the spatial analysis, at a national scale is computed as 29,002 GWh in an area of 1896.130 km\({}^{2}\). Moreover, the distribution of the PV outputs was within the range of 7.9 MWh to 16.7 MWh, with a mean, median, and standard deviation of 13.667 MWh, 13.967 MWh, and 0.697 MWh, respectively. Furthermore, selected areas \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline \multirow{3}{*}{**Condition**} & \multirow{3}{*}{
\begin{tabular}{c} **Area** \\ **(km\({}^{2}\))** \\ \end{tabular} } & \multicolumn{6}{c}{**Monthly PV Power Output**} \\ \cline{3-7}  & & **Total** & **Mean** & **Median** & **Standard** & **Range of PV** \\  & & **(GWh)** & **(MWh)** & **(MWh)** & **Deviation** & **Distribution** \\ \hline Within 200 m of & & & & & & \\ a highway at a & 1896.130 & 29,002 & 13.887 & 13.967 & 0.697 & 7.9 to 16.7 MWh \\ national scale & & & & & & \\ \hline Restricted area & & & & & & \\ that satisfies the & & & & & & \\ spatial analysis & 455.063 & 6784 & 13.531 & 13.754 & 0.920 & 9.4 to 15.4 MWh \\ at a national scale & & & & & & \\ \hline Case study area & & & & & & \\ that satisfies the & 1.669 & 8.227 & 13.407 & 12.782 & 0.827 & 11.2 to 14.4 MWh \\ spatial analysis & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of the distribution of PV outputs potentially produced in different conditions. Figure 7: Maps of (**a**) solar PV power output per capacity per hour; (**b**) extracted PV power map in the vicinity of the highway networks (200 m); (**c**) restricted PV power map by geo-spatial analysis; and (**d**) visualization of the PV power map in the case area (Ucheon-myeon). within 200 m of the highway networks were sorted into available regions (i.e., the area was reduced from 1896.130 km\({}^{2}\) to 455.063 km\({}^{2}\)) while satisfying the spatial analysis (Section 2.2) to rule out the four factors (distance to road, slope, river, reservoir), that are inappropriate for installing PV plants.