Quantitative Evaluation of TOD Performance Based on Multi-Source Data: A Case Study of Shanghai

Abstract

Transit-oriented development (TOD) has been widely adopted as a primary urban planning strategy to better integrate transit and land use; further, the pedestrian-oriented perspective has been receiving increasing attention. However, most studies so far have only focused on few features and fail to capture comprehensive perceptions in the transportation (T), pedestrian-oriented accessibility (O), and urban development (D) dimensions. New emerging urban datasets provide a more refined and systematic approach to quantify the characteristics of metro station areas. This study offers a more efficient and convenient process and comprehensive approach to measure TOD performance. With a combination of traditional data collected by an official department, high-resolution open data, and innovative technology, large-scale analyses of 347 metro stations in Shanghai were conducted. Fifteen indicators for T, O, and D were chosen to categorize TOD performance into five clusters. Radar charts, boxplots, and colored maps were used to display numerous quantitative factors for each type. Combining the results with the Shanghai Comprehensive Plan (2017–2035) showed that the majority of Cluster 4 is located at the center of the Five New Towns. The correlation analysis between ridership and TOD performance showed that the transportation dimension indicator has a strong correlation with daily ridership, followed by the O and D indicators. Moreover, ridership per capita was found to be affected by resident density, employment density, O value, and D value, whereas no significant correlation was found between ridership per capita and T value. Population plays a pivotal role in metro passenger traffic, indicating ridership per capita had a high, strong correlation with resident density, with R = 0.658 for weekdays and R = 0.654 for weekends. This study reinterpreted the node-place method and 5Ds framework, resulting in a renewal method with new datasets and analysis tools. It contributes to providing pedestrian-oriented TOD planning methodology for urban planners and policymakers by combining T, O, and D dimensions and visualizing the results with current urban planning.

Measuring metro station area's TODness: An exploratory study of Shenyang based on multi‐source urban data

“…We initially collected 74 indicators of "Transit," "Oriented," and "Development" from the worldwide TOD literature to build and implement our expanded node-place model (Figure 3). Based on previous studies (Kamruzzaman, Baker, et al, 2014;Lyu et al, 2016;Qiang et al, 2022;Singh et al, 2017;Sung & Oh, 2011;Vale, 2015;Zhang et al, 2022;Zhou et al, 2019) Furthermore, the indicators must be quantifiable using information available to the general public. The number of indications for each type of TOD was equal.…”

“…This difference is mainly reflected in the following four aspects. First, Shenyang's MSAs have a lower O Index (Figure 8) than cities with advanced metro networks (Qiang et al, 2022),…”

Evaluation of indicators of railway-induced annoying vibration based on building measurements developed by TOD: a discussion

“…In recent years, under the guidance of the Transit-Oriented Development (TOD) model [1], it has become a new trend to develop over-track buildings on metro depots [2][3][4]. Along with enhancing the utilization rate of urban land [5], the over-track building also contributes to the construction and maintenance budget for the subway. However, the vibrations generated by the frequent operations of the trains in early morning and late night annoy the building residents [6,7].…”

TOD and vibrancy: The spatio-temporal impacts of the built environment on vibrancy

“…Since the 21st century, with rapid urbanization and urban rail transit construction, TOD has become an important concept that guides urban development and enhances urban vibrancy in China (Yang et al, 2022a;Qiang et al, 2022). TOD transit nodes are generally located in developed areas with multiple functions such as transportation, commerce, resident, and office.…”