| 摘要: |
| 多中心作为一项城市发展战略，已逐渐
受到国内外大都市区的广泛认可。基于集聚—分
散维度和单中心—多中心维度理论，结合百度热
力图等人口空间化数据，提出能够客观反映不同
大都市区多中心空间结构差异性的测度方法和
量化指标——多中心指数（PI）。建立轨道交通
系统对多中心指数的多元线性回归模型，以全国
40个已开通运营轨道交通的大都市区作为实证
研究对象，探索轨道交通系统对大都市区多中心
空间结构的影响效应。研究发现，在控制了道路
交通、人口就业和经济发展等因素的影响下，轨
道交通系统通过线网规模、线网结构以及站点
布局对大都市区的多中心空间结构产生显著影
响，但影响的正负取决于近远郊圈层的轨道交
通发展水平。通过科学规划和系统建设，提高
近远郊线网比重、次中心TOD耦合度以及轨道
网密度，可以显著提高我国大都市区多中心空间
结构的发展水平。 |
| 关键词: 大都市区 空间结构 轨道交通 多中
心 热力图 |
| DOI：10.13791/j.cnki.hsfwest.20230115 |
| 分类号: |
| 基金项目:天津市哲学社会科学规划项目（TJGLQN22-005） |
|
| Influence of Rail Transit System on Polycentric Spatial Structure in Metropolitan Area |
|
YANG Jiaxuan,YUN Yingxia,REN Lijian
|
| Abstract: |
| As an urban development strategy, polycentricity has been recognized widely both in
Chinese and foreign metropolitan areas. Based on the theory of monocentricity-polycentricity
dimension and centralizaition-dispersion dimension, using spatialized population data such as
Baidu heatmap, this paper introduces a new measure of polycentric spatial structure difference in
metropolitan area and a new index: polycentricity index (PI). Polycentricity index can improve the
objectivity and comparability of measurement of polycentric spatial structure, which is helpful
for related quantitative research and horizontal comparison of polycentric spatial structure in
metropolitan areas. This study builds a multiple linear regression model of PI to explore the influence
of rail transit system on polycentric spatial structure in metropolitan area, using panel data of 40
metropolitan areas with rail transit as the empirical research objects in China. The results indicate
that the rail transit system has significant impacts on polycentric spatial structure in metropolitan
area in terms of the scale and structure of rail network, the distribution of rail stations, when the road
traffic, the population, the employment and the economic development factors have been controlled.
However, whether the impacts are positive depends on the development level of rail transit in
suburban circle of metropolitan area.
Firstly, in terms of the scale of rail network, PI is highly dependent on operating length and rail
network density, which regression coefficients are -0.421 5 and 0.355 6, and both are significant at the
level of 0.01, indicating that the scale of rail network can significantly affect the polycentric spatial
structure in metropolitan areas. Among them, the density of rail network has positive and significant
impacts on polycentric spatial structure, indicating that increasing the density of rail network will
promote the development and evolution of polycentric spatial structure in metropolitan areas in
China, which is consistent with previous research conclusion. On the contrary, the operating length
has significant negative impacts on polycentric spatial structure, indicating that simply increasing
the operating length cannot significantly affect the development of polycentric spatial structure. If
only paying attention to the main center and neglecting the suburbs, it will inhibit the development
of polycentricity and intensify the spread of monocentricity in metropolitan areas.
Secondly, in terms of the structure of rail network, the proportion of suburban network reflects
the spatial layout of rail network, and the proportion of subway network reflects the multi-level
structure of rail network. The empirical test results show that the proportion of suburban network
has significant positive impacts on polycentric spatial structure, which is consistent with previous
studies; the proportion of subway network also has certain positive impacts, but not significant, and
it is eliminated in the stepwise regression analysis, which is different from previous studies. This is
because the construction of rail transit relies on subway too much, accounting for 76.9% in China.
Most metropolitan areas have not formed a multi-mode & multi-level rail transit system.
Thirdly, in terms of the distribution of stations, both the density of stations in main center
and the coupling of secondary centers TOD have significant positive impacts on polycentric spatial
structure. Among them, PI has the highest dependence on the coupling of secondary center TOD,
which is 0.315 1, and is significant at the level of 0.01, indicating that the greater proportion of
population centers within 100 0-meter service radius of rail stations located in suburbs, the higher PI.
This is consistent with the TOD model theory, the more concentrated population of rail stations, and
the higher level of coupling with secondary centers, the more useful to polycentric spatial structure.The dependence of PI on the density of stations in main center is only 0.098 7, but it is also significant at the level of 0.1, indicating that the denser rail
stations in main center, and the stronger ability to gather population, the higher level of polycentric spatial structure. It also reflects the theoretical consensus
that polycentricity is not equal to no-centricity, and conforms to the hypothesis of idealized polycentric spatial structure in this article.
Through scientific planning and system construction, increasing the proportion of suburban rail network, the coupling of secondary center TOD and
the density of rail network can significantly improve the development level of polycentric spatial structure in metropolitan areas in China. These conclusions
have important enlightenment for the planning and construction of rail transit and the optimization of metropolitan spatial structure. |
| Key words: Metropolitan Area Spatial Structure Rail Transit Polycentricity Heat Map |
