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

Abstract

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.

Keywords

Tourism space / Correlation study / Spatial heterogeneity / GWR model / Heat map on Baidu map Extension

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