## 1 Introduction  
The demand for energy is steadily increasing with respect to the world's total energy supply by source. In particular, fossil fuels (e.g., oil, coal, and natural gas) represent a large proportion of energy sources; for example, the global share of the total energy supply by fossil fuels was more than 80% in 2018 [1]. However, fossil fuel use should be reduced because it has negatively impacted the environment, such as the emission of greenhouse gases that cause global warming. Alternatively, renewable energy resources (e.g., solar energy, bioenergy, wind energy, ocean energy) can alleviate environmental pollution [2]. Among the many renewable energy sources, solar photovoltaic (PV) power generation is one of the promising renewables, with an infinite supply without additional pollution (e.g., soil contamination, noise pollution), ease of maintenance, and high reliability. Solar PV electricity production has sharply increased by nearly 4.7 times (i.e., 472.981%) between 2008 and 2018 [3]. To fulfill the increasing PV demand, large areas are needed to install solar power plants. However, South Korea has limited space to install power plants because it has complex terrains, such as mountains. Thus, the analysis of potential sites for installingPV plants should precede the construction of effective, lucrative, and sustainable solar PV plants in limited territories. Recent studies have focused on investigating optimal sites for PV plants by integrating geographic information systems (GISs) and multiple-criteria decision-making (MCDM) frameworks (e.g., the analytic hierarchy process, AHP) [4]. MCDM-based solar-site selection involves selecting the best candidates from among several alternatives in various criteria; e.g., geographical (e.g., slope, aspect, land use) [5], meteorological (e.g., solar irradiation, average temperature) [6], economic (e.g., land cost, construction cost) [7], and locational factors (e.g., distance to urban areas, distance to main roads, distance to power lines) [8]. Then, the candidate site is determined by estimating the weight of each factor. For example, [PERSON] and [PERSON] [9] presented a GIS-AHP-based solar PV site-selection approach using various criteria (e.g., solar irradiation, air temperature, slope, land aspect, proximity to urban areas, proximity to roads, and proximity to power lines) for Saudi Arabia. They revealed that solar irradiation had the greatest impact on site selection (32.2% of the total). [PERSON] et al. [10] also investigated the evaluation of suitable candidates for PV plants using GIS and AHP for Morocco; they reported that climate factors (solar irradiation: 42%, temperature: 22%) are important in site selection. In previous studies, solar irradiation has been revealed as a critical factor for selecting optimal PV power-plant sites. On the other hand, the direct application of PV power-generation data (e.g., the map-type data in [PERSON] et al. [11]) to investigate potential candidates can be more useful in terms of energy management and economic feasibility. This is because PV output data may not only be used to explore suitable sites but also to compute the electricity production at the candidate sites and, further, use it for economic analyses, such as marginal profits [12; 13]. Despite these advantages, research has rarely been conducted on the application of PV power output to site selection, as existing PV power-output estimation is only based on single or a few historical data collected from specific regions (i.e., solar farms) and does not consider topographical effects. Specifically, the insufficient use of historical PV power data may create challenges when geographic or weather patterns differ from the area where the data were collected. For example, the spatial heterogeneity of different terrain types (e.g., plains, mountains, and urban areas) can influence solar-energy estimation. [PERSON] et al.