地理科学进展 ›› 2017, Vol. 36 ›› Issue (6): 677-684.doi: 10.18306/dlkxjz.2017.06.003

• 研究论文 • 上一篇    下一篇

基于空间分形特征的城市群实体空间识别方法

刘飞(), 郑新奇*(), 黄晴   

  1. 中国地质大学(北京)信息工程学院,北京100083
  • 出版日期:2017-06-20 发布日期:2017-06-20
  • 通讯作者: 郑新奇 E-mail:liufei@escience.cn;zhengxq@cugb.edu.cn
  • 作者简介:

    作者简介:刘飞(1989- ),男,博士生,主要研究方向为地理分形与自组织, E-mail:liufei@escience.cn

  • 基金资助:
    国家国际科技合作与交流专项(S2015ZR1018)

Identification of the physical space of urban systems based on fractal analysis

Fei LIU(), Xinqi ZHENG*(), Qing HUANG   

  1. School of Information Engineering, China University of Geosciences (Beijing), Beijing 100083, China
  • Online:2017-06-20 Published:2017-06-20
  • Contact: Xinqi ZHENG E-mail:liufei@escience.cn;zhengxq@cugb.edu.cn
  • Supported by:
    National Major Programs of International Cooperation and Exchanges of China, No.S2015ZR1018

摘要:

城市群是城市地理学的重要研究领域,对城市群的实体空间进行界定识别是研究城市群的前提和基础。城市群作为众多城镇的集群,前人对城市群的空间识别主要是以城市为单元进行的,缺少对识别单元空间形态的考虑。城市群实体空间的形态具有自相似性,空间分形特征可作为自相似性的表征工具,通过对空间分形特征的分析、识别及提取,可以实现对空间对象基于形态的客观测度。本文借鉴单个城市其边界的相关识别方法,从不同尺度的空间最小可识别单元出发,测度城市群城镇空间形态的分形特征,并据此提出了城市群城镇的客观识别方法。该方法利用城镇的空间分形特征识别归属于城市群的城镇,通过空间最小可识别单元的变化得到不同的城镇规模并获取城市群城镇的空间分形特征,再以此为基础对空间分形特征的存在范围进行识别,将其映射于空间最终实现对城市群城镇的识别,进而得到城市群在空间上的分布状况。本文将该方法应用于京津冀城市群,基于2016年Landsat卫星遥感影像,实现了对京津冀城市群构成城镇的识别,为界定城市群的实体空间提供了一次有益尝试。

关键词: 城市群, 实体空间, 空间识别, 空间形态, 分形特征

Abstract:

Urban system study is an important field of urban geography. Identification of the physical space of urban systems is a precondition and basis for the research on urban systems. Existing research on urban system identification primarily took city as the minimum unit since urban systems are aggregations of towns and cities. They determine whether a city belong to an urban system through the comparison between values of selected indicators and the criteria set by subjective estimates, which unfortunately lacks consideration of spatial morphology. The morphology of the physical space of urban systems has self-similarity, which can be expressed by the feature of fractal. Through the analysis, identification, and extraction of fractals we can describe the spatial objects objectively based on morphology. In this study, by referencing the experience in identifying boundary of individual cities by fractal, we measured the spatial fractal feature of towns of urban systems from the perspective of spatially identifiable minimum unit at different scales, and proposed a method to identify the towns of urban systems. Through the change of identifiable minimum unit we obtained different scales of towns by which we derive their spatial fractal feature. Then, the range of spatial fractal features was identified, and the identification of urban systems that is the spatial distribution of urban systems was achieved by mapping the range to the space. Finally, this study applied the method to the Beijing-Tianjin-Hebei urban system and achieved the identification of the system based on Landsat images in 2016.

Key words: urban systems, physical space, space identification, spatial morphology, fractal