地理研究 ›› 2007, Vol. 26 ›› Issue (2): 383-390.doi: 10.11821/yj2007020020

• 城市与乡村 • 上一篇    下一篇

城市人口分布的空间自相关分析——以沈阳市为例

杜国明1,2, 张树文1, 张有全1,2   

  1. 1. 中国科学院东北地理与农业生态研究所,长春 130012;
    2. 中国科学院研究生院,北京 100049
  • 收稿日期:2006-03-14 修回日期:2006-09-23 出版日期:2007-03-25 发布日期:2007-03-25
  • 作者简介:杜国明(1978-),男,内蒙古宁城县人,地图学与地理信息系统专业博士研究生。主要研究方向为地理信息系统、遥感应用。E-mail :nmgdgm@126.com
  • 基金资助:

    中国科学院知识创新工程重要方向项目(KZCX2-SW-320-1) 。

Analyzing spatial auto-correlation of population distribution: A case of Shenyang city

DU Guo-ming1,2, ZHANG Shu-wen1, ZHANG You-quan1,2   

  1. 1. Northeast Institute of Geography and Agricultural Ecology, CAS, Changchun 130012, China;
    2. Graduate University, of the Chinese Academy of Sciences, Beijing 100049, China
  • Received:2006-03-14 Revised:2006-09-23 Online:2007-03-25 Published:2007-03-25
  • Supported by:

    中国科学院知识创新工程重要方向项目(KZCX2-SW-320-1) 。

摘要: 为探测经典城市人口密度模型在微观层面上的适用性,本文通过计算基于格网的沈阳市人口景观密度,利用地统计学的理论与方法来分析其空间自相关性和变异性。研究发现:在10种不同采样粒度上人口密度半变异函数都符合球状模型,表征着城市人口分布具有较强的空间自相关性和变异性;但由于粒度不同,人口密度的空间自相关尺度不同,块金值不同,基台值不同,块金值与基台值的比值差异较大,证明人口分布的空间自相关具有较强的尺度依赖性;对于700m粒度而言,通过计算不同方向的半变异函数曲线可以发现,沈阳市人口密度呈现典型的带状异向性,反映出人口分布在不同方向上具有不同的结构特征。因此,研究城市人口分布时,可以城市人口分布的自相关性和变异性分析为基础,并须充分注意适宜尺度的选择和结构特征的识别。

关键词: 空间自相关, 城市人口分布, 人口密度模型, 空间变异性, 地统计学

Abstract: For detecting the applicability of classical urban population density models on the microcosmiclevel, this paper calculates grid-based population landscape density of Shenyang city, analyzes it's spiatial auto-correlation and variability using theories and methods of geostatiatics. It is found out that all semivariogram functions of populatin density fit with spherical model with negget in ten kinds of grains from 100m to 1000m, indicating that population distribution presents structural characteristics in the spatial extension of Shenyang city. But because of different grains, the auto-correlation scales, neggets, and stills, the rate of negget and still is different. This means that spatial auto-correlation of population distribution depended on the scale intensively, resulting in scale effects.By calculating semivariogram functions curves of different directions, it can be found that population density takes on a classical zonal anisotropy, which means that there were different structural characteristics in different directions for poplation distribution. The analysis of population density auto-crrelation and variability should be taken as bases for researching urban population density distribution. The impacts of grain on population density auto-correlation and anisotropy are objective, so more attention should be paid to choosing feasible scale and identifying structure of population distribution. In the specific time for a certain city, the condition of population distribution is objective, while population density models are abstract expressions of population distribution characteristics, whose parameters are only quantitative indexes of expressing population distribution pattern. So, when researching spatial structure of population distribution in a city, the emphases should be put on how to identify spatial structural characteristics of population distribution, rather than on how to apply classical population density models mechanically.

Key words: spatial auto-correlation, urban population distribution, population density models, spatial variability, geosatistics