Spatiotemporal characteristics of Chinese metro-led underground space development: A multiscale analysis driven by big data

Nowadays, the use of metro-led underground spaces (MUS) has become imperative in high-density urban environments. However, a comprehensive and systematic understanding of MUS development patterns in denselypopulated countries like China is still lacking. Therefore, this study employed a data-driven spatiotemporal analytical framework based on multisource big data to investigate the development mechanism of Chinese MUSs using a full sample. The multiscale analysis, covering MUS, urban, and regional scales, was conducted to identify the driving forces of MUS development over five temporal stages. The results revealed that the development characteristics of Chinese MUSs varied across different spatiotemporal contexts. At the micro level, the primary driving factors, including density, diversity, distance to transit, and destination accessibility, had a strong explanatory power, which is consistent with the mainstream transit-oriented development (TOD) theory. At the macro level, the main drivers included economic factors, environmental factors, and development scale factors. This study provides new insights for MUS development in high-density regions worldwide, and the obtained regularities could be effectively adopted in the planning and design for MUS.