[P1-31] A Spatial Cluster Approach for Delineating Metropolitan CBD Using Big Data
Keywords:Sustainable Urban Growth Management, Big Data, CDB Boundary, Spatial Cluster Analysis
The purpose of this study is to delineate the DBD boundary of metropolitan using various big data and spatial cluster analysis methods to determine the spatial structure for sustainable urban growth and balanced regional development. Spatial cluster analysis using big data was used to define the boundaries of undefined metropolitan CDB. Building commercial use, land price, pedestrian volume, and card usage, which are indicators representing the characteristics of CBD, were used, and the spatial cluster method was applied to find areas with high CDB characteristic indicators. The final metropolitan CBD boundary was delineated by overlapping spatial cluster areas with high indicators. The boundary can be used as a boundary for measuring the centripetal force of DBD using other methodologies to analyze the influence of the city center, and the measurement results can be used for hierarchical analysis compared to other CDB measurements.