地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (7): 1246-1258.doi: 10.12082/dqxxkx.2021.200687

• 地理空间分析综合应用 • 上一篇    下一篇

武汉市不同站域建成环境与轨道交通站点客流特征关系分析

李清嘉(), 彭建东, 杨红*()   

  1. 武汉大学城市设计学院,武汉 430072
  • 收稿日期:2020-11-14 修回日期:2021-02-08 出版日期:2021-07-25 发布日期:2021-09-25
  • 通讯作者: 杨红
  • 作者简介:李清嘉(1995— ),女,河南驻马店人,硕士生,主要研究方向为国土空间规划。E-mail: chdyqjli@whu.edu.cn
  • 基金资助:
    国家自然科学基金项目(71871027)

Research on Relationship Analysis between Passenger Flow Characteristics of Rail Transit Stations and Built Environment of Different Station Areas in Wuhan

LI Qingjia(), PENG Jiandong, YANG Hong*()   

  1. School of Urban Design Wuhan University, Wuhan 430072, China
  • Received:2020-11-14 Revised:2021-02-08 Online:2021-07-25 Published:2021-09-25
  • Contact: YANG Hong
  • Supported by:
    National Natural Science Foundation of China(71871027)

摘要:

中国已经成为全世界城市轨道交通建设里程最长、建设速度最快的国家,合理识别城市轨道站点类别与影响不同类别站点客流特征的建成环境因素对轨道交通的建设具有十分重要的作用。因此,本文以武汉市为例,通过轨道交通刷卡数据,运用引入客流特征的EM聚类方法,将轨道交通站点分为职住错位型、居住导向型、就业导向型、居住综合型、就业综合型、综合型6类。并在此基础上,建立无序多分类logistic回归模型,定量分析站点客流吸引范围内建成环境因素对不同类型站点轨道交通客流特征的影响。结果表明:以综合型站点为对照组,路网密度和交叉口密度对所有类型站点的客流特征有显著影响,低路网密度高交叉口密度更有利于职住平衡;公交车站密度与就业导向型站点的客流特征存在负相关;商务用地占比对职住错位型、居住导向型、居住综合型站点有负向关系;服务业设施用地占比与职住错位型、居住导向型和就业综合型站点的客流特征负相关;科研教育用地占比与居住导向型和就业导向型站点客流特征负相关;土地利用混合度与居住导向型和就业综合型站点的客流特征负相关。研究结论将对武汉市轨道交通建设、轨道交通和土地利用协调发展等具有重要意义。

关键词: 城市轨道交通, 站点分类, 建成环境, AFC数据, 聚类分析, 无序多分类logistic回归, 客流特征, 武汉市

Abstract:

China has become the country with the longest urban rail transit construction mileage and the highest construction speed in the world. Thus, It is of great significance for the construction of rail transit to reasonably identify different types of urban railway stations and environmental building factors that affect the characteristics of passenger flow. In this study, we take Wuhan as an example. We divide rail transit sites into six types (jobs-housing mismatch, residence-oriented, employment-oriented, comprehensive residence, comprehensive employment, and integrated type) through analyzing automatic fare collection system data and using EM clustering method with the introduction of passenger flow characteristics. On this basis, a multinomial logistic regression model is established to quantitatively analyze the impact of built-in environmental factors on the characteristics of rail transit passenger flow at different types of stations within the passenger flow attraction range. Taking comprehensive stations as control group, the results are shown as follows: (1) The densities of road network and intersection have a significant impacts on the passenger flow characteristics of all types of stations. A lower road network density and a higher intersection density are more beneficial to jobs-housing balance. (2) The density of bus station is negatively correlated with the passenger flow characteristics of employment-oriented stations. (3) The proportion of commercial land is negatively correlated with the passenger flow characteristics of jobs-housing mismatch, residence-oriented, and comprehensive residence stations. (4) The proportion of service industry facility land is negatively correlated with the passenger flow characteristics of jobs-housing mismatch, residence-oriented, and comprehensive employment stations. (5) The proportion of land used for scientific research and education is negatively correlated with the passenger flow characteristics of residence-oriented and employment-oriented stations. (6) The degree of land use mixture is negatively correlated with the passenger flow characteristics of residence-oriented and employment-integrated stations. This study is of great significance to coordinated development of rail transit construction, rail transit, and land use in Wuhan.

Key words: urban rail transit, station classification, built environment, automatic fare collection data, cluster analysis, multinomial logistic regression, passenger flow characteristics, Wuhan