College of Geography and Environment, Shandong Normal University, No. 1 Daxue Road, University Science Park, Changqing District, Jinan 250358, China.
Int J Environ Res Public Health. 2022 Nov 23;19(23):15558. doi: 10.3390/ijerph192315558.
In the existing literature on the correlation between street centrality and land use intensity (LUI), only a few studies have explored the disparity of this correlation for different types of LUI and the differences across various locations. In response to the above shortcomings, in this study, the main urban area of Jinan, China, was taken as an example, and the disparity and spatial heterogeneity of the correlation between street centrality and LUI were explored for different categories of land use. The multiple centrality assessment (MCA) model was used to calculate the closeness centrality, betweenness centrality, and straightness centrality of the traffic network. Based on the floor area ratio (FAR) of each parcel, the utilization intensities of the residential, industrial, commercial, and public service land uses were measured. Employing the kernel density estimation (KDE) method, the street centrality of the traffic network vis-à-vis the urban LUI was rasterized into the same spatial analysis framework. The Pearson correlation coefficient and geographically weighted regression (GWR) were used to measure the correlation between the two variables and the spatial heterogeneity of the correlation, respectively. The results showed that traffic network street centrality strongly correlated with the LUI of the residential, commercial, and public service land use types, but it had a very weak association with the LUI of industrial land use. The GWR results also confirmed the spatial heterogeneity of the correlation. The results of this research highlighted the important role of traffic network street centrality in understanding the urban spatial structure. The study also helped to explain the dynamic mechanism of the road network form and the topological structure of urban spatial evolution.
在现有的街道中心度与土地利用强度（LUI）相关性研究文献中，仅有少数研究探索了不同类型的 LUI 之间以及不同地点之间这种相关性的差异。针对上述不足，本研究以中国济南市主城区为例，探讨了不同土地利用类型的街道中心度与 LUI 之间的差异和空间异质性。采用多中心度评估（MCA）模型计算交通网络的接近中心度、中间中心度和直线中心度。基于每个地块的建筑面积比（FAR），测算了居住、工业、商业和公共服务用地的利用强度。利用核密度估计（KDE）方法，将交通网络的街道中心度与城市 LUI 栅格化为相同的空间分析框架。采用 Pearson 相关系数和地理加权回归（GWR）分别测量了两个变量之间的相关性和相关性的空间异质性。结果表明，交通网络的街道中心度与居住、商业和公共服务用地的 LUI 呈强相关，而与工业用地的 LUI 呈极弱相关。GWR 结果也证实了相关性的空间异质性。本研究结果强调了交通网络街道中心度在理解城市空间结构中的重要作用。该研究还有助于解释路网形态和城市空间演变拓扑结构的动态机制。
