基于多源大数据的人口分布影响因素空间异质性探析——以南京主城区为例

Spatial Heterogeneity Analysis of Population Distribution Factors Based on Multi-source Big Data:A Case Study of the Central Urban Area of Nanjing

本文使用手机信令、互联网大数据等多源数据分析城市人口空间分布的影响因素及其作用机制,首先借助地理探测器和普通最小二乘法识别主导影响因素,发现就业岗位、距离、房价、土地利用混合度四类因素对人口空间分布影响作用显著,随后利用地理加权回归模型探析四类因素对人口分布影响作用的空间异质性。研究发现,南京中心城区人口分布具有明显的老城集聚现象,不同因素作用效果的空间异质性较强,且作用效果的分层聚类与城市部分功能组团在空间上相契合。

In this paper,mobile phone signaling,Internet big data,and other multi-source data are used to analyze the influencing factors of urban population spatial distribution and their mechanisms.Geographical detector and OLS are used to identify the leading influencing factors.It is found that employment position,distance,housing price and land use mixing degree have significant effects on the spatial distribution of population.Geographical weighted regression model is used to analyze the spatial heterogeneity of the effects of the four factors above on population distribution.Results show that the population distribution in the central urban area of Nanjing has obvious agglomeration,the spatial heterogeneity of the effect of different factors is strong,and the hierarchical clustering of the effect is spatially compatible with the functional groups of the city.