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

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 expan...

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Autores principales: Shi, Ge, Shan, Jie, Ding, Liang, Ye, Peng, Li, Yang, Jiang, Nan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651249/
https://www.ncbi.nlm.nih.gov/pubmed/31261989
http://dx.doi.org/10.3390/ijerph16132318
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author Shi, Ge
Shan, Jie
Ding, Liang
Ye, Peng
Li, Yang
Jiang, Nan
author_facet Shi, Ge
Shan, Jie
Ding, Liang
Ye, Peng
Li, Yang
Jiang, Nan
author_sort Shi, Ge
collection PubMed
description 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.
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spelling pubmed-66512492019-08-07 Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City Shi, Ge Shan, Jie Ding, Liang Ye, Peng Li, Yang Jiang, Nan Int J Environ Res Public Health Article 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. MDPI 2019-06-30 2019-07 /pmc/articles/PMC6651249/ /pubmed/31261989 http://dx.doi.org/10.3390/ijerph16132318 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shi, Ge
Shan, Jie
Ding, Liang
Ye, Peng
Li, Yang
Jiang, Nan
Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City
title Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City
title_full Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City
title_fullStr Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City
title_full_unstemmed Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City
title_short Urban Road Network Expansion and Its Driving Variables: A Case Study of Nanjing City
title_sort urban road network expansion and its driving variables: a case study of nanjing city
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651249/
https://www.ncbi.nlm.nih.gov/pubmed/31261989
http://dx.doi.org/10.3390/ijerph16132318
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