###### Abstract  
With a steady increase in impervious surfaces due to urbanization in Korea, there is a growing burden and an urgent need to fund better management of nonpoint sources of pollution and stormwater. A prerequisite for securing the necessary financial resources is the determination of basic data for the accurate calculation of impervious surfaces as the basis for estimating the costs of nonpoint source pollution control and billing of stormwater utility fees. This requires the extraction of landcover information in a Geographic Information System (GIS) environment and development of a landcover map that accurately delineates previous surfaces within impervious surface areas. However, since landcover maps in Korea are generated and updated at irregular intervals, it is difficult to properly track land use changes. To address this problem, this study has developed a new method for the detailed updating of landcover maps in developing urban areas to facilitate the calculation of stormwater utility fees. Sejong City was selected as the study site because it has experienced large-scale land use changes due to the recent relocation of the national administrative capital and continuous urbanization. The methodology proposed in this study is based on various spatial data such as aerial photographs and digital topographic maps and follows four process steps: preprocessing, first and second updates of landcover information, and quality assurance. In a test of this method, a total of 19,049 redclassified items were generated in the first and second updates, affecting a total area of 26.49 redkm2 within the original landcover map. The accuracy of these updates reached 99.78%, considering the changed areas and rate of change. This study provides fundamental data for further application of a stormwater utility fee policy in Korea. However, further research is required to automate the generation of accurate pervious/impervious maps and develop pertinent guidelines so that individual municipal and provincial governments can generate and update their own pervious/impervious maps as a basis for calculating the impervious surfaces in their regions. high-level landcover map; nonpoint pollution source management; spatial data; stormwater utility fee; impervious surfaces +
Footnote †: journal: Applied  
other developed countries, being hampered by variable standards among governmental departments and a lack of interdepartmental coordination. The development and implementation of a proper stormwater management plan based on the amount of impervious surface area should be preceded by the securing of resources to finance the management of nonpoint source pollution. One potential funding method is a stormwater utility fee, which can be determined by the ratio of impervious surface area to total parcel area according to the \"polluter pays\" principle [11]. Therefore, it is essential to prepare the basic data necessary for calculating the impervious surface area of a given parcel, i.e., area information by landcover class extracted in a Geographic Information System (GIS) environment and a landcover map clearly delineating pervious and impervious surfaces [12]. A landcover map is a spatial information database representing the shapes of ground objects in a given area after classification according to a set of scientific criteria and color-indexing of objects with similar characteristics. It reflects land surface features better than any other map type and hence is widely used for calculating the nonpoint source pollution load and the mapping of impervious surfaces. Intensive research has been conducted on landcover map generation for the purpose of identifying land use changes and calculating the ground surface area by land use class, in order to solve the problem of nonpoint source management and pollutant load estimation. [PERSON] et al. [13] generated landcover maps using low- and medium-resolution satellite imagery and various thematic maps, and calculated pollutant loads based on these areas by landcover class. [PERSON] et al.