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清华大学学报(自然科学版)  2022, Vol. 62 Issue (7): 1195-1202    DOI: 10.16511/j.cnki.qhdxxb.2022.26.019
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基于位置服务大数据的粤港澳大湾区通勤标度特征分析
陈若宇1,2,3, 周江评1,2,4
1. 香港大学 深圳研究院, 深圳 518057;
2. 粤港澳智慧城市联合实验室, 香港 999077;
3. 北京大学深圳研究生院 城市规划与设计学院, 深圳 518055;
4. 香港大学 建筑学院, 香港 999077
Understanding the scaling patterns of commuting in the Guangdong-Hong Kong-Macao Greater Bay Area with location-based service big data
CHEN Ruoyu1,2,3, ZHOU Jiangping1,2,4
1. Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen 518057, China;
2. Guangdong-Hong Kong-Macao Joint Laboratory on Smart Cities, Hong Kong 999077, China;
3. School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China;
4. Faculty of Architecture, The University of Hong Kong, Hong Kong 999077, China
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摘要 城市群是中国发展的重要增长极点和核心节点,城市群交通一体化是推进城市群协调发展的首要任务之一,而对城市群内多种交通出行模式的充分认识是实现这一目标的重要基础。该文基于位置服务大数据,以粤港澳大湾区“9+2”城市群为例,分析了城市群内部通勤出行标度特征的一致性与差异性,得到以下结果:粤港澳大湾区的市内通勤仍占主导地位,但部分区域存在相当规模的跨市通勤;粤港澳大湾区通勤联系的“概率-距离”分布具有指数标度特征;对各城市而言,市内通勤的标度参数比跨市通勤更大,意味着市内通勤者对距离更加敏感;标度参数可以进一步反映交通与土地利用联系的紧密程度,进而为政策制定提供参考。
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陈若宇
周江评
关键词 城市群通勤出行距离衰减交通与土地利用    
Abstract:Urban clusters are important in China's development. The integration of transportation systems in these urban clusters is one of the most important tasks for promoting the development of these clusters, which requires a full understanding of the current travel patterns. Location-based service (LBS) big data for the Guangdong-Hong Kong-Macao Greater Bay Area was analyzed to identify the commuter travel scaling patterns. The results show that most commuting trips are still inside the cities, but there are sizable inter-city commutes in some areas. The results also show that the probability density of the commute distance is exponentially related to the distance. In addition, the scaling parameter for intra-city commuting is generally larger than that of inter-city commuting, which indicates that trips within cities are more sensitive to the commuting distance. The scaling parameter further reflects the connections between the transportation and land use, which can be useful for policy making.
Key wordsurban clusters    commuting travel    distance decay    transportation and land use
收稿日期: 2021-10-25      出版日期: 2022-06-16
基金资助:科技部国家重点研发计划项目(2019YFB1600703);2020年广东省科技创新战略专项资金(粤港澳联合实验室)项目(2020B1212030009)
通讯作者: 周江评,副教授,E-mail:zhoujp@hku.hk      E-mail: zhoujp@hku.hk
作者简介: 陈若宇(1997—),男,硕士研究生。
引用本文:   
陈若宇, 周江评. 基于位置服务大数据的粤港澳大湾区通勤标度特征分析[J]. 清华大学学报(自然科学版), 2022, 62(7): 1195-1202.
CHEN Ruoyu, ZHOU Jiangping. Understanding the scaling patterns of commuting in the Guangdong-Hong Kong-Macao Greater Bay Area with location-based service big data. Journal of Tsinghua University(Science and Technology), 2022, 62(7): 1195-1202.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2022.26.019  或          http://jst.tsinghuajournals.com/CN/Y2022/V62/I7/1195
  
  
  
  
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