## 1 Introduction
Therefore, because of the difficulties in data acquisition and limitations in computer performance, it takes a lot of time and effort to analyze the potential locations for rooftop greening and roadside tree planting for the entire metropolitan area. In the case of South Korea, relatively detailed data on entire cities can be secured and is being updated regularly through national GIS projects that have occurred six times. Furthermore, recent advances in CPU and GPU technology have enabled detailed location analyses of small facilities across cities. Meanwhile, with the increasing occurrence of abnormal weather and changing climates, the importance of temperature reduction among ecosystem control services is growing. As a result, various studies [18; 19; 20; 21; 22] analyzed the temperature reduction effects of rooftop greening and roadside tree planting. [PERSON] and [PERSON] [18] and [PERSON] et al. [19] emphasize that a lack of green areas in a city exacerbates the urban heat island phenomenon, while roadside trees can reduce temperatures by increasing latent heat during evaporation by blocking solar energy and creating shade. [PERSON] et al. [20] found that air temperatures could be decreased by introducing rooftop green areas based on monitored temperatures in four neighborhoods in New York City where urban heat island phenomena occur. [PERSON], [PERSON] and [PERSON] [21] measured the temperature of rooftop green spacesand found that temperatures decreased after sunset and that the surrounding air cooled down during nighttime. [PERSON] et al. [22] confirmed through an energy balance model that rooftop greening in China during the summer months could result in a loss of solar energy of up to 58% due to evaporation and a 30.9% exchange of longwave radiation, thereby reducing temperatures. With recent advances in computer technology, mathematical climate simulation models (MCSM) have been actively introduced and utilized in urban thermal environment analysis, showing reliable results with relatively accurate performance [23; 24; 25; 26]. Among the MCSM, CFD models like Envi-met have been widely applied in the research field to analyze air temperature differences due to rooftop greening and roadside tree planting. Applying Envi-met, [PERSON] et al. (2012) identified 0.5-1.7 \({}^{\circ}\)C air temperature reduction effects due to additional rooftop greening. [PERSON], [PERSON], and [PERSON] [21] applied a weather simulation to observe temperature-reducing effects according to the height of trees and the size of tree crowns and found a temperature difference of 1.2 to 3.3 \({}^{\circ}\)C depending on the shading effects during the day. [PERSON] et al. [27] analyzed air temperature variations in residential areas according to vegetation type, method, and planting density, and found that increasing planting density is most advantageous for reducing temperature and improving thermal comfort. As such, several experimental studies were conducted on the effects of reducing temperatures through rooftop greening and roadside planting, but there has been a lack of research analyzing this effect in consideration of the locations and quantities that are available for possible greening [28]. To support decision-making involved with solving problems arising in complex urban spaces, it is necessary to build a data analysis model based on a conceptual framework to achieve set goals [5; 29]. To ensure the effectiveness of urban greening, a detailed analysis is needed of how much greenery can be additionally introduced into urban spaces. In addition, the spatial characteristics of suitable locations of green roofs and roadside trees should be identified [30; 31]. The scientific credibility of urban greening plans would increase if the positive effects of rooftop greening and roadside tree planting introduced could be proved where possible in a city.