地球信息科学学报 ›› 2022, Vol. 24 ›› Issue (4): 698-710.doi: 10.12082/dqxxkx.2022.210406

• 地理空间分析综合应用 • 上一篇    下一篇

2005—2018年北京市外来人口迁移特征与影响因素分析

赵迪1(), 陈鹏1,*(), 李海成2, 苗红斌2   

  1. 1.中国人民公安大学信息网络安全学院,北京 102600
    2.北京市公安局,北京 100082
  • 收稿日期:2021-07-17 修回日期:2021-09-22 出版日期:2022-04-25 发布日期:2022-06-25
  • 通讯作者: *陈 鹏(1981— ),辽宁营口人,博士,副教授,主要研究方向为犯罪地理、公安大数据分析。 E-mail: chenpeng@ppsuc.edu.cn
    *陈 鹏(1981— ),辽宁营口人,博士,副教授,主要研究方向为犯罪地理、公安大数据分析。 E-mail: chenpeng@ppsuc.edu.cn
  • 作者简介:赵 迪(1998— ),黑龙江哈尔滨人,硕士生,研究方向为犯罪地理、公安大数据分析。E-mail: 2836694958@qq.com
  • 基金资助:
    教育部人文社会科学规划基金项目(20YJAZH009)

Beijing Non-registered Population Spatiotemporal Distribution Characteristics and Influencing Factors from 2005 to 2018

ZHAO Di1(), CHEN Peng1,*(), LI Haicheng2, MIAO Hongbin2   

  1. 1. School of Police Information Engineering and Cyber Security, People's Pubic Security University of China, Beijing 102600, China
    2. Beijing Municipal Public Security Bureau, Beijing 100082, China
  • Received:2021-07-17 Revised:2021-09-22 Online:2022-04-25 Published:2022-06-25
  • Supported by:
    Humanities and Social Sciences planning fund project of the Ministry of Education(20YJAZH009)

摘要:

外来人口是大型或超大型城市人口结构的重要组成部分,研究特定城市外来人口的迁移特征及其影响因素不仅有助于从迁入地视角发现以特定城市为目标的人口迁移规律,对新城镇化背景下的城市化建设与发展也具有重要的现实意义。本文以北京市为例,通过收集2005—2018年的公安机关外来人口登记数据,对外来人口在不同年份的市级迁出地空间分布格局进行了研究,并利用空间回归模型对人口迁移的影响因素进行了分析,得到如下发现:① 北京市外来人口的迁出地在市级尺度下表现出明显的空间聚集效应,且聚集效应逐年增强;外来人口迁出地空间分布基本稳定,热点迁出地分布主要集中在河北-天津和河南省南部-湖北省北部2个主要聚集簇中;② 影响人口向北京迁移的主要变量为各迁出地的人口规模、交通时间、人均收入、高等教育水平、人口密度等,其中人口规模和人均收入对人口迁移的影响较为稳定,而高等教育水平和人口密度的影响分别从2010年和2014年后才开始显现,交通时间对人口迁移的障碍性作用虽然有所下降,但对人口迁移的影响变化不大;③ 空间误差项持续显著,表明迁出地的人口迁出量可能受相邻地市的社会文化等其他变量的影响。

关键词: 外来人口, 空间分布, Moran' s I指数, 空间异质性, 多元线性回归, 空间误差回归

Abstract:

The migrant population is an important part of the population structure of large or super large cities. Studying the migration characteristics and influencing factors of the migrant population in a particular city will not only help to discover the pattern of population migration targeting a particular city from the perspective of the migration place, but also affect new towns. The construction and development of urbanization in the context of urbanization also has important practical significance. Taking Beijing as an example, this paper collects the migrant population registration data of the public security organs from 2005 to 2018, studies the spatial distribution pattern of the migrant population in different years in the city-level emigration areas, and uses the spatial regression model to analyze the factors that affect population migration. The following findings are obtained: ① The emigration area of Beijing's migrant population shows obvious spatial agglomeration effect at the municipal scale, and the aggregation effect is increasing year by year. The spatial distribution of migrant population emigration area is generally stable. The hot spot emigration places is mainly concentrated in two main clusters: Hebei-Tianjin and southern Henan Province-Northern Hubei Province; ② The main variables affecting population migration from various places to Beijing are the population size of the emigration area, transportation time, per capita income, and education level. The impact of population size and per capita income on population migration is relatively stable, while the effects of education level and population density only began to appear after 2010 and 2014, respectively. Transportation time has an negative effect on population migration. Although the transportation time has decreased in recent years, its impact on population migration has not changed much; ③ The spatial error continues to be significant, indicating that the population migration volume of a given emigration area may be affected by other variables such as the social culture of neighboring cities.

Key words: Non-registered population, spatial distribution, Moran' s I index, special heterogeneity, multiple linear regression, spatial error model