Evaluating the performance of transit-oriented development in Beijing metro station areas: Integrating morphology and demand into the node-place model

Cong Liao and Bronte Scheuer

Journal of Transport Geography, 2022, vol. 100, issue C

Abstract: Transit-oriented development (TOD) is being promoted as a promising development strategy to integrate transit and land use around public transportation stations. The node-place model provides a useful framework to evaluate the performance of TOD by focusing on the balancing of node and place characteristics. Although the demand characteristics in station areas reflects current development situation and hierarchical status at the station level and regional level respectively, which promotes the reshaping of urban spatial structures, the demand related factors have rarely been systematically incorporated into the node-place model in previous studies compared to various morphological factors used in TOD evaluation. In this study, the demand related factors derived from multi-source geotagged big data in ‘Transit’, ‘Development’ and ‘Interaction’ dimensions of TOD are implemented into the node-place model. Metro station areas in Beijing were used as the case study area and were classified using K-means clustering method based on combination of both demand and morphology indicators. Our results show that the performance of TOD in station areas in terms of demand and morphology do not necessarily match well, especially for ‘Transit’ and ‘Interaction’ dimensions. The five identified types with different TOD characteristics based on demand factors indicate three levels of station areas (large, medium and small) in Beijing. The seven identified types based on both morphological and demand factors provide a more comprehensive characterization of TOD station area. We suggest adding demand factors to the node-place model to better assess the existing level of station areas.

Keywords: TOD typologies; Transport accessibility; Geotagged big data; Clustering analysis (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:100:y:2022:i:c:s0966692322000564

DOI: 10.1016/j.jtrangeo.2022.103333

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