The built environment dimensions of stationary activities in volumetric TOD station service areas : a multi-source urban data approach

Abstract

This study investigates the relationship between Built Environment (BE) dimensions, volumetric station spatial configuration, and stationary activities within Transit-Oriented Development (TOD) station service areas in the rapidly growing megacity of Shenzhen, China. Despite the importance of promoting inviting urban public spaces in TOD planning policies, research on the emerging phenomenon of volumetric station service area spatial configuration and its relation to stationary activities remains scarce. The original research contribution lies in examining the multi-scale relationships between BE dimensions of urban rail service areas, volumetric station spatial configuration, and people's stationary activities, using Shenzhen as a case study.

A multi-scale, multi-source approach incorporating indoor and outdoor urban data, Network Science, Machine Learning, and on-site surveys are employed to better understand these relationships across macro, meso, and micro spatial scales.

At the macro-scale, the study investigates the BE characteristics and factors influencing volumetric station spatial distribution for 236 existing stations in 2021, exploring development context and distribution patterns.

At the meso-scale, it examines the characteristics of 35 volumetric station service areas in relation to stationary activities, comparing them to non-volumetric stations and analyzing spatiotemporal patterns.

Finally, at the micro-scale, it scrutinizes three contrasting case studies of volumetric station service areas, assessing their detailed BE variables and their relationship with stationary activities.

This exploratory study offers valuable insights into the multi-scale relationships between volumetric station service area locational propensity, built environment spatial configuration, and people's stationary activities in a fast-growing, subtropical megacity. It highlights the significant roles of development phases, road and metro network dimensions, urban form, densities, and 3D vertical and horizontal spatial integration in relation to stationary activities. The research emphasizes the importance of adopting a multi-scale, multi-source approach, including Network Science, Machine Learning, and on-site surveys, to better understand the complex dynamics between volumetric station service areas and stationary activities. The findings from this study can inform urban design and planning strategies needed to implement recent volumetric station service area policy and design guidance, leading to effective BE configuration for SA in TOD VSSA. This research contributes to enhancing urban livability and fostering a healthier, more sustainable future for cities.