Research on spatial differentiation and influencing factors of rural tourism industry based on POI data mining: A case study of Zhejiang province

Based on POI big data, spatial data measurement methods such as nearest neighbor distance analysis, kernel density estimation, Simpson diversity index and geographic detector model are used to quantitatively analyze the spatial distribution characteristics, mixed vitality and influencing factors of...

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Bibliographic Details
Published inZhejiang da xue xue bao. Journal of Zhejiang University. Sciences edition. Li xue ban Vol. 50; no. 4; pp. 483 - 494
Main Authors Ge, Dandong, Zheng, Yanyan, Tong, Lei
Format Journal Article
LanguageChinese
Published Hangzhou Zhejiang University 01.07.2023
Zhejiang University Press
Subjects
Agglomeration
Air quality
Big Data
Data mining
Deforestation
Economic conditions
Measurement methods
Natural resources
Regional development
Spatial data
Spatial distribution
Sustainable development
Tourism
Traffic
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Summary:Based on POI big data, spatial data measurement methods such as nearest neighbor distance analysis, kernel density estimation, Simpson diversity index and geographic detector model are used to quantitatively analyze the spatial distribution characteristics, mixed vitality and influencing factors of rural tourism industry in Zhejiang province. The results show that:（1） the rural tourism industry in Zhejiang province as a whole presents the spatial agglomeration characteristics of "two core areas and multiple growth poles";（2） the regional differences in the development level of the rural tourism industry in Zhejiang province are still significant. The industrial vitality in the north is significantly higher than that in the south;（3） the distribution of rural tourism industry in Zhejiang province is significantly affected by social and economic conditions, while the influence of traffic conditions is the weakest; the influence of the interaction of two factors is higher than that of a single factor, and produc
ISSN:1008-9497
DOI:10.3785/j.issn.1008-9497.2023.04.012