Abstract
ABSTRACT Although there is a need to determine the spatial accessibility of cities in China, the limitations in available data and methods hinder research in this area. The main objective of this study was to quantify the accessibility of cities in China. We developed a comprehensive analytical method to quantify spatial accessibility at a spatial resolution of one kilometer by integrating both land surface conditions and transport networks. The results show that the spatial patterns of accessibility of Chinese cities at the prefecture level and above are characterized by significant spatial heterogeneity, consistent with the patterns in physical geography, population density, and economic activities. The results improve our understanding of deficiencies in the accessibility of cities in China and provide a foundation for transportation infrastructure planning.
Highlights
The man-made and economic resources that provide the foundation for economic growth and human wellbeing are not distributed evenly across the planet
Spatial accessibility plays a key role in improving the mobility of people and goods, producing far-reaching effects on development of different regions, positive or negative
Most previous studies concentrated on the effects of land-based transport infrastructure on spatial accessibility and largely ignored the influences of different land surface conditions
Summary
The man-made and economic resources that provide the foundation for economic growth and human wellbeing are not distributed evenly across the planet. As a result of the increasing availability of high-resolution datasets and the development of spatial analytical methods in GIS, a growing number of researchers have evaluated the spatial accessibility of cities in China, at the national scale (Cao et al, 2013; Jin et al, 2017) or regional scale (Hou & Li, 2011; Wang, Liu, Liu, Sun, & Huang, 2016; Zhang & Lu, 2007). Past studies on the spatial accessibility of cities in China concentrated mainly on the effects of land-based transport infrastructure and explicitly or implicitly overlooked the influences of land surface conditions.
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