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基于GIS的清远市人口分布时空演变特征分析
引用本文:莫莹,朱煜峰,张明,周博.基于GIS的清远市人口分布时空演变特征分析[J].西南师范大学学报(自然科学版),2019,44(4):41-48.
作者姓名:莫莹  朱煜峰  张明  周博
作者单位:东华理工大学测绘工程学院;中山大学地理科学与规划学院
基金项目:国家自然科学基金资助项目(41464001);江西省自然科学基金资助项目(2012ZBAB216001);江西省教育厅科技研究资助项目(GJJ14489).
摘    要:采用人口密度、空间自相关、人口分布结构指数和人口重心等分析方法,结合GIS技术和GeoDa软件分析了清远市2005年—2015年人口分布时空演变特征.结果显示:清远市人口密度地域差异明显,北低南高;人口向清远市区集聚,但多地空间相关性较弱;人口分布不均衡但态势逐渐减弱;人口重心始终位于英德市黄花镇境内,偏离几何中心,呈西北向东南移动.清远市人口时空演变主要受自然环境和区位、城市规划和政策、轨道交通和经济发展水平等因素影响.

关 键 词:人口分布  空间自相关  时空演变  GIS
收稿时间:2018/7/13 0:00:00

A GIS-based Study on Temporal-spatial Evolution Characteristics of Population in Qingyuan City
MO Ying,ZHU Yu-feng,ZHANG Ming,ZHOU Bo.A GIS-based Study on Temporal-spatial Evolution Characteristics of Population in Qingyuan City[J].Journal of Southwest China Normal University(Natural Science),2019,44(4):41-48.
Authors:MO Ying  ZHU Yu-feng  ZHANG Ming  ZHOU Bo
Institution:1. School of Surveying and Mapping Engineering, East China University of Technology, Nanchang 330013, China;2. School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275 China
Abstract:Combined with GIS and GeoDa software in this paper, the temporal-spatial evolution characteristics of population in Qingyuan City from 2005 to 2015 have been discussed with population density, spatial autocorrelation method, imbalance index, concentration index and gravity center of population method. The results show that the population density of Qingyuan City characterizes by north-low and south-high, showing obvious regional differences. The population is closing to urban area, but most areas have a weak spatial correlation. The distribution of population is unbalanced but this situation is declining.The population gravity center is always located in Huanghua town of Yingde City and deviating from the geometric center in the northwest to southeast movement. The temporal and spatial evolution of population in Qingyuan City is mainly influenced by natural environment and location, urban planning and policy, rail transit and economic development level.
Keywords:population distribution  spatial autocorrelation  temporal-spatial evolution  GIS
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