Journal of Urban Management (Dec 2015)

Density and diversity of OpenStreetMap road networks in China

  • Yingjia Zhang,
  • Xueming Li,
  • Aiming Wang,
  • Tongliga Bao,
  • Shenzhen Tian

DOI
https://doi.org/10.1016/j.jum.2015.10.001
Journal volume & issue
Vol. 4, no. 2
pp. 135 – 146

Abstract

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OpenStreetMap is a geographic information platform designed to provide real-time updates and user-generated content related to its freely available global map, and it is one of the most widely used examples of volunteered geographic information, a technique associated with so-called neogeography. This paper, based on the data from China’s OpenStreetMap road network in May 2014, taking 340 prefecture-level cities in China as its study area, presents the geometric-related (road density) and attribute-related (type diversity) spatial patterns of the OpenStreetMap road network, and explores their relationship. The results are as follows. (1) The distribution of OpenStreetMap road density in Shenzhen, Shanghai, Hong Kong, and Macao predominantly obeys a “positive skewness distribution”. OpenStreetMap data for eastern China shows a higher overall and circular structure. In central China, there are noticeable discrepancies in the road density, whereas in western China, the road density is low. (2) The OpenStreetMap road diversity shows a normal distribution. The spatial pattern for the so-called “Hu Huanyong line” was broken by the effect of diplomatic and strategic factors, showing a high diversity along the peripheral border, coastal cities, and core inland cites. (3) China’s OpenStreetMap is partitioned into four parts according to road density and diversity: high density and high diversity; low density and low diversity; high density and low diversity; and low density high diversity. (4) The OpenStreetMap geographical information-collection process and mechanism were analyzed, demonstrating that the road density reflects the preponderance of traffic in the real world. OpenStreetMap road diversity reflects the road-related geographic information demand and value, and it also reflects the interests of users toward to OpenStreetMap geographical information.

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