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COVID-19: A Comparative Study of Population Aggregation Patterns in the Central Urban Area of Tianjin, China

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  • Peng Zeng

    (School of Architecture, Tianjin University, Tianjin 300272, China)

  • Zongyao Sun

    (School of Architecture, Tianjin University, Tianjin 300272, China)

  • Yuqi Chen

    (Tianjin University Research Institute of Architectural Design & Urban Planninng Co., Ltd, Tianjin 300350, China)

  • Zhi Qiao

    (School of Environmental Science and Engineering, Tianjin University, Tianjin 300350, China)

  • Liangwa Cai

    (School of Architecture, Tianjin University, Tianjin 300272, China)

Abstract

When a public health emergency occurs, a potential sanitation threat will directly change local residents’ behavior patterns, especially in high-density urban areas. Their behavior pattern is typically transformed from demand-oriented to security-oriented. This is directly manifested as a differentiation in the population distribution. This study based on a typical area of high-density urban area in central Tianjin, China. We used Baidu heat map (BHM) data to calculate full-day and daytime/nighttime state population aggregation and employed a geographically weighted regression (GWR) model and Moran’s I to analyze pre-epidemic/epidemic population aggregation patterns and pre-epidemic/epidemic population flow features. We found that during the COVID-19 epidemic, the population distribution of the study area tended to be homogenous clearly and the density decreased obviously. Compared with the pre-epidemic period: residents’ demand for indoor activities increased (average correlation coefficient of the floor area ratio increased by 40.060%); traffic demand decreased (average correlation coefficient of the distance to a main road decreased by 272%); the intensity of the day-and-night population flow declined significantly (its extreme difference decreased by 53.608%); and the large-living-circle pattern of population distribution transformed to multiple small-living circles. This study identified different space utilization mechanisms during the pre-epidemic and epidemic periods. It conducted the minimum living security state of an epidemic-affected city to maintain the operation of a healthy city in the future.

Suggested Citation

  • Peng Zeng & Zongyao Sun & Yuqi Chen & Zhi Qiao & Liangwa Cai, 2021. "COVID-19: A Comparative Study of Population Aggregation Patterns in the Central Urban Area of Tianjin, China," IJERPH, MDPI, vol. 18(4), pages 1-15, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:2135-:d:503764
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    as
    1. Olsen, Jonathan R. & Mitchell, Richard & McCrorie, Paul & Ellaway, Anne, 2019. "Children's mobility and environmental exposures in urban landscapes: A cross-sectional study of 10–11 year old Scottish children," Social Science & Medicine, Elsevier, vol. 224(C), pages 11-22.
    2. Fang Wang & Zhao Liu & Shanshan Shang & Yuelei Qin & Bihu Wu, 2019. "Vitality continuation or over-commercialization? Spatial structure characteristics of commercial services and population agglomeration in historic and cultural areas," Tourism Economics, , vol. 25(8), pages 1302-1326, December.
    3. Meihan Jin & Lu Liu & De Tong & Yongxi Gong & Yu Liu, 2019. "Evaluating the Spatial Accessibility and Distribution Balance of Multi-Level Medical Service Facilities," IJERPH, MDPI, vol. 16(7), pages 1-19, March.
    4. Wang, Shaojian & Shi, Chenyi & Fang, Chuanglin & Feng, Kuishuang, 2019. "Examining the spatial variations of determinants of energy-related CO2 emissions in China at the city level using Geographically Weighted Regression Model," Applied Energy, Elsevier, vol. 235(C), pages 95-105.
    5. Peter Headicar, 2013. "The Changing Spatial Distribution of the Population in England: Its Nature and Significance for 'Peak Car'," Transport Reviews, Taylor & Francis Journals, vol. 33(3), pages 310-324, May.
    6. Larson, Lincoln R. & Keith, Samuel J. & Fernandez, Mariela & Hallo, Jeffrey C. & Shafer, C. Scott & Jennings, Viniece, 2016. "Ecosystem services and urban greenways: What's the public's perspective?," Ecosystem Services, Elsevier, vol. 22(PA), pages 111-116.
    7. Deyi Feng & Lingli Tu & Zhongwei Sun, 2019. "Research on Population Spatiotemporal Aggregation Characteristics of a Small City: A Case Study on Shehong County Based on Baidu Heat Maps," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    8. Fang Wang & Fang-qu Niu, 2019. "Urban Commercial Spatial Structure Optimization in the Metropolitan Area of Beijing: A Microscopic Perspective," Sustainability, MDPI, vol. 11(4), pages 1-18, February.
    9. Lan Ma & Nianxue Luo & Taili Wan & Chunchun Hu & Mingjun Peng, 2018. "An Improved Healthcare Accessibility Measure Considering the Temporal Dimension and Population Demand of Different Ages," IJERPH, MDPI, vol. 15(11), pages 1-19, October.
    10. Yanyan Chen & Hanqiang Qian & Yang Wang, 2020. "Analysis of Beijing’s Working Population Based on Geographically Weighted Regression Model," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    11. Xinliang Xu & Shihao Wang & Jinhui Dong & Zhicheng Shen & Shuwan Xu, 2020. "An analysis of the domestic resumption of social production and life under the COVID-19 epidemic," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-15, July.
    12. Essam A. Rashed & Sachiko Kodera & Jose Gomez-Tames & Akimasa Hirata, 2020. "Influence of Absolute Humidity, Temperature and Population Density on COVID-19 Spread and Decay Durations: Multi-Prefecture Study in Japan," IJERPH, MDPI, vol. 17(15), pages 1-14, July.
    13. Heather Allen & Rebecca Katz, 2010. "Demography and Public Health Emergency Preparedness: Making the Connection," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 29(4), pages 527-539, August.
    14. Zuo Zhang & Yangxiong Xiao & Xiang Luo & Min Zhou, 2020. "Urban human activity density spatiotemporal variations and the relationship with geographical factors: An exploratory Baidu heatmaps‐based analysis of Wuhan, China," Growth and Change, Wiley Blackwell, vol. 51(1), pages 505-529, March.
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    1. Ming Sun & Xueyu Jiao, 2023. "Quantitative Identification Study of Epidemic Risk in the Spatial Environment of Harbin City," Sustainability, MDPI, vol. 15(9), pages 1-22, May.

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