| COVID-19疫情影响下的“五一”小长假城际出行特征与影响因素 |
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| 引用本文： | 李涛,李宇,戴靓,王姣娥.COVID-19疫情影响下的“五一”小长假城际出行特征与影响因素[J].地理研究,2021,40(11):3225-3241. |
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| 作者姓名： | 李涛 李宇 戴靓 王姣娥 |
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| 作者单位： | 1.陕西师范大学西北国土资源研究中心, 西安 7101192.中国科学院地理科学与资源研究所中国科学院区域可持续发展分析与模拟重点实验室, 北京 1001013.南京财经大学公共管理学院, 南京 2100234.中国科学院大学资源与环境学院, 北京 100049 |
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| 基金项目： | 国家自然科学基金项目(41501120);国家社科基金重大项目(20&ZD099);江苏省自然科学基金青年项目(BK20190797);中央高校基本科研业务费项目(GK202103124) |
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| 摘 要： | 科学评估重大公共卫生事件扰动对节假日城际出行活动的影响对于科学预防疫情传播、提升城际出行安全性具有重要意义。文章利用百度迁徙平台提供的城际出行数据,系统探讨了COVID-19疫情影响下的“五一”小长假城际出行规模时序变化、格局变化与出行流格局特征,并基于空间计量模型剖析了疫情与节假日叠加背景下的城际出行影响因素。结果表明：受COVID-19疫情影响,2020年“五一”小长假期间的城际出行规模同比下降达46.0%,时段波动主要表现为省内波动,省外城际出行总体较为平稳;COVID-19疫情对城际出行的影响呈现出东北>东中部>西部的特征;COVID-19疫情显著降低了“五一”小长假城际出行范围,相较于正常期70%的城际出行联系集中在400km范围内,疫情影响下的70%的城际出行联系集中在250 km范围以内;GDP、城镇化率、行政等级等城市规模吸引力因素,公路密度与高铁等交通变量是影响“五一”期间城际出行的主要因素,但各变量对城际出行的影响在“五一”不同时段具有时间异质性。公路密度与有无高铁具有显著的正向作用;城镇化率在出行期与返程期对城际出行分别起到了显著负向与正向作用;旅游资源丰富度仅在出行期显著。
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| 关 键 词： | 新冠肺炎疫情（COVID-19） “五一”小长假 城际出行 空间计量模型 重大公共卫生事件 |
| 收稿时间： | 2020-12-30 |
Characteristics and influencing factors of intercity travel during the May Day holiday under the influence of the COVID-19 outbreak in China |
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| LI Tao,LI Yu,DAI Liang,WANG Jiaoe.Characteristics and influencing factors of intercity travel during the May Day holiday under the influence of the COVID-19 outbreak in China[J].Geographical Research,2021,40(11):3225-3241. |
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| Authors: | LI Tao LI Yu DAI Liang WANG Jiaoe |
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| Institution: | 1. Northwest Land and Resource Research Center, Shaanxi Normal University, Xi’an 710119, China2. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China3. School of Public Administration, Nanjing University of Finance & Economics, Nanjing, 210023, China4. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | Evaluation of the impact of the public health emergencies on intercity travel during holidays is of great significance for scientifically preventing the spread of the epidemic and ensuring the safety of intercity travel. Intercity travel data obtained by the Baidu migration platform is available to systematically explore the changes of time series, patterns and characteristics of the travel flows of the intercity travel during the May Day holiday under the influence of the COVID-19 epidemic. The formation mechanism of intercity travel under the background of the superposition of epidemics and holidays is revealed based on the spatial econometric models. The results are as follows: Affected by the COVID-19 epidemic, the scale of intercity travel during the May Day holiday in 2020 dropped by 46.0% compared with 2019. The fluctuation of intercity travel in the study period is mainly characterized by the fluctuation within the province, and the pattern of interprovincial intercity travel is generally stable. The region most seriously affected by the epidemic is northeast China, followed by the eastern and central China, and the last is western China. The COVID-19 epidemic significantly restricted the intercity travel during the May Day holiday. Compared with normal years (the same period of 2015), nearly 70% of the holiday intercity travel routines are limited within a range of 400 km, and 70% of the routines are concentrated within 250 km affected by the epidemic. Urban attractive factors such as GDP, urbanization rate, administrative level, and traffic connectivity variables such as highway density, connectivity of high-speed rail and aviation are the main factors affecting intercity travel during the May Day holiday period. However, the impact of each variable on intercity travel has temporal heterogeneity during different periods in holiday. Highway density and high-speed rail have a significant positive effect. The urban rate has a significant negative effect on intercity travel during the leaving period of the holiday, but a positive effect on it during the return period. The richness of tourism resources is only significant during the leaving period. Finally, this paper summarizes the formation mechanism of holiday intercity travel under the influence of the pandemic. |
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| Keywords: | COVID-19 epidemic May Day holiday intercity travel spatial econometric models public health emergency |
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