基于腾讯迁徙大数据的长三角城市群春运人口流动时空特征

doi:10.13959/j.issn.1003-2398.2020.04.016

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Abstract The research on population flow in urban agglomerations has important theoretical and practical guiding significance for promoting the orderly flow of regional population and coordinated development of urban agglomerations. In recent years, with the rapid development of information and communication technology, the data acquisition environment and collection methods in urban scale and regional scale have been greatly improved. New data sources related to geographic location are constantly emerging. This geographical behavior big data with the characteristics of real-time, quantitative objectivity, and strong spatio-temporal heterogeneity provides a new support and approach for the study of population flow. This article takes the urban agglomeration of the Yangtze River Delta in China as an example, based on Tencent migration big data, using GIS spatial statistics, spatial analysis and K-shell decomposition methods, to systematically analyze the spatio-temporal characteristics of the population flow of the Yangtze River Delta urban agglomeration during the Spring Festival travel rush in 2018, from the aspects of total population, order, time series and network level, etc. The results of the study showed that in the Yangtze River Delta urban agglomeration, Shanghai, Suzhou, Hangzhou, Ningbo, and Nanjing, which have relatively high levels of economic development, are labor-importing cities. While Yancheng, Anqing, and Chuzhou, which have relatively low economic development levels, are labor-exporting cities.

Key words： tencent migration big data population flow Spring Festival travel Yangtze River Delta urban agglomeration

Received: 26 September 2019

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K901.3

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	CHEN Shuang
	ZHOU Rui
	GAO Jun

Cite this article:

CHEN Shuang,ZHOU Rui,GAO Jun. SPATIAL-TEMPORAL CHARACTERISTICS OF POPULATION FLOW DURING SPRING FESTIVAL TRAVEL RUSH IN YANGTZE RIVER DELTA URBAN AGGLOMERATION BASED ON TENCENT MIGRATION DATA[J]. HUMAN GEOGRAPHY, 2020, 35(4): 130-138.

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http://rwdl.xisu.edu.cn/EN/10.13959/j.issn.1003-2398.2020.04.016 OR http://rwdl.xisu.edu.cn/EN/Y2020/V35/I4/130

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