The spatial aggregation pattern, characteristic and driving mechanism of recreational region around metropolises: A case study in Beijing, China

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Abstract

The research on spatial pattern and development regularity of recreational regions around metropolises is the important theoretical basis of urban planning. But in current times there are few quantitative studies on it. Selecting 1172 samples of recreational regions in Beijing, using the function of Nearest Neighbor Indicator (NNI) and the spatial analysis and geographical statistical function of GIS software, the authors do some work to quantitatively describe the spatial pattern and structure of recreational region around metropolises, based on the space statistical unit of type and different distance. Analysis results show that the recreational regions around Beijing metropolis generally present the typical spatial clustering status. But differences between different types of aggregation status are significant. The aggregation level of cultural sightseeing type is the highest, while sports relaxation type presents random distribution status. The spatial aggregation of different regions has greater differentiation. The recreational regions within the 40-60Km from the city center have rich types, and present the high degree of aggregation pattern. The driving mechanism analysis of spatial aggregation indicates that the distance from the urban centers, the landform, rivers and other factors of natural features have an important impact on the spatial aggregation of recreational regions. The quantitative research on spatial aggregation pattern and spatial differentiation of the recreational region around metropolises can identify its spatial pattern and development mechanism, and provide a reference for making urban development planning reasonably.

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Guo, F., Ma, L., Li, R., Zhang, J., & Fu, X. (2010). The spatial aggregation pattern, characteristic and driving mechanism of recreational region around metropolises: A case study in Beijing, China. In 2010 18th International Conference on Geoinformatics, Geoinformatics 2010. https://doi.org/10.1109/GEOINFORMATICS.2010.5568138

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