摘要
为探究我国春运人口省际流动特征及高铁发展对其造成的影响,基于腾讯春运迁徙数据,本文构建了2015和2018年省际流动网络模型,宏观上表征我国省际人口流动现象,并对其进行特征研究和对比分析。结果表明:春运人口省际流动网络结构基本稳定,但2018年网络内部的流动强度较2015年明显增大,其整体分布特征与人口分布特征相符;影响该网络的主要因素有城市发展成熟度、交通发展状况和旅游吸引力;2018年网络内部形成新的交通枢纽,城市间直达性增强,内部联系增强;省际人口流动具有层聚特征,城市的流动等级与其自身及周围城市的经济和交通状况有关,高铁发展扩大了城市的辐射范围,部分城市流动等级发生变化。
In order to explore the characteristics of inter-provincial mobility of China′s Spring Festival travel rush and the impact of high-speed rail development on it.Using the Tencent migration data in 2015 and 2018 to construct network models,macroscopically characterize the phenomenon of inter-provincial population movement in China,and conduct characteristic research and comparative analysis.and compare them.The results are as follows:The network structure of Spring Festival in these two years are basically stable,however,the internal flow intensity of the 2018 network is significantly larger than that of 2015.The overall distribution characteristics of the mare consistent with the characteristics of population distribution;The main factors affecting the network are urban development maturity,traffic development and tourism attractiveness;Due to the development of high-speed rail,new transportations hubs have been formed within the network of 2018,the direct access between cities has increased,and the links between the western region and the central and eastern regions have increased;The population mobility in different regions has the characteristics of stratification.The mobility level of the city is related to the economic status and traffic conditions of the city itself and the surrounding cities.The development of high-speed railway increases the radiation range of the city,and the urban mobility level of some cities have changed.
作者
翟婷婷
任福
ZHAI Tingting;REN Fu(School of Resource and Environmental Sciences,Wuhan University,Wuhan 430072,China)
出处
《测绘与空间地理信息》
2020年第4期31-35,39,共6页
Geomatics & Spatial Information Technology
基金
国家自然科学基金资助项目(41571438)
国家重点研发计划资助项目(2016YFC0803106)资助。
关键词
腾讯迁徙数据
人口流动
社会网络分析
春运
高铁
Tencent migrationdata data
migration
social network analysis
spring festival travel rush
high-speed railway