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Open AccessArticle

Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City

by Ge Shi 1,2,3,4, Jie Shan 2,*, Liang Ding 5,6, Peng Ye 1,3,4, Yang Li 1,3,4 and Nan Jiang 1,3,4,*
1
School of Geographic Science, Nanjing Normal University, Nanjing 210046, China
2
Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall, West Lafayette, IN 47907, USA
3
Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210046, China
4
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
5
College of Computer and Information, Hohai University, Nanjing 210098, China
6
Information Center of Jiangsu Natural Resources Department, Nanjing 210017, China
*
Authors to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(13), 2318; https://doi.org/10.3390/ijerph16132318
Received: 14 May 2019 / Revised: 25 June 2019 / Accepted: 27 June 2019 / Published: 30 June 2019
(This article belongs to the Special Issue Spatio-Temporal Environmental Monitoring and Social Sensing)
Developing countries such as China are undergoing rapid urban expansion and land use change. Urban expansion regulation has been a significant research topic recently, especially in Eastern China, with a high urbanization level. Among others, roads are an important spatial determinant of urban expansion and have significant influences on human activities, the environment, and socioeconomic development. Understanding the urban road network expansion pattern and its corresponding social and environmental effects is a reasonable way to optimize comprehensive urban planning and keep the city sustainable. This paper analyzes the spatiotemporal dynamics of urban road growth and uses spatial statistic models to describe its spatial patterns in rapid developing cities through a case study of Nanjing, China. A kernel density estimation model is used to describe the spatiotemporal distribution patterns of the road network. A geographically weighted regression (GWR) is applied to generate the social and environmental variance influenced by the urban road network expansion. The results reveal that the distribution of the road network shows a morphological character of two horizontal and one vertical concentration lines. From 2012 to 2016, the density of the urban road network increased significantly and developed some obvious focus centers. The development of the urban road network had a strong correlation with socioeconomic and environmental factors, which however, influenced it at different degrees in different districts. This study enhances the understanding of the effects of socio-economic and environmental factors on urban road network expansion, a significant indicator of urban expansion, in different circumstances. The study will provide useful understanding and knowledge to planning departments and other decision makers to maintain sustainable development. View Full-Text
Keywords: urbanization; road network; PM2.5; spatial patterns; geographically weighted regression; Nanjing urbanization; road network; PM2.5; spatial patterns; geographically weighted regression; Nanjing
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Shi, G.; Shan, J.; Ding, L.; Ye, P.; Li, Y.; Jiang, N. Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City. Int. J. Environ. Res. Public Health 2019, 16, 2318.

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