Agglomeration centrality examination of cities: an urban transport perspective

Cities are complicated dynamic systems that result in the agglomerations of streets, population and socioeconomic activities. In this paper, the authors use the partition method of regular grid model to divide a city into small areas, and introduce the concept of agglomeration centrality for describing agglomeration characteristics of local areas in a city. A new measure of agglomeration centrality is defined considering the penetrability of roads within a local area from the 2-dimension plane perspective. Based on this, the authors introduce the concept of overall agglomeration intensity to illustrate the agglomeration pattern of the city from macro level. Experiments on a set of cities show that the agglomeration centrality distribution of local areas in a city present a power law phenomenon. Besides, the results reveal a crucial important phenomenon that the power law exponent is related to city area and partition scale. The exponent can be described using a power function with two terms and has an upper limit. Moreover, the authors find that the overall agglomeration intensity indicator is useful to reflect the spatial agglomeration pattern of street networks. In summary, this study develops a new centrality measure from 2-dimension perspective and demonstrates its effectiveness for understanding the spatial agglomeration pattern of cities.

• Record URL:
  https://doi.org/10.1016/j.scs.2020.102273
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S2210670720304947
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/22106707
• Supplemental Notes:
  • © 2020 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Liu, Gang
  • 0000-0002-8856-8746
  • Yao, Xiaobai
  • Fan, Qinjin
• Publication Date: 2020-10

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Serial:
  • Sustainable Cities and Society
  • Volume: 61
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2210-6707
  • Serial URL: http://www.sciencedirect.com/science/journal/22106707?sdc=2

Subject/Index Terms

• TRT Terms: Cities; Grids (Coordinates); Mathematical models; Networks; Spatial analysis; Streets
• Subject Areas: Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01743727
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 23 2020 12:30PM