测绘学报 ›› 2023, Vol. 52 ›› Issue (3): 464-477.doi: 10.11947/j.AGCS.2023.20210514

• 地图学与地理信息 • 上一篇    下一篇

人群时空行为与城市昼夜人口空间集聚分析——以武汉市为例

孙立坚1, 马志勇1,2, 常迎辉1,3, 郭庆胜4, 张玉1   

  1. 1. 中国测绘科学研究院, 北京 100830;
    2. 中国测绘学会, 北京 100830;
    3. 西安科技大学测绘科学与技术学院, 陕西 西安 710054;
    4. 武汉大学资源与环境科学学院, 湖北 武汉 430079
  • 收稿日期:2021-09-09 修回日期:2022-01-12 发布日期:2023-04-07
  • 通讯作者: 张玉 E-mail:zhangyu@casm.ac.cn
  • 作者简介:孙立坚(1977-),男,博士,副研究员,研究方向为自然资源空间计算。E-mail:sunlj@casm.ac.cn
  • 基金资助:
    国家自然科学基金(71903183);北京市自然科学基金(9212001)

Analyzing spatial and temporal dynamics of crowds and spatial agglomeration variations between the daytime and nighttime population within city—a case study in Wuhan

SUN Lijian1, MA Zhiyong1,2, CHANG Yinghui1,3, GUO Qingsheng4, ZHANG Yu1   

  1. 1. Chinese Academy of Surveying and Mapping, Beijing 100830, China;
    2. Chinese Society of Surveying and Mapping, Beijing 100830, China;
    3. College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China;
    4. School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China
  • Received:2021-09-09 Revised:2022-01-12 Published:2023-04-07
  • Supported by:
    The National Natural Science Foundation of China (No.71903183);Beijing Natural Science Foundation (No. 9212001)

摘要: 城市是人口和资源在时空上的聚集,昼夜人群空间集聚是其中最基本、最主要、最频繁的人口时空变化模式,是理解城市复杂演变的基础微观机制。由于缺乏先进的技术手段,往往无法真实地记录和量测城市人口的个体流动与整体趋势,人们对城市昼夜人口空间集聚的了解仍然十分有限。本文基于城市人群时间地理特征,从城市大数据中挖掘并模拟城市人群的社会时空行为,在此基础上计算并分析城市昼夜人口集聚时空分布。对武汉市主城区的昼夜人口集聚分析表明:①人口密度与分布面积具有幂律关系,符合Clark模型;②傅里叶变换可有效地揭示人口分布空间变化的主方向和延伸程度;③中心城区夜间人口较白天人口分布更为集聚,研究区昼夜间人口流动主要以城区内部流动为主。归纳出城市昼夜人口集聚差异具有5种模式:交通线、三明治、光晕、椒盐和单体模式,这些模式与城市演化及空间格局有密切关系,其中交通线模式是研究区人口昼夜差异最大的一种模式。

关键词: 昼夜人口集聚, 时空场景, 空间梯度, 城市标度律

Abstract: Cities are spatial-temporal agglomerations of population and resources, and population spatial-agglomeration at daytime and nighttime is one of the most basic, dominant, and frequent spatio-temporal variation patterns for urban population distribution, which is the basic microscopic mechanism for understanding complicated urban development. Lack of advanced technical tools, it is often impossible to truly record and measure the individual flows and overall trends of urban population, and our understanding of the spatial clustering of urban population at daytime and nighttime is still very limited. Based on the temporal and geographical aspects of urban groups behaviors, this paper mines and simulates the social spatial and temporal behaviors of urban dwellers from urban big data. Based on this basis to simulate the spatial and temporal distribution of urban population agglomeration at daytime and nighttime, and to analyze the urban population agglomeration at daytime and nighttime in the main urban area of Wuhan city. The results show:①In the study area, the relationship between population density and area display a power-law model: Clark distribution. ②Population distribution gradient based on Fourier transform can reveal the main direction and extension of the variation.③The population cluster is obvious at nighttime than at daytime, and the daytime and nighttime population flows are mainly internal to the city. Five patterns of urban population between the daytime and nighttime concentration differences are summarized: traffic line, sandwich, halo, pepper and salt, single, which are closely related to urban evolution and spatial patterns, among which the traffic line pattern is the one with the largest urban population between the daytime and nighttime differences in the study area.

Key words: daytime and nighttime population spatialization, spatio-temporal scene, spatial gradient, urban scaling laws

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