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Volume 11
Issue 7
10.3390/land11070990
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Article

Using Crowdsourced Big Data to Unravel Urban Green Space Utilization during COVID-19 in Guangzhou, China

by
Shuhao Liu
1,
Chang Su
2,
Ruochen Yang
1,
Jianye Zhao
1,
Kun Liu
1,
Kwangmin Ham
3,
Shiro Takeda
1 and
Junhua Zhang
1,*
1
Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan
2
School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China
3
Gangneung-si Public Design Promotion Committee, 33 Gangneung Daero, Gangneung-si 25522, Gangwon-do, Korea
*
Author to whom correspondence should be addressed.
Land 2022, 11(7), 990; https://doi.org/10.3390/land11070990
Submission received: 21 May 2022 / Revised: 25 June 2022 / Accepted: 28 June 2022 / Published: 29 June 2022
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Abstract

Urban green spaces (UGSs) can meet the spiritual and cultural needs of citizens and provide various ecosystem services. In the context of the COVID-19 pandemic, the utilization of UGSs has been affected in various countries worldwide. This study considered 13 UGSs in Guangzhou, China, as examples. It obtained user check-in data by sampling the check-in pages of Sina Weibo locations using a Python-based web crawler program. The study was conducted for 731 days from 1 October 2019 to 30 September 2021, during different phases of the pandemic. Based on automated Chinese corpus recognition technology, statistical results were obtained after periodization and sentiment calculation. The study assessed the pandemic’s impact on the use of UGSs by analyzing the time, frequency, and emotions of residents visiting UGSs. The study concluded that the emotions of UGS users during COVID-19 tended to be positive. They tended to choose UGSs with low expected population density and visited UGSs on weekdays. Additionally, the religious attributes of UGSs also influenced their utilization.
Keywords: urban green spaces; urban green space utilization; expected population density; religious attributes; emotions; COVID-19 urban green spaces; urban green space utilization; expected population density; religious attributes; emotions; COVID-19

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MDPI and ACS Style

Liu, S.; Su, C.; Yang, R.; Zhao, J.; Liu, K.; Ham, K.; Takeda, S.; Zhang, J. Using Crowdsourced Big Data to Unravel Urban Green Space Utilization during COVID-19 in Guangzhou, China. Land 2022, 11, 990. https://doi.org/10.3390/land11070990

AMA Style

Liu S, Su C, Yang R, Zhao J, Liu K, Ham K, Takeda S, Zhang J. Using Crowdsourced Big Data to Unravel Urban Green Space Utilization during COVID-19 in Guangzhou, China. Land. 2022; 11(7):990. https://doi.org/10.3390/land11070990

Chicago/Turabian Style

Liu, Shuhao, Chang Su, Ruochen Yang, Jianye Zhao, Kun Liu, Kwangmin Ham, Shiro Takeda, and Junhua Zhang. 2022. "Using Crowdsourced Big Data to Unravel Urban Green Space Utilization during COVID-19 in Guangzhou, China" Land 11, no. 7: 990. https://doi.org/10.3390/land11070990

APA Style

Liu, S., Su, C., Yang, R., Zhao, J., Liu, K., Ham, K., Takeda, S., & Zhang, J. (2022). Using Crowdsourced Big Data to Unravel Urban Green Space Utilization during COVID-19 in Guangzhou, China. Land, 11(7), 990. https://doi.org/10.3390/land11070990

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