Revealing population flow patterns in the Sichuan-Chongqing region, China, during the COVID-19 epidemic in 2020

IF 2.7 Q1 GEOGRAPHY
Jingwei Shen, Zhongyu Huang, Wei Zhou, Dongzhe Zhao
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引用次数: 3

Abstract

ABSTRACT COVID-19 has had a serious impact on the lives and health of people and severely affected the population flow in 2020. Baidu migration data offer great opportunities to study spatiotemporal interactions among cities. Revealing population flow patterns has important scientific significance for the precise prevention and control of the COVID-19 epidemic. The aim of this article is to reveal the spatiotemporal patterns of population flow and associated influential factors in 22 cities in the Sichuan-Chongqing region (SCR), which is regarded as the fourth pole of China’s economy. Four typical time periods are selected to study the spatiotemporal patterns of population flow. The regional population flow intensities in all cities and between different cities in the SCR are illustrated. Stepwise regression is used to analyse the factors affecting regional population flow intensity in four selected periods. The results show that (1) the COVID-19 epidemic greatly affected population flow in the SCR, (2) more travel occurred between cities on holidays than on weekdays in the SCR when the epidemic was not serious, and (3) the regional population flow intensity was strongly correlated with the population education level and transportation facilities when the epidemic was not serious.
揭示2020年新冠肺炎疫情期间中国川渝地区人口流动模式
新冠肺炎疫情严重影响人民群众生命健康,严重影响2020年人口流动。百度人口迁移数据为研究城市间的时空相互作用提供了很好的机会。揭示人口流动规律对精准防控疫情具有重要的科学意义。以中国经济第四极川渝地区22个城市为研究对象,分析川渝地区人口流动的时空格局及其影响因素。选取4个典型时段,研究人口流动的时空格局。分析了区域内各城市间和各城市间的人口流动强度。采用逐步回归方法,分析了四个时期影响区域人口流动强度的因素。结果表明:(1)新冠肺炎疫情对区域人口流动的影响较大,(2)疫情不严重时,区域假日城市间的出行量大于工作日,(3)疫情不严重时,区域人口流动强度与人口受教育程度和交通设施密切相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Annals of GIS
Annals of GIS Multiple-
CiteScore
8.30
自引率
2.00%
发文量
31
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