Article(id=1308454748932296824, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308454712513156008, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1672-6073.2026.04.007, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1778688000000, receivedDateStr=2026-05-14, revisedDate=1782316800000, revisedDateStr=2026-06-25, acceptedDate=null, acceptedDateStr=null, onlineDate=1789889522059, onlineDateStr=2026-09-20, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789889522059, onlineIssueDateStr=2026-09-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789889522059, creator=13701087609, updateTime=1789889522059, updator=13701087609, issue=Issue{id=1308454712513156008, tenantId=1146029695717560320, journalId=1146123302524792850, year='2026', volume='39', issue='4', pageStart='1', pageEnd='197', issueExtLink='null', onlineDate='null', pubDate='1786291200000', pubDateStr='2026-08-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1789889513376, creator='13701087609', updateTime=1789889839088, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308456079029986178, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308454712513156008, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308456079029986179, tenantId=1146029695717560320, journalId=1146123302524792850, issueId=1308454712513156008, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=59, endPage=72, ext={EN=ArticleExt(id=1308454749217509497, articleId=1308454748932296824, tenantId=1146029695717560320, journalId=1146123302524792850, language=EN, title=Urban Rail Transit Station-area Types and Scenario Differences Based on the Node-Place-Vitality Model, columnId=1308454713645618089, journalTitle=Urban Rapid Rail Transit, columnName=Special Feature: 200th Issue, runingTitle=null, highlight=null, articleAbstract=

To address the limitation of the traditional Node-Place model in capturing actual passenger-flow vitality and its variation across travel scenarios, this study introduces a vitality dimension and develops a Node-lace-vitality model to identify urban rail transit station-area types and examine their differences across travel scenarios. Taking 211 urban rail transit stations in Xi'an as the sample, this study integrates multi-source data, including rail transit network topology, station facilities, feeder transport services, built environment characteristics, population activities, point of interest (POI) functional facilities, and hourly origin-destination (OD) ridership. An evaluation indicator system covering the three dimensions of node, place, and vitality is established. A combined weighting method is used to determine indicator weights, and a Gaussian mixture model is applied to identify station-area types under workday and National Day holiday scenarios. The transition characteristics of station-area types across different scenarios are then analyzed. The results show that the node, place, and vitality scores of Xi'an rail transit stations generally exhibit a spatial pattern of "high values in the central urban area and low values along peripheral lines". Under the National Day holiday scenario, some stations show a significant increase in passenger flow vitality. The station areas can be classified into five types: hub-integrated stations, station-city coordinated stations, vitality-responsive stations, place-supporting stations, and basic-cultivation stations. Their spatial distribution presents a clear concentric pattern characterized by "central agglomeration and peripheral differentiation". Station-area types remain generally stable between workday and holiday scenarios. Among the 211 stations, 192 stations retain the same type, accounting for 91.00%, while 19 stations experience type transitions, accounting for 9.00%. These transitions mainly occur between place-supporting stations and basic-cultivation stations, and are primarily distributed outside the Second Ring Road. The findings provide a scientific basis for station-area functional optimization, peripheral station cultivation, differentiated development under the Transit-Oriented Development (TOD) framework, and refined rail transit operations management.

, authors=Qushun Wang, Zhuanglin Ma, Cuihua Zhang, Shengrui Zhang, authorsList=Qushun Wang, Zhuanglin Ma, Cuihua Zhang, Shengrui Zhang, authorCompany=null, correspAuthors=Zhuanglin Ma, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1308454749464973434, articleId=1308454748932296824, tenantId=1146029695717560320, journalId=1146123302524792850, language=CN, title=基于节点-场所-活力模型的城市轨道交通站域类型及其情景差异研究, columnId=1308454713796613035, journalTitle=都市快轨交通, columnName=200期专辑, runingTitle=null, highlight=null, articleAbstract=

针对传统节点-场所模型难以充分刻画轨道交通车站实际客流活力及其出行情景差异的问题，引入活力维度构建节点-场所-活力模型，用于识别城市轨道交通站域类型及其情景差异。以西安市211座轨道交通车站为研究对象，综合轨道交通网络拓扑结构、车站设施供给、接驳交通、建成环境、人口活动、兴趣点（point of interest, POI）功能设施及小时级起讫点（origin-destination, OD）客流等多源数据，构建涵盖节点、场所和活力三维度的评价指标体系，采用组合赋权方法确定指标权重，并利用高斯混合模型识别工作日和国庆长假情景下的站域类型，分析不同情景下站域类型的转换特征。结果表明：西安市轨道交通车站节点、场所和活力得分总体呈现“中心城区高、外围线路低”的空间格局，国庆长假情景下部分车站活力集聚程度明显增强；站域可划分为枢纽综合型、站城协调型、活力响应型、场所承载型和基础培育型5类，其空间分布呈现“中心集聚—外围分异”的圈层特征；工作日与国庆长假情景下站域类型整体保持稳定，211座车站中有192个站域类型不变，占比91.00%，19座车站发生转换，占比9.00%，站域类型转换主要发生在场所承载型与基础培育型之间，并主要分布于二环以外区域。研究结果可为轨道交通站域功能优化、外围车站培育、公共交通导向开发（transit-oriented development, TOD）模式下的差异化建设和精细化运营管理提供科学依据。

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王曲顺，男，博士研究生，从事城市轨道交通站域空间结构与客流特征研究，2022034006@chd.edu.cn

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王曲顺，男，博士研究生，从事城市轨道交通站域空间结构与客流特征研究，2022034006@chd.edu.cn

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