## 2 Dataset and Methodology
### Site Selection Results  
The AHP was employed to determine suitable areas for PV farms in Gaziantep as an MCDM method. The AHP methodology integrates spatial data from various criteria to evaluate and rank potential locations. This approach is especially effective in regions like Gaziantep, where multiple geographical and environmental factors influence the feasibility of PV installations. By incorporating diverse datasets, such as for solar radiation, land use, slope, aspect, and distances to roads, faults, and powerlines, as well as wind speed, the study sought to identify optimal areas for solar energy deployment. In the study, the AHP tool in ArcGIS 10.6 was used to apply weightings to the criteria. All reclassified criteria were aggregated and weighted using the function of overlay analysis in ArcGIS 10.6. The use of AHP ensures a structured and systematic evaluation process, facilitating informed decision-making for renewable energy planning. In this study, the AHP framework uses eight primary criteria to assess suitability: solar radiation, land use, slope, aspect, distance to roads, distance to faults, distance to powerlines, and wind speed, and 8 \(\times\) 8 pairwise comparison matrices were formed. Each criterion was evaluated based on its relative importance using a pairwise comparison matrix. This matrix enables the assignment of weights to each criterion, reflecting their influence on the decision-making process. Through the matrix, normalized weight vectors are obtained based on the assigned importance values of the criteria. For instance, solar radiation, being critical for energy generation, typically receives the highest weight, followed by land use and slope. The normalized eigenvalues derived from the matrix ensure consistency and objectivity in weight distribution. These weights are then applied to the spatial layers of the criteria, which are analyzed and combined in GIS to produce a suitability map,  
Figure 2: Existing PV installations on DEM maps of Gaziantep. highlighting areas with the highest potential for PV farm installations in Gaziantep. After the pairwise comparison of criteria and the determination of importance, the consistency of the comparison matrix was evaluated using the CR, consistency index CI, and random index RI. The consistency ratio was calculated based on Equation (1), where values below 0.1 indicate an acceptable level of consistency. The CI was 0.043, which was calculated by \(\lambda\)max and n as 8.3 and 8, respectively. The CR was 0.082 and since this value was below 0.1, it was inferred that appropriate weightings were used for the AHP method. After determining the weights, the criteria were combined using a weighted overlay. The pairwise comparisons are illustrated in Table 4.  
Also, the criteria weights for the suitability map of PV farms were calculated and are shown in Table 5. The most influential criterion was GHI, with a weight of 38.89%, where areas receiving more than 1850 kWh/m\({}^{2}\) were rated as highly suitable (Grade 5), while locations with irradiation below 1550 kWh/m\({}^{2}\) received an unsuitable score (Grade 1). Land use/cover followed with a weight of 20.15%, where agricultural and barren lands (categories 3.3.2 and 3.3.3) were rated as highly suitable (Grade 5), whereas other land types, such as dense vegetation, received lower suitability scores. Distance to roads received a weight of 14.22%, where proximity to roads (0.1-1 km) was deemed to be highly suitable (Grade 5), while areas located more than 6 km away were considered to be unsuitable (Grade 1). The distance to fault lines (9.65% weight) influenced the safety of PV installations, with locations farther than 35 km from fault lines being rated as highly favorable. Similarly, distance to powerlines (6.82% weight) was viewed as crucial for energy transmission efficiency, with locations within 2 km receiving the highest value. Topographical factors, such as slope (4.68%), played a significant role, with flatter areas (0-2%) being the most ideal for PV farms.