多源数据下电动汽车充电站空间分布与地铁站锚点效应的关系研究

Research on the Relationship between the Spatial Distribution of Electric Vehicle Charging Stations and the Anchor Effect of Subway Stations Based on Multi-Source Data

摘要: 随着中国新能源汽车产业的迅猛发展，充电基础设施布局合理性成为制约其推广的关键。研究以徐州市中心城区为案例，探究城市轨道交通(地铁)站点对电动汽车充电站空间分布的引力作用。综合运用GIS空间分析(渔网分析、核密度估计、叠加分析)以及数理统计(相关性分析)模型，对693个充电站POI数据与地铁网络进行多维度解析。研究发现：1) 徐州市充电站空间分布呈现显著的“核心–边缘”结构，形成多中心集聚与轴向延伸格局，存在服务盲区与过度集中并存的问题；2) 充电站与地铁站点存在显著的空间耦合性与统计相关性，强有力地验证了轨道交通锚点效应的存在；3) 充电站与商圈POI的重合度高达61.4%，并且“到地铁站距离”与“商场密度”的交互作用对充电站密度解释力最高。验证了地铁站对于电动汽车充电站的锚点效应，应是未来布局优化的优先区域。研究结论可为高密度城市充电基础设施的精准布局与优化提供科学依据和决策支持，也为后续建立“交通–能源–用地”一体化配置模型奠定案例基础。

Abstract: With the rapid development of China’s new energy vehicle (NEV) industry, the rational layout of charging infrastructure has become a key constraint to large-scale adoption. Taking the central urban area of Xuzhou as a case study, this research investigates the spatial attraction of urban rail transit (metro) stations on the distribution of electric vehicle (EV) charging stations. A combination of GIS spatial analyses (fishnet analysis, kernel density estimation, and overlay analysis) and statistical models (correlation analysis) is employed to examine 693 charging station POIs in relation to the metro network. The results reveal that: 1) EV charging stations exhibit a distinct “core-periphery” structure, forming a multi-centered and axis-oriented pattern with both service gaps and over-concentration areas; 2) Charging stations show significant spatial coupling and statistical correlation with metro stations, confirming the existence of a rail transit anchor effect; 3) The overlap rate between charging stations and commercial POIs reaches 61.4%, and the interaction between “distance to metro stations” and “commercial density” provides the highest explanatory power for charging station density. The findings demonstrate that metro station areas should be prioritized in future layout optimization. This study offers empirical support for the precise planning of charging infrastructure in high-density cities and provides a foundation for developing integrated “transport-energy-land use” configuration models.