摘要
研究充电设施的空间分布与供需匹配规律,是充电设施优化布局的关键依据,对推广绿色出行方式具有重要意义。本研究基于昆明市充电设施POI数据,运用核密度分析,网络分析和区位熵方法从空间均衡性、可达性和公平性视角测度该市充电设施空间分布格局,利用机器学习决策树模型对其进行布局优化预测,并制定提升方案。结果表明:①昆明市充电设施空间分布不均,呈主城区双核心集聚,现有设施可达性受限且围绕行政中心呈距离衰减规律。各区县充电资源配置与人口分布适配性低,社会公平性有待提升。②决策树模型表明居住类设施是昆明市充电设施选址的首要影响因素,交通、商业及办公设施共存提升了其建设适宜性,运动设施因闲置空间广也具有建站优势。③提出功能保障型、服务提升型、效能完善型的差异化布局优化策略,以期因地制宜实现优化目标。
Analyzing the spatial distribution and supply-demand matching of charging facilities provides critical evidence for layout optimization,which is essential for promoting sustainable transportation.Leveraging the Point of Interest(POI)data for charging facilities in Kunming,kernel density analysis,network analysis,and location quotient method are employed to assess the spatial distribution characteristics of charging facilities within the city from the perspectives of spatial equilibrium,accessibility,and equity.A machine learning decision tree model is applied to forecast layout optimization.Meanwhile,an enhancement plan is developed.The findings indicate:①Charging facilities in Kunming are unevenly distributed,characterized by a dual-core concentration in the central urban area.The accessibility of existing facilities is limited,exhibiting a distance-decay effect surrounding the administrative center.The distribution of charging resources does not match the population across various districts and counties,which calls for improvements in social equity.②The decision tree model identifies residential facilities as the principal factor influencing the location of charging facilities in Kunming,while the presence of transportation,commercial,and office facilities increases their suitability for development.Sports facilities present an opportunity for station construction due to the availability of extensive unused space.③Differentiated layout optimization strategies focused on securing functions,enhancing services,and improving efficiency are proposed to attain the optimization objective tailored to local conditions.
作者
谭嘉为
葛旭瑞
钱镜帆
TAN Jiawei;GE Xurui;QIAN Jingfan(Faculty of Geography,Yunnan Normal University,Kunming Yunnan 650000,China;Southwest United Graduate School,Kunming Yunnan 650092,China;Yunnan University Institute of International Relations,Kunming Yunnan 650091,China)
出处
《河北省科学院学报》
2025年第4期17-26,共10页
Journal of The Hebei Academy of Sciences
基金
云南省哲学社会科学创新团队(2023CX02)
云南省中青年学术技术带头人后备人才项目(202105AC160059)。
关键词
充电设施
POI数据
布局优化
机器学习
决策树
昆明市
Charging facilities
POI data
Layout optimization
Machine learning
Decision tree
Kunming City
