Generating Natural Cities Using 3D Road Network to Explore Living Structure: A Case Study in Hong Kong

Zhiyang Xiao, Zhenhan Peng, Zidong Yu, Xintao Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


Compared with administrative cities, natural cities can be generally referred to as the areas generated based on the density of different urban facilities (e.g., point of interest, road network, etc.). To some extent, natural cities are outperformed in some related urban studies, such as urban living structure analysis. Nevertheless, traditional ways of generating natural cities are mostly limited to the planar space. Modern cities such as Hong Kong are vertical cities with high buildings, 3D road networks and land uses. Therefore, traditional nature cities could be biased when applied to 3D cities. In this work, a 3D road network in Hong Kong is adopted to extract true road intersections and generate modified natural cities to explore urban living structures. Numerous living structure units are classified into two parts: tiny and serried ones representing natural cities and vast ones representing rural areas. The classification method applies head/tail breaks, and a clustering algorithm was fitted for heavy-tailed distribution. According to the living structure theory, the living structures of the proposed natural cities and traditional natural cities based on the same road network in Hong Kong are compared. The findings show that the distribution of modified natural city regions is more reasonable compared with typical ones. The improved model will more clearly show the inherent living structure of the city and will allow an analysis of the relationship between the part and wholeness of the city.

Original languageEnglish
Pages (from-to)1485-1506
Number of pages22
JournalSmart Cities
Issue number3
Publication statusPublished - Jun 2023


  • complex system
  • head/tail breaks
  • living structure
  • natural cities

ASJC Scopus subject areas

  • Urban Studies
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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