Understanding uneven urban expansion with natural cities using open data

Ying Long, Weixin Zhai, Yao Shen, Xinyue Ye

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

The last several decades have witnessed a rapid yet uneven urban expansion in developing countries. The existing studies rely heavily on official statistical yearbooks and remote sensing images. However, the former data sources have been criticized due to its non-objectivity and low quality, while the latter is labor and cost consuming in most cases. Recent efforts made by fractal analyses provide alternatives to scrutinize the corresponding “natural urban area”. In our proposed framework, the dynamics of internal urban contexts is reflected in a quasi-real-time manner using emerging new data and the expansion is a fractal concept instead of an absolute one based on the conventional Euclidean method. We then evaluate the magnitude and pattern of natural cities and their expansion in size and space. It turns out that the spatial expansion rate of official cities (OCs) in our study area China has been largely underestimated when compared with the results of natural cities (NCs). The perspective of NCs also provides a novel way to understanding the quality of uneven urban expansion. We detail our analysis for the 23 urban agglomerations in China, especially paying more attention to the three most dominating urban agglomerations of China: Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD). The findings from the OC method are not consistent with the NC method. The distinctions may arise from the definition of a city, and the bottom-up NC method contributes to our comprehensive understanding of uneven urban expansion.

Original languageEnglish (US)
Pages (from-to)281-293
Number of pages13
JournalLandscape and Urban Planning
Volume177
DOIs
StatePublished - Sep 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Ecology
  • Nature and Landscape Conservation
  • Management, Monitoring, Policy and Law

Keywords

  • China
  • Head/tail division
  • New data
  • Open data
  • Social media
  • Urban expansion

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