Exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering: Take the main area of Wuhan, China as an example
Urban tourism space is the primary area where tourism activities occur and a key driver of regional tourism space evolution. To explore the correlation between population aggregation and urban tourism spatial heterogeneity in the big data era, this study focuses on Wuhan's main urban area in 20...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2025-10-01
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| Series: | Frontiers of Architectural Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095263525000378 |
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| author | Xincan Yu Hong Xu Yuelin Yan |
| author_facet | Xincan Yu Hong Xu Yuelin Yan |
| author_sort | Xincan Yu |
| collection | DOAJ |
| description | Urban tourism space is the primary area where tourism activities occur and a key driver of regional tourism space evolution. To explore the correlation between population aggregation and urban tourism spatial heterogeneity in the big data era, this study focuses on Wuhan's main urban area in 2023. Using the Geographically Weighted Regression model, it analyzes the factors influencing tourism spatial heterogeneity. Additionally, Baidu Heat map data is employed to identify crowd aggregation levels during holidays, revealing the distribution patterns of urban tourism space. The results indicate that (1) factors derived from the GWR model significantly influence the number of tourism spaces in Wuhan, with evident spatial differences; (2) based on the spatial matching of heterogeneity factors and crowd aggregation levels, urban tourism space can be categorized into six types, including five core tourism spaces and other scattered spaces. This research highlights the spatial heterogeneity of urban tourism in Wuhan and provides a scientific basis for the transformation and quality improvement of urban tourism space by exploring the impact of population activity density. |
| format | Article |
| id | doaj-art-4f580927f9cf4927a07328e6d48ab48d |
| institution | DOAJ |
| issn | 2095-2635 |
| language | English |
| publishDate | 2025-10-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Frontiers of Architectural Research |
| spelling | doaj-art-4f580927f9cf4927a07328e6d48ab48d2025-08-20T02:52:37ZengKeAi Communications Co., Ltd.Frontiers of Architectural Research2095-26352025-10-011451328134910.1016/j.foar.2025.03.002Exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering: Take the main area of Wuhan, China as an exampleXincan Yu0Hong Xu1Yuelin Yan2School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, ChinaSchool of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China; Hubei Provincial Engineering Research Center of Urban Regeneration, Wuhan University of Science and Technology, Wuhan 430065, China; Corresponding author. School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China.School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, ChinaUrban tourism space is the primary area where tourism activities occur and a key driver of regional tourism space evolution. To explore the correlation between population aggregation and urban tourism spatial heterogeneity in the big data era, this study focuses on Wuhan's main urban area in 2023. Using the Geographically Weighted Regression model, it analyzes the factors influencing tourism spatial heterogeneity. Additionally, Baidu Heat map data is employed to identify crowd aggregation levels during holidays, revealing the distribution patterns of urban tourism space. The results indicate that (1) factors derived from the GWR model significantly influence the number of tourism spaces in Wuhan, with evident spatial differences; (2) based on the spatial matching of heterogeneity factors and crowd aggregation levels, urban tourism space can be categorized into six types, including five core tourism spaces and other scattered spaces. This research highlights the spatial heterogeneity of urban tourism in Wuhan and provides a scientific basis for the transformation and quality improvement of urban tourism space by exploring the impact of population activity density.http://www.sciencedirect.com/science/article/pii/S2095263525000378Tourism spaceCorrelation studySpatial heterogeneityGWR modelHeat map on Baidu map Extension |
| spellingShingle | Xincan Yu Hong Xu Yuelin Yan Exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering: Take the main area of Wuhan, China as an example Frontiers of Architectural Research Tourism space Correlation study Spatial heterogeneity GWR model Heat map on Baidu map Extension |
| title | Exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering: Take the main area of Wuhan, China as an example |
| title_full | Exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering: Take the main area of Wuhan, China as an example |
| title_fullStr | Exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering: Take the main area of Wuhan, China as an example |
| title_full_unstemmed | Exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering: Take the main area of Wuhan, China as an example |
| title_short | Exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering: Take the main area of Wuhan, China as an example |
| title_sort | exploring the correlation between spatial heterogeneity of urban tourism and the degree of crowd gathering take the main area of wuhan china as an example |
| topic | Tourism space Correlation study Spatial heterogeneity GWR model Heat map on Baidu map Extension |
| url | http://www.sciencedirect.com/science/article/pii/S2095263525000378 |
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