밀도기반클러스터링기법을 활용한 고용중심지 식별

다국어 초록 (Multilingual Abstract)

In urban planning, center identification has been one of the most important subjects in terms of urban growth management and efficiency. Therefore, many studies have investigated more accurate and efficient methodology in order to identify the urban center such as employment density, network concentration density and land price gradient. They have used the administrative boundary as the spatial analysis unit because almost all data are collected by it. However, it has serious limitation in detecting the accurate boundary of urban center because it is restricted within the existing administrative unit boundary. This study suggests the Density-Based Clustering (DENCLUE) method as the alternative which identifies more accurate urban center boundary. We examined pros and cons of DENCLUE method on the Gangnam subcenter identification with 9-Dong employment data. The results showed that DENCLUE can improve the accuracy of center identification and expectation power about future growth of center. In fact, the center identification results by DENCLUE are significantly different from those by the existing methods which use administrative unit.

목차 (Table of Contents)

• Abstract
• 1. 서론
• 2. 선행연구
• 3. 분석자료 및 분석방법
• 4. 분석결과
• 5. 결론
• 참고문헌

참고문헌 (Reference)

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