GIS 네트워크분석을 활용한 도시철도역 주변지역 상업시설 입지분포패턴 추정 연구- 서울시 도시철도 2호선 신림역을 사례로 - (A Study on the Distribution Pattern of Commercial Facilities around a Subway Station Using GIS Network Analysis - Focused on Sillim Station of Seoul Subway Line 2 -)

The purpose of this study is to estimate the distribution pattern of commercial facilities around Sillim subway station in the City of Seoul during the period between 2010 and 2020. To conduct the task, this study analysed the relationship between the distribution pattern of commercial facilities and the floating population at the station. This study set up a method to estimate the commercial area around the station using the network analysis of ArcGIS 10.0. According to the result of the analysis, the buildings for commercial purpose occupy 66% from the total building units in the estimated area in 2000 and indicate 67% in 2010. Furthermore, 6% of the total building units in the area estimated in the base year of 2010 would be converted to commercial building in 2020, if the floating population in the area would be enlarged to 120% of 2010. This amounts to 64 building units. So, this study can provide an important empirical result for decision makers to quantitatively anticipate the impact of a public transport policy. The methodology developed for the study is able to be applied to the other subway stations as well.

The purpose of this study is to estimate the distribution pattern of commercial facilities around Sillim subway station in the City of Seoul during the period between 2010 and 2020. To conduct the task, this study analysed the relationship between the distribution pattern of commercial facilities and the floating population at the station. This study set up a method to estimate the commercial area around the station using the network analysis of ArcGIS 10.0. According to the result of the analysis, the buildings for commercial purpose occupy 66% from the total building units in the estimated area in 2000 and indicate 67% in 2010. Furthermore, 6% of the total building units in the area estimated in the base year of 2010 would be converted to commercial building in 2020, if the floating population in the area would be enlarged to 120% of 2010. This amounts to 64 building units. So, this study can provide an important empirical result for decision makers to quantitatively anticipate the impact of a public transport policy. The methodology developed for the study is able to be applied to the other subway stations as well.