## 4 Conclusions  
Low Impact Development (LID) and Green Stormwater Infrastructure (GSI) are actively promoted in advanced countries in an effort to better manage stormwater runoff, mitigate the expansion of impervious surface areas, and minimize the adverse effects of impaired water circulation structures. In line with these trends, this study developed a method for detailed updating of high-resolution landcover map as well as high-accuracy map generation to facilitate the accurate calculation of stormwater utility fees as new financial resources capable of securing funding for LID and GSI projects. Given the inadequacy of existing Korean landcover maps for the accurate calculation of stormwater utility fees due to discrepancies between maps and actual land-use status, the upgrade method proposed here is expected to serve as a valuable basis for accurate calculation. The updated high-resolution landcover maps were updated using various spatial data, and accurate classification of landcover map items and clear boundary delineation could be performed. By additionally classifying other grassland and barren land (such as greenery within apartment complexes) as impervious surfaces, landcover could be classified in a highly detailed and accurate manner. In South Korea, notifications are absolutely mandatory when changing the use of land or completing constructions, and, among required notification items, address information should be included. If the map is updated by identifying landcover changes by the corresponding address through collection of address information and using up-to-date image data, then more effective editing, maintenance, and management of the map are possible. Such methods for updating maps would be applied in cases of artificial changes, as natural changes cannot be reflected. As urban areas mostly show artificial changes rather than natural changes, minimal effort may be required to maintain the newest traits and accuracy of the map. However, the manual updating process based on spatial data is time consuming, making it necessary to develop an automated update algorithm to address this problem. Accurate and precise landcover maps generated and updated using the method proposed in this study will greatly contribute to facilitating systematic impervious surface management. In this study, changes with time were not considered in the process of map generation; landcover changes with each hour, and change is more frequent in urban areas. Therefore, future methods should consider changes with time, as well as maintenance. After the large-scale impervious surface map is generated, the ratio of impervious surface to individual land parcel can be easily calculated by overlaying the impervious surface map with a cadastral map in GIS. These statistics can be used as basic data for suggesting plans of management and policy regarding impervious surfaces. They can be used as a major factor in urban environment management, new development plans, and selecting priority management areas for impervious surfaces. This study serves as a guide for future efforts on generating and using large-scale impervious surface maps for effective and scientific management of the urban environment. In addition, further research is needed to develop algorithms for automated pervious/impervious surface map generation based on the results of this study in order to enhance the efficiency of urban nonpoint source management. Conceptualization, J.Y. and C.L. ; methodology, J.Y. and C.L. ; validation, J.Y. and C.L. ; formal analysis, J.Y. ; investigation, J.Y. ; resources, J.Y. ; data curation, J.Y. ; writing--original \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Existing vs. First Updated** & **First vs. Second Updated** \\  & **Landcover Maps** & **Landcover Maps** \\ \hline Changed area (km\({}^{2}\)) & 25.45 & 1.04 \\ \hline Change rate (\%) & 5.47 & 0.22 \\ \hline Matching rate (\%) & 94.53 & 99.78 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of changed areas between the first and second update processes.