Spatial differentiation characteristics of regional self-driving tourism flow: A case study of central Yunnan urban agglomeration
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
Heliyon
Abstract
The aim of this study was investigate the spatial effects of A-class scenic spots and the spatial
distribution of highway networks on the influence of self-driving tour behavioral patterns in
China at the urban agglomeration scale, based on big data of road traffic during three holidays. A
spatial analysis method and a geographically weighted regression model were used to analyze the
spatial distribution differences and influencing factors of self-driving tourism flows in the central
Yunnan urban agglomeration. The results showed that holiday self-driving tourism in the central
Yunnan urban agglomeration presented a typical core-edge spatial pattern. The mean value of the
spatial autocorrelation coefficient was 0.54, indicating significant spatial autocorrelation. The
influence of tourism resources and traffic conditions on self-driving tourism flow showed a
decreasing trend from the center of the high positive value to the periphery of the main urban
area of Kunming. This study reveals the spatial differentiation characteristics of self-driving
tourism flows in urban agglomerations and lays a theoretical foundation for understanding
flow pattern.
Description
Heliyon 9 (2023) e21814
Keywords
Traffic engineering,Traffic accessibility,Geographically weighted regression,Spatial heterogeneity,Tourism transport