| Vol. - No. | Vol.12 - No.1 |
|---|---|
| Date | Mar., 2023 |
| Title | Classification of Metro Station Areas Using Multi-Source Big Data: Case Studies in Beijing |
| Author | Shuo Chen and Xiangyu Li+ |
| Institutions | Faculty of Architecture, Civil And Transportation Engineering, Beijing University of Technology, Beijing 100124 |
| Abstract |
Large-capacity public transportation systems, represented by urban metro lines, are the key to alleviating the significant increase in urbanization and motorization in China. But to improve the agglomeration effect of metro stations in a more accurate and targeted way requires scientific evaluation and classification of the surrounding areas of metro stations. As spatial and functional design are the core factors for urban renewal design, this study took Beijing as an example, using multi-source data to evaluate the morphology and functional composition surrounding areas of metro stations, and the Boston Consulting Group (BCG) matrix was used to classify and characterize each type of surrounding areas from morphological-functional dimensions. It shows a negative correlation of the mix-use index with the floor area ratio, and only about 20% of the areas achieve the ideal situation of high construction intensity with high mix-use diversity. Hoping to provide a reference for city managers and designers in dealing with the surrounding metro stations with different construction intensities in a more precise way. |
| Keyword | BCG Matrix, Beijing, High density, Mixed-Use, Metro Station Area, Reachable Area |
| PP. | PP.63~74 |
| Paper File |
 View |