地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (7): 988-995.doi: 10.12082/dqxxkx.2018.180075

• 地理空间分析综合应用 • 上一篇    下一篇

沈阳市城市功能区分布与人口活动研究

刘彤(), 周伟*(), 曹银贵   

  1. 中国地质大学(北京)土地科学技术学院 国土资源部土地整治重点实验室,北京 100091
  • 收稿日期:2018-01-25 修回日期:2018-04-18 出版日期:2018-07-20 发布日期:2018-07-13
  • 通讯作者: 周伟 E-mail:18801329118@163.com;zhouw@cugb.edu.cn
  • 作者简介:

    作者简介:刘 彤(1993-),女,硕士生,研究方向为城市群空间结构,土地复垦。E-mail: 18801329118@163.com

  • 基金资助:
    国土资源部公益项目(2015-2016)

Distribution of Functional Areas and Population Activities in Shenyang City

LIU Tong(), ZHOU Wei*(), CAO Yingui   

  1. School of Land Science and Technology, China University of Geosciences(Beijing), Beijing 100091, China
  • Received:2018-01-25 Revised:2018-04-18 Online:2018-07-20 Published:2018-07-13
  • Contact: ZHOU Wei E-mail:18801329118@163.com;zhouw@cugb.edu.cn
  • Supported by:
    Ministry of Land and Resources Public Welfare Projects(2015-2016)

摘要:

从精细尺度上研究城市功能区分布与人口活动规律对于政府和相关部门合理调节城市内部资源配置、安排城市设施布局具有重要意义。以沈阳市中心城区为例,根据核密度估计原理,基于兴趣点(POI)数据探索沈阳市中心功能区分布情况,通过解读多时相百度热力图数据,探索工作日和周末城区人口时空分布规律,即从城市人口活动和城市功能设施分布2个角度解读沈阳市中心城区空间结构与组织形式。借助SPSS 20.0分析人口热度和设施分布的相关性关系,建立多元线性回归模型。主要结论如下:① 沈阳市城市活力区呈现多中心分布模式,大多位于商业中心、金融中心或者城市功能复合中心。② 工作日人口高热区空间分布较周末更为分散,面积较大,早晚波动较大。周末人口高热区主要集中在商业中心和城市复合功能区且白天存在较大波动。③ 功能区分布与人口热度显著相关,其中生活服务设施、金融设施、交通设施、住宿设施和景点设施是工作日人口热度的主要影响因子;教育设施、餐饮设施、交通设施、金融设施和公共服务设施是周末人口热度的主要影响因子。

关键词: 沈阳市, 热力图, 空间结构, 人口活动, 多元线性回归

Abstract:

Studying the distribution of urban functional areas and the laws of population activities on a fine scale has important implications for the government and relevant departments to rationally adjust the allocation of urban internal resources and arrange the layout of urban facilities. Taking the center area of Shenyang City in Liaoning Province as research area, based on the principle of nuclear density estimation, the distribution of functional areas in downtown Shenyang is explored based on point-of-interest (POI) data, and the temporal and spatial distribution patterns of urban population on working days and weekends are explored by interpreting the multi-temporal Baidu thermogram data. This paper analyzed the spatial structure of Shenyang city center from two perspectives: the distribution of the urban physical facilities and the law of the population activities. Finally, we used SPSS to analyze the correlation between population heat and urban physical facilities and established multiple linear regression models. The results showed that: (1) Shenyang City vitality area showed a multi-center distribution model, mostly in the commercial center, financial center or urban function complex center. (2) The spatial distribution of the hot spots in the working day was more scattered than that on the weekend. The area was larger and fluctuated greatly. However, population hot spots were mainly concentrated in the commercial center and urban complex functional area and there was a large fluctuation during the daytime on weekend. (3) The distribution of functional areas was significantly correlated with the population heat. Life service facilities, financial facilities, transports, accommodation facilities and attractions are the main factors influencing the population heat on the working day. While educational institutions, transports, public service facilities, catering facilities and financial facilities are the main influential factors on weekend.

Key words: Shenyang City, Baidu thermal chart, special structure, population activities, multiple linear regression