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Spatial inequality of bus transit dependence on urban streets and its relationships with socioeconomic intensities: A tale of two megacities in China

机译:公交公交交通依赖城市街道的空间不等式及其与社会经济强度的关系:中国两种兆的故事

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The dependence of urban bus transit on their covered streets is expected to be significant and heterogeneous in megacities. Using a bipartite network approach, we develop several weighted centrality-based connectivities to quantify the degree of dependencies of urban bus transit on streets. Two megacities with different road patterns, i.e., Beijing and Shanghai in China are taken as examples to depict comparatively spatial inequalities of the centrality-based dependencies at both local and global scales. Then, a series of spatial cross-section regression models are introduced to explore the colocation relationships between the dependencies of bus transit and urban socioeconomic intensities. The methodology of kernel density estimation (KDE) is used to convert all data with different scales into the same unit of measurement. Results indicate that there are significant statistical and spatial inequalities of the centrality-based dependencies of bus transit on urban streets. These inequalities with evident hierarchies, variances and clusters were validated by statistical analysis including power-law function, rank-size distribution, multiple variance indices, together with Global Moran's I. Besides, a majority of bus transit rely heavily on minor streets concentrating on circumferential expressways in central urban areas and radial highways oriented to outer suburbs under industrial or residential suburbanization. The unequal distribution is found to be strongly related to population, nighttime light intensity, transport-related services, and commercial and leisure services by the spatial regression models. A good spatial matching between bus routes' dependencies and socioeconomic activities intensities is found both in these two megacities.
机译:城市巴士运输在其覆盖街道上的依赖预计在巨大的巨大性中是显着和异质的。使用二分网络方法,我们开发了几个加权基于中心的连接性,以量化街道上城市公交车辆的依赖程度。中国北京和上海的两种巨大的巨型特征被视为示例,以描绘在本地和全球范围内基于中心的依赖性的相对空间不等式。然后,引入了一系列空间横截面回归模型,以探索公交交通和城市社会经济强度的依赖关系之间的主导关系。内核密度估计(KDE)的方法用于将具有不同尺度的所有数据转换为同一单位的测量单元。结果表明,城市街道上总线依赖性的基于中心依赖性的显着统计和空间不平等。通过统计分析验证了具有明显等级,差异和集群的这些不等式,包括幂律函数,秩规模分布,多个方差指数以及全球莫兰的I.此外,大多数公交车际依赖于圆周的小街道在中央城区的高速公路和径向高速公路面向工业或住宅郊区化下的外郊区。发现不等的分布与空间回归模型的人口,夜间光线强度,运输相关服务和商业和休闲服务强烈相关。在这两种巨大的巨型城市都发现了公交路线之间的良好空间匹配和社会经济活动的强度。

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