## 2 Materials and Methods
### Data
#### 2.2.2 Independent Variable  
Independent variables of the study consist of (1) socioeconomic, (2) topographic, (3) land-cover, and (4) environmental features. Socioeconomic and environmental features were constructed based on national statistics, and topographic, land-cover features were derived from remotely sensed data (Figure 2). \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Data** & **Source (Year)** \\ \hline
**Dependent** & Dummy variables for urbanization from 2007 to 2019 & Land Cover Map (2007 and 2019) \\
**Variable** & (0: non-urbanized area, 1: urbanized area) & \\ \hline  & Socioeconomic features & Population density & SGIS and KOSIS \\ \cline{2-3}  & \multirow{2}{*}{Socioeconomic features} & GRDP per capita & (2007 and 2019) \\ \cline{2-3}  & \multirow{2}{*}{Topographic features} & Elevation & \\ \cline{2-3}  & & Slope & \\ \cline{2-3}  & & Residential area & \\ \cline{2-3}  & & Commercial area & \\ \cline{2-3}  & & Industrial area & \\ \cline{2-3}
**Independent** & \multirow{2}{*}{Land-cover features (distance to:)} & Transportation area & \\ \cline{2-3}
**Variable** & & Agricultural area & \\ \cline{2-3}  & \multirow{2}{*}{Land cover Map (2007 and 2019)} & Forest area & \\ \cline{2-3}  & & Grassland area & \\ \cline{2-3}  & & Wetland area & \\ \cline{2-3}  & & Bare land area & \\ \cline{2-3}  & & Water area & \\ \hline \multirow{2}{*}{Environmental features} & Ecological ECVAM grade & ECVAM \\ \cline{2-3}  & \multirow{2}{*}{Legislative ECVAM grade} & (2007 and 2019) \\ \cline{1-1} \cline{2-3} \end{tabular}
\end{table} 
Table 1: Description of variables used in the study. \begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**2019**} \\ \cline{2-3}  & \multicolumn{2}{c}{**Urban Area**} \\
**(Residential, Commercial, Industrial Area)** & **Non-Urban Area** \\ \hline
**2007** & Urban Area & \\ \cline{2-3}  & (Residential, Commercial, Industrial Area) & - & - \\ \cline{2-3}  & Non-Urban Area & 1 (Urbanized) & 0 (Non-urbanized) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Classification of urbanized and non-urbanized area. First, socioeconomic features include population density and gross regional domestic product (GRDP) per capita. Each feature was derived from Statistical Geographic Information Service (SGIS, [[https://sgis.kostat.go.kr/](https://sgis.kostat.go.kr/)]([https://sgis.kostat.go.kr/](https://sgis.kostat.go.kr/)) (accessed on 1 August 2022)) and Korean Statistical Information Service (KOSIS, [[https://kosis.kr/](https://kosis.kr/)]([https://kosis.kr/](https://kosis.kr/)) (accessed on 1 August 2022)), respectively. The spatial unit of population density was the census block group level, while that of GRDP per capita was the county level. In this study, raster cells that were located within each census boundary were assigned to corresponding values in 2007 and 2019. Second, this study adopted the elevation and slope of each raster cell as topographic features. To calculate those, we utilized 10 m digital elevation model (DEM) data provided by the National Spatial Data Infrastructure Portal ([[http://www.nsdi.go.kr/](http://www.nsdi.go.kr/)]([http://www.nsdi.go.kr/](http://www.nsdi.go.kr/)) (accessed on 1 August 2022)) and the Surface tool in ArcGIS software. As a land-cover feature, we calculated the closest distance from a certain raster cell to other land-cover types. To this end, the Euclidean distance tool in ArcGIS was applied to residential, commercial, industrial, transportation, agricultural, forest, grassland, wetland, bare land, and water area on land-cover maps in 2007 and 2019. Figure 2: _Cont._  
Last, the Environmental Conservation Value Assessment Map (ECVAM) provided by the Ministry of Environment ([[https://ecvam.neins.go.kr/](https://ecvam.neins.go.kr/)]([https://ecvam.neins.go.kr/](https://ecvam.neins.go.kr/)) (accessed on 1 August 2022)) was utilized to measure environmental conservation value in South Korea.