## 2 Materials and Methods
### Accuracy Comparison between the First and Second Update Processes  
A total of 19,049 polygons were newly generated in the landcover map update processes with respect to the existing landcover map, whereby the number of vertices increased by 762,973. In the first update process, boundary corrections were performed based on aerial photos with high spatial resolutions as well as detailed classification of pervious surfaces existing within areas classified as impervious surface area. As a result, the numbers of polygons and vertices increased by 17,726 and 732,787, respectively, relative to the existing landcover map. In the second update process, these increased further by 1323 and 30,186, respectively. Thus, in this study, through this two-tiered updating process, it was possible to generate a new map with very high accuracy. The degree of increase in the number of vertices indicates the degree of detail of the polygons (Table 5). Comparison of the updated and existing landcover maps revealed class changes covering a total area of 26.49 km\({}^{2}\). The accuracy of the first and second update results reached 99.78%, considering the changed area and rate of change. This suggests that errors can occur when calculating the impervious surface areas for nonpoint source management (Table 6). Results demonstrated the accuracy of the proposed method, enabling the generation of updated landcover maps with substantially increased accuracy and precision in landcover classification and boundary delineation compared with the existing high-resolution (large-scale, 1:5000) landcover map in Korea. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Quality Assurance (QA) Items**} & \multicolumn{2}{c}{**Total Number of**} & \multicolumn{3}{c}{**Type of Errors**} & \multicolumn{1}{c}{**Total Error**} & \multicolumn{1}{c}{**Error Rate**} \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} **Medium-Level** \\ **Classification** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **High-Level** \\ **Classification** \\ \end{tabular} } & \(\otimes\)**Mis-** & \(\otimes\)**Non-Classifi-** & \(\otimes\)**Boun-Dary** & \(\otimes\)**Other** & **(\(\mathbf{b}\))** & **(\%)** \\ \hline Natural grass & Natural grassland & 157 & 3 & - & 10 & - & 13 & 8.28 \\ \hline \multirow{3}{*}{Artificial grass} & Golf courses & 24 & - & - & 4 & - & 4 & 16.67 \\ \cline{2-8}  & Cemetiers & 153 & - & - & - & - & - & - \\ \cline{2-8}  & Other grass & 10,231 (3148) & 40 & - & 416 & - & 456 & 4.46 \\ \hline \multicolumn{2}{c}{Inland wetland} & Inland wetland & 247 & - & - & - & - & - & - \\ \hline \multirow{3}{*}{Coastal wetland} & Tidal fats & - & - & - & - & - & - & - \\ \cline{2-8}  & Salt pools & - & - & - & - & - & - & - \\ \hline \multirow{3}{*}{Natural barren} & Beaches & - & - & - & - & - & - & - \\ \cline{2-8}  & River banks & - & - & - & - & - & - & - \\ \cline{2-8}  & Rock faces, rocks & - & - & - & - & - & - & - \\ \hline \multirow{3}{*}{Artificial barren} & Mining areas & - & - & - & - & - & - & - \\ \cline{2-8}  & Playgrounds & 146 & - & - & 5 & - & 5 & 3.42 \\ \cline{2-8}  & Other barren & 7952 (876) & 38 & 2 & 375 & - & 415 & 5.22 \\ \hline \multirow{3}{*}{Inland waters} & Rivers & 45 & - & - & 2 & - & 2 & 4.44 \\ \cline{2-8}  & Lakes & - & - & - & - & - & - & - \\ \hline Coastal waters & Coastal waters & - & - & - & - & - & - & - \\ \hline \multicolumn{2}{c}{Total} & 132,786 (13,358) & 425 & 2 & 1015 & - & 1442 & 2.06 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: _Cont._