兰州市轨道交通站点功能识别与优化路径探究

Functional Identification and Optimization Paths of Rail Transit Stations in Lanzhou

摘要

精准识别轨道交通站点功能，是推进站城融合与城市空间优化的重要前提。本文以兰州地铁1、2号线27座站点为研究对 象，以800m步行范围为研究尺度，基于2025年高德地图POI数据，采用信息熵模型与K-means聚类算法，开展轨道站点功 能识别、混合度测度及空间格局分析。结果显示：兰州地铁站点可分为城市中心型、组团中心型、居住主导型、交通枢纽 型，各类功能结构与混合度差异显著；城市中心型与组团中心型站点沿1号线中段呈“串珠状”轴向集聚，构成城市东西向 功能发展主轴；居住主导型站点多分布于线路两翼，具备明显卧城化特征；交通枢纽站点多与铁路客运枢纽一体化布局。 据此提出差异化TOD优化策略，可为同类河谷型城市轨道站点功能提质、站城融合与空间结构优化提供借鉴。

Abstract

Accurately identifying the functions of rail transit stations is an important prerequisite for promoting station-city integration and urban spatial optimization. Taking 27 stations of Lanzhou Metro Lines 1 and 2 as the research objects and the 800-meter walking scope as the research scale, this paper conducts functional identification, mixing degree measurement and spatial pattern analysis of rail transit stations based on 2025 Amap POI data by using the information entropy model and K-means clustering algorithm. The results show that Lanzhou metro stations can be divided into four categories: urban center type, cluster center type, residential- dominated type and transportation hub type, with significant differences in functional structure and mixing degree among all types. Urban center and cluster center stations are axially clustered in a beaded pattern along the middle section of Metro Line 1, forming the east-west functional development axis of the city. Residential-dominated stations are mostly distributed on both sides of the lines with obvious bedroom-town characteristics, and transportation hub stations are mostly integrated with railway passenger transport hubs. On this basis, differentiated TOD optimization strategies are proposed, which can provide a reference for the functional improvement of rail transit stations, station-city integration and spatial structure optimization of similar valley-type cities.

关键词

轨道交通站点 / 功能识别 / 空间格局 / TOD优化 / 兰州市

Key words

rail transit station / functional identification / spatial pattern / TOD optimization / Lanzhou

参考文献

[1] 孙久文, 张翱, 周正祥. 城市轨道交通促进城市化进程研究[J]. 中国软科学, 2020,(06):96-111.

[2] 陈万丽, 徐中春. 基于POI数据的贵阳主城区公共交通设施空间演变研究[J]. 测绘科学, 2025, 50(12):167-176.DOI:10.16251/j.cnki.1009-2307.2025.12.018.

[3] 刘洁瑄, 符超峰. 基于兴趣点数据的山西太原地铁站点生活圈服务设施时空演化特征[J]. 地球科学与环境学报, 2025, 47(03):485-499.DOI:10.19814/j.jese.2025.03024.

[4] 刘亚静, 张新莲. 基于POI数据的城市功能区识别及其混合度分析[J]. 西安文理学院学报(自然科学版), 2025, 28(03):68-75.

[5] 夏雪, 盖靖元. 基于K-Means聚类算法的城市轨道交通站点分类及客流特征分析[J]. 现代城市轨道交通, 2021,(04):112-118. DOI:10.20151/j.cnki.1672-7533.2021.04.021.