## 4 Discussion  
This study aimed to identify the most suitable areas for the establishment of PV farms in Gaziantep using the AHP methodology. By incorporating various criteria, including  
Figure 6: Example of existing PV farms on suitability map. (**a**) PV farm closest to the city center; (**b**) Westermmost PV farm; (**c**) Northwestern PV farm; (**d**) The farthest PV farm from the city center; (**e**) PV farm southwest of the city center; (**f**) PV farm in the northwest and closest to the center.  
global solar irradiation, land use/cover, distance to roads, fault lines, and powerlines, slope, aspect, and wind speed, areas were identified with varying levels of suitability for solar energy production. The analysis revealed that approximately 80% of the city is suitable for PV farm installations, with the southern and northern regions exhibiting the highest suitability levels. In terms of the existing PV farms, the findings indicate that a significant portion of them are located in moderately suitable to highly suitable areas, confirming that the majority of current installations align with optimal conditions for solar energy generation. Moreover, the comparison of the identified suitable areas with the existing PV farms indicated that while most of the farms are placed in favorable regions, some farms in the western and northern parts of the city are in less favorable locations, especially due to constraints related to the proximity to faults or lower solar radiation values. This study emphasizes the importance of using a multi-criteria decision-making approach like AHP for identifying optimal PV farm locations, which can guide future solar energy projects and maximize the efficiency of energy production in Gaziantep. Future research could further refine the criteria and incorporate additional factors, such as economic feasibility and environmental impact, to provide a comprehensive framework for PV farm site selection in the region.  
In addition, the application of MCDM methods, such as AHP, combined with GIS, offers a rapid and efficient solution for renewable energy site selection. By incorporating literature and data-driven models, this approach ensures a comprehensive evaluation of potential sites for PV farms, factoring in both environmental and technical suitability. GIS allows for the spatial analysis of multiple factors, while AHP provides a structured method for ranking and comparing the criteria. This integration in GIS environments streamlines decision-making processes and supports informed, evidence-based choices for the development of renewable energy infrastructure. Moreover, it offers a flexible tool that can be applied in various geographic and climatic conditions, making it a valuable resource for sustainable energy planning and development in regions like Gaziantep.  
The data and materials used in the analysis are available upon request from the corresponding author.  
The author would like to express gratitude to [PERSON] and the Earth3 Bee Laboratory for their support and valuable insights throughout this research. The author would like to thank the Land Monitoring Service of Copernicus for generously making the Corine data available. The author would like to thank the anonymous reviewers, whose comments and suggestions helped to improve the paper.  
The authors declare no conflicts of interest.