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基于热力图数据的轨道交通站点服务区活力测度研究——以深圳市地铁为例
引用本文:周雨霏,杨家文,周江评,周佩玲,刘海涛.基于热力图数据的轨道交通站点服务区活力测度研究——以深圳市地铁为例[J].北京大学学报(自然科学版),2020,56(5):875-883.
作者姓名:周雨霏  杨家文  周江评  周佩玲  刘海涛
作者单位:1. 北京大学深圳研究生院城市规划与设计学院, 深圳 518055 2. 香港大学建筑学院, 香港 3. 哈尔滨工业大学(深圳)建筑学院, 深圳 518055 4. 天津市城市规划设计研究院, 天津 300000
基金项目:国家自然科学基金(51678004)资助
摘    要:以深圳市地铁为案例, 利用百度热力图, 通过热力平均值和热力离散系数构建轨道站点服务区活力测度体系。结果表明: 1) 深圳市人口聚集具有站点导向, 占深圳市总面积15%的轨道服务区在7—23时集聚全市38%~50%的人口, 呈现夜间少、日间多的人口聚集特征; 2) 测度体系将深圳市166个轨道站点服务区划分为低平衡成熟型、高平衡成熟型、高平衡孕育型和低平衡孕育型, 活力表现与建成环境有关, 成熟型服务区建设强度更高, 低平衡型服务区用地不均衡的情况更严重, 拥有规模性城中村的服务区更易表现出高平衡型特征。基于热力图数据的活力测度能帮助不同类型的轨道站点服务区采取相应的规划策略, 产生更理想的公共交通导向式土地开发(TOD)效益。

关 键 词:轨道站点服务区  大数据  城市活力  深圳市  
收稿时间:2019-08-15

Evaluating Vitality of Metro Station Service Area with Heat Map: A Case Study on Shenzhen Subway
ZHOU Yufei,YANG Jiawen,ZHOU Jiangping,ZHOU Peiling,LIU Haitao.Evaluating Vitality of Metro Station Service Area with Heat Map: A Case Study on Shenzhen Subway[J].Acta Scientiarum Naturalium Universitatis Pekinensis,2020,56(5):875-883.
Authors:ZHOU Yufei  YANG Jiawen  ZHOU Jiangping  ZHOU Peiling  LIU Haitao
Institution:1. School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055 2. Faculty of Architecture, The University of Hong Kong, Hong Kong 3. School of Architecture, Harbin Institute of Technology (Shenzhen), Shenzhen 518055 4. Tianjin Urban Planning and Design Institute, Tianjin 300000
Abstract:Taking Shenzhen subway as an example, we use Baidu Heat Map to construct a system to evaluate vitality of station service area through heat average and heat coefficient of variation. Station service area, which accounts for 15% of Shenzhen municipal area, has 38%~50% of the city population from 7:00 to 23:00, less population gather at night and more during daytime. The 166 service areas can be classified into four groups: lowbalance mature areas, low-balance developing areas, high-balance mature areas and high-balance developing areas. Their vitality characteristics are quite relevant to built environment. Mature areas have higher development density. High-balance areas have higher land use mixture. Station service areas with large-scale urban village are more likely to show high-balance. The evaluation can be beneficial to adopting available strategies for different types of station service area, and shed light on trancit oriented development (TOD) planning and design.
Keywords:metro station service area  big data  urban vitality  Shenzhen  
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