Spatial-temporal fractal of urban agglomeration travel demand
Zhengbing He
Physica A: Statistical Mechanics and its Applications, 2020, vol. 549, issue C
Abstract:
In modern society, an urban agglomeration is a highly developed spatial form of integrated cities. Travel activities driven by various travel demands frequently take place within an urban agglomeration. Understanding urban agglomeration travel demand is a basic but significant task. The paper constructs spatial–temporal networks for urban agglomeration travel demand via spatial–temporal decomposition and makes explicit analyses of the attributes of the networks. Taiwan and taxi demand, which are a typical urban agglomeration and representative travel demand, respectively, are taken as the empirical objects of the study. It is found that the degree distributions of the spatial–temporal travel demand networks follow power laws, whose exponents monotonically decrease with the growth of the square cells that are used to divide an urban agglomeration to aggregate travel demand. Nevertheless, the fact of following power laws is not influenced by the spatial–temporal granularity of network construction, indicating a spatial–temporal fractal property of urban agglomeration travel demand. The findings contribute to understanding the nature of travel demand and human mobility in the scale of an urban agglomeration.
Keywords: Urban agglomeration; Travel demand; Spatial–temporal network; Power law; Taxi trip (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437120302211
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:549:y:2020:i:c:s0378437120302211
DOI: 10.1016/j.physa.2020.124503
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().