摘要
近年来高铁站已成为城市交通枢纽和经济发展的重要动力,然而站点和周边地区空间开发隶属于不同部门,铁路部门和地方政府存在分割,站城融合度并不高。路网是城市的骨架,是城市及区域良好发展的基础,以中日6个高铁站域为研究对象,采用空间句法和地理信息系统(Geographic Information System,GIS)软件对比分析不同路网结构。研究发现,中国低密度大路网与日本高密度小路网在路网密度、可达性、便捷性及空间感知方面差异较大,不同路网结构的空间感知能力强弱依次为混合式、方格式、自由式,东京站站域的混合式路网空间感知最好。通过对比分析中日高铁站域路网结构的差异,为国内新建高铁站路网规划和已建成高铁站的路网优化提供参考。
In recent years,high-speed railway stations have become urban transportation hubs and important driving forces for economic development.However,in China,the spatial development of stations and surrounding areas is subordinate to different departments,and railway departments are separated from local governments,so the integration degree of stations and cities is not high.Road network is the skeleton of a city and the basis for the good development of a city and a region.Taking six high-speed railway stations in China and Japan as the research object,this paper uses space syntax and GIS software to compare and analyze different road network structures.It is found that there are great differences between China′s low-density large road network and Japan′s high-density small road network in terms of road network density,accessibility,convenience and spatial perception.The spatial perception ability of different road network structures is in order of hybrid,square format and freestyle,and Tokyo station has the best spatial perception of hybrid road network.By comparing and analyzing the differences of network structure of high-speed railway stations between China and Japan,this paper aims to provide reference for network planning of new high-speed railway stations and network optimization of existing high-speed railway stations in China.
作者
桂汪洋
李成成
GUI Wangyang;LI Chengcheng(School of Architecture&Urban Planning,Anhui Jianzhu University,Hefei 230601,China)
出处
《沈阳建筑大学学报(社会科学版)》
2023年第2期186-194,共9页
Journal of Shenyang Jianzhu University:Social Science
基金
国家自然科学基金项目(51708099)
安徽省住房城乡建设科学技术计划项目(2020-YF27)。
关键词
高铁站域
路网结构
空间感知
感知差异
high-speed railway station area
road network structure
spatial perception
perception differences