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中国科学院大学学报 ›› 2018, Vol. 35 ›› Issue (4): 506-514.DOI: 10.7523/j.issn.2095-6134.2018.04.013

• 环境科学与地理学 • 上一篇    下一篇

1982-2010年乌鲁木齐市主城区人口时空分布特征及模拟

杨振1,2, 雷军1   

  1. 1. 中国科学院新疆生态与地理研究所, 乌鲁木齐 830011;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2017-02-16 修回日期:2017-05-08 发布日期:2018-07-15
  • 通讯作者: 雷军
  • 基金资助:
    国家自然科学基金面上项目(41671168)资助

Spatial-temporal distribution characteristics and simulation of population in the main urban area of Urumqi City from 1982 to 2010

YANG Zhen1,2, LEI Jun1   

  1. 1. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-02-16 Revised:2017-05-08 Published:2018-07-15

摘要: 城市人口空间分布是影响社会经济活力、公共服务配置、基础设施建设以及城市生态环境、交通、住宅等方面的重要因素之一,是科学开展城市规划的前提和基础。从主城区人口集中指数、人口集聚度指数、不同圈层人口密度分布变化、单中心与多中心人口密度分布模拟及主城区人口密度空间重构角度探讨1982-2010年乌鲁木齐市主城区人口空间分布规律。结果如下。1)近30年来主城区人口分布的集中程度一直在增加,人口分布的向心性较强,人口郊区化现象不明显。人口分布集中速度具有明显的阶段性特征:1982-2000年为高速增长阶段,2000-2010年为低速增加阶段。从人口集聚度指数来看,人口分布集聚特性明显且人口集聚沿主要交通走廊呈条带状特征。2)各年份人口密度随离城市中心的距离增加趋于减小,人口密度在0~3 km最大,在3~6 km处出现快速下降趋势;高人口密度街道分布有渐趋内移之势,低人口密度街道有渐趋外移趋势。3)单核心模型的回归表明:主城区4个年份的人口密度分布模型不尽相同,1982年与2000年反函数模型模拟效果较好;而1990年和2010年三次函数模型模拟更优。多核心模型的回归表明:2010年主城区双中心结构初露端倪,主中心在影响人口分布方面起到重要作用,而次中心在集聚人口能力方面较弱。

关键词: 人口分布, 人口密度, 人口密度模拟, 乌鲁木齐

Abstract: Spatial distribution of population in the main urban area of Urumqi City was studied from the perspectives of concentration index,population agglomeration index, population density changs in different spheres, monocentric and polycentric population density simulations, and space reconstruction. This work reveals the characteristics and laws of the population growth and distribution in the main urban area of Urumqi City. The main conclusions are given as follows. 1)The concentration degree of population distribution could be divided into two stages, the rapid growth stage from 1982 to 2000 and the slow growth stage from 2000 to 2010. From the viewpoint of the population agglomeration index, the agglomeration characteristics of population distribution were obvious, and the agglomeration presented a band feature along the main traffic corridor. 2) The population density maintained a centralized regular pattern. 3) Based on the regression of monocentric model, population density models of the main city area were different for the four years. The inverse function model was better for 1982 and 2000 while the cubic function model was fit for 1990 and 2010. Based on the regression of polycentric model, the authors found that a double-center structure appeared in the main city area in 2010. The main center played an important role in affecting the population distribution, and the subcenter was weak in the agglomeration population capacity.

Key words: population distribution, population density, population density simulation, Urumqi

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