A review of research methods on the coupling relationship between urban rail transit and urban space: revealing spatiotemporal relationships through big data

Abstract

ABSTRACTUrban rail transit (URT) systems play an evident role in shaping city spatial structures; however, the principles and mechanisms behind this influence are not fully understood. This paper reviews research progress on the coupling relationship between URT and urban space, focusing on big data analysis methods and the timeliness and sequence of coupling effects. It highlights the importance of the temporal dimension in coupling analysis. By thoroughly exploiting data value and extracting key elements, big data technology imparts temporal attributes to these elements, exploring their interaction and influence mechanisms over different time sequences. The paper also discusses the potential application of big data to urban planning to support sustainable urban development. Finally, the paper outlines future research directions, including the deepened application of big data to urban spatial analysis and the role of new data sources in understanding and shaping the coupling relationship between URT and urban space. This analysis offers new perspectives and methodologies for urban development and transportation planning.

Keywords

• Urban rail transit
• urban space
• coupling relationship
• functional elements
• data approach