The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing
The COVID-19 pandemic is a major challenge for society as a whole, and analyzing the impact of the spread of the epidemic and government control measures on the travel patterns of urban residents can provide powerful help for city managers to designate top-level epidemic prevention policies and spec...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/7/479 |
| _version_ | 1797526973158785024 |
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| author | Yihang Li Liyan Xu |
| author_facet | Yihang Li Liyan Xu |
| author_sort | Yihang Li |
| collection | DOAJ |
| description | The COVID-19 pandemic is a major challenge for society as a whole, and analyzing the impact of the spread of the epidemic and government control measures on the travel patterns of urban residents can provide powerful help for city managers to designate top-level epidemic prevention policies and specific epidemic prevention measures. This study investigates whether it is more appropriate to use groups of POIs with similar pedestrian flow patterns as the unit of study rather than functional categories of POIs. In this study, we analyzed the hour-by-hour pedestrian flow data of key locations in Beijing before, during, and after the strict epidemic prevention and control period, and we found that the pedestrian flow patterns differed greatly in different periods by using a composite clustering index; we interpreted the clustering results from two perspectives: groups of pedestrian flow patterns and functional categories. The results show that depending on the specific stage of epidemic prevention and control, the number of unique pedestrian flow patterns decreased from four before the epidemic to two during the strict control stage and then increased to six during the initial resumption of work. The restrictions on movement are correlated with most of the visitations, and the release of restrictions led to an increase in the variety of unique pedestrian flow patterns compared to that in the pre-restriction period, even though the overall number of visitations decreased, indicating that social restrictions led to differences in the flow patterns of POIs and increased social distance. |
| first_indexed | 2024-03-10T09:37:53Z |
| format | Article |
| id | doaj.art-0d7c4d4da812452590aba4babcf9a7c9 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T09:37:53Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-0d7c4d4da812452590aba4babcf9a7c92023-11-22T03:55:09ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-07-0110747910.3390/ijgi10070479The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from BeijingYihang Li0Liyan Xu1College of Urban and Environmental Sciences, Peking University, Beijing 100871, ChinaCollege of Architecture and Landscape Architecture, Peking University, Beijing 100871, ChinaThe COVID-19 pandemic is a major challenge for society as a whole, and analyzing the impact of the spread of the epidemic and government control measures on the travel patterns of urban residents can provide powerful help for city managers to designate top-level epidemic prevention policies and specific epidemic prevention measures. This study investigates whether it is more appropriate to use groups of POIs with similar pedestrian flow patterns as the unit of study rather than functional categories of POIs. In this study, we analyzed the hour-by-hour pedestrian flow data of key locations in Beijing before, during, and after the strict epidemic prevention and control period, and we found that the pedestrian flow patterns differed greatly in different periods by using a composite clustering index; we interpreted the clustering results from two perspectives: groups of pedestrian flow patterns and functional categories. The results show that depending on the specific stage of epidemic prevention and control, the number of unique pedestrian flow patterns decreased from four before the epidemic to two during the strict control stage and then increased to six during the initial resumption of work. The restrictions on movement are correlated with most of the visitations, and the release of restrictions led to an increase in the variety of unique pedestrian flow patterns compared to that in the pre-restriction period, even though the overall number of visitations decreased, indicating that social restrictions led to differences in the flow patterns of POIs and increased social distance.https://www.mdpi.com/2220-9964/10/7/479public health eventskey urban areaspedestrian flow change patternstime series clustering |
| spellingShingle | Yihang Li Liyan Xu The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing ISPRS International Journal of Geo-Information public health events key urban areas pedestrian flow change patterns time series clustering |
| title | The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing |
| title_full | The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing |
| title_fullStr | The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing |
| title_full_unstemmed | The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing |
| title_short | The Impact of COVID-19 on Pedestrian Flow Patterns in Urban POIs—An Example from Beijing |
| title_sort | impact of covid 19 on pedestrian flow patterns in urban pois an example from beijing |
| topic | public health events key urban areas pedestrian flow change patterns time series clustering |
| url | https://www.mdpi.com/2220-9964/10/7/479 |
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