Identifying Urban structure based on transit-oriented development

Yingqun Zhang, Rui Song*, Rob van Nes, Shiwei He, Weichuan Yin

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

21 Citations (Scopus)
38 Downloads (Pure)

Abstract

The fast development of urbanization has led to imbalances in cities, causing congestion, pollution, and urban sprawl. In response to the growing concern over the distribution of demand and supply, a more coordinated urban structure is addressed in comprehensive planning processes. In this study, we attempt to identify urban structure using a Network-Activity-Human model under the Transit-Oriented Development (TOD) concept, since TOD is usually regarded as an urban spatial planning tool. In order to explore the strengths and weaknesses of the urban structure, we define the TOD index and unbalance degree and then classify the urban areas accordingly. We take the city of Beijing as a case study and identify nine urban types. The results show a hierarchical urban structure: the city center covers most of the hotspots which display higher imbalances, the surroundings of the city center are less developed, and the city edges show higher potentials in both exploitation and transportation development. Moreover, we discuss the extent to which the spatial scale influences the unbalance degree and apply a sensitivity analysis based on the goals of different stakeholders. This methodology could be utilized at any study scale and in any situation, and the results could offer suggestions for more accurate urban planning, strengthening the relationship between TOD and spatial organization.
Original languageEnglish
Article number7241
Number of pages21
JournalSustainability
Volume11
Issue number24
DOIs
Publication statusPublished - 2019

Keywords

  • Activity
  • Human
  • Imbalance
  • TOD
  • Transportation network
  • Urban structure

Fingerprint

Dive into the research topics of 'Identifying Urban structure based on transit-oriented development'. Together they form a unique fingerprint.

Cite this