###### Abstract
Despite these advancements, the suitability analysis often varies by region, influenced by local climatic, geographic, and socio-economic conditions [17; 18; 19; 20; 21]. When determination of suitable areas for PV fields with different parameters in many different national or regional areas with the AHP method was examined, it was found that 32.77% of the central region of the state of Rio Grande do Sul in Brazil was suitable for PV installations, with 453 specific sites identified [22]. In another study area, the suitability of locations for PV farms was categorized into five classes, revealing that approximately 28% of the city was suitable for such installations, as in Kayseri, Turkiye [23]. In addition to fundamental data such as solar radiation and land use/cover, which are commonly preferred for identifying suitable PV areas, parameters such as distance to power transmission lines, fault lines, roads, wind speed, annual dusty days, and others are also utilized depending on the characteristics of the study area [17; 24; 25; 26]. To mitigate the effects of climate change, analyses of renewable energy sources using the AHP at the national level have proven effective in identifying suitable areas for both wind and solar energy. A total of 25.28% of the area was identified as suitable for large-scale PV farms, 5.93% for large-scale wind farms, and 40.02% for small-scale PV farms with twelve different datasets and using the AHP method in Pakistan. These findings demonstrate the potential for tailored renewable energy deployment, supporting sustainable energy goals and efficient land use [27]. These findings underscore the potential for targeted renewable energy development to enhance energy sustainability and reduce carbon emissions. Moreover, the comparison of identified suitable areas with existing PV installations provides valuable insights into the efficiency of current site selection processes. Economic constraints, political influences, and land ownership issues can lead to inconsistencies between ideal and actual locations. When evaluating PV farm locations, it is important to consider both suitability analysis and real-world implementation factors. Additionally, when analyzing the spatial distribution of existing PV farms, a high correlation will be observed between the identified suitable areas and the locations of installed PV systems, when the AHP method is used to assess optimal PV farm suitability, considering environmental and infrastructural criteria and integrating factors such as solar irradiance, proximity to roads, and land use in Turkey and Greece. The growing recognition of the value of combining GIS with AHP in renewable energy site selection can ensure a more systematic and objective approach to planning [19; 28; 29; 30]. Turkey has significant solar energy potential due to its geographical location. With approximately 31,491 solar power plants, it generates around 14-15 TWh of electricity annually, which accounts for nearly 10% of the country's total energy production. The solar energy potential maps of Turkey, which analyze solar radiation and sunshine duration, reveal that regions such as southeast Anatolia and the Mediterranean have particularly high potential. Therefore, identifying suitable PV farm areas in these regions, based on various parameters, is crucial for energy efficiency and production [31; 32]. In the literature, it is observed that different datasets are used depending on the field of study. By examining the fields of study in the literature, suitable datasets for Gaziantep were identified, and the research was conducted accordingly. It is generally indicated that, in addition to data types such as GHI, land use, topography, etc., natural disasters and weather conditions should also be considered in relation to the solar energy system. Following the earthquake that occurred in Gaziantep and surrounding provinces in February 2023, it was suggested that the distance to faults should be examined.