Measurement of accessibility of self-driving tour during Golden Week based on spatio-temporal utility method
Based on the theoretical foundation of time geography,this study focuses on 4A and above scenic spots in Yunnan Province,and employs the spatiotemporal utility method to develop a Golden Week self-driving travel accessibility measurement model that takes into account the spatiotemporal constraints of self-driving travel and the attractiveness of scenic spots.The multi-scale geographically weighted regression model(MGWR)is utilized to investigate its influencing factors.The results show that:1)The Golden Week self-driving travel accessibility is jointly influenced by the attractiveness of scenic area,spatial and temporal limitations,forming high accessibility areas in central Yunnan,western Yunnan,and southeastern Yunnan,and decreasing towards areas with scarce resources and insufficient transportation accessibility.2)The Golden Week self-driving travel accessibility is classified into four categories of highly efficient connectivity,balanced accessibility,limited constraints,and marginal vulnerability using K-means clustering,in which the highly efficiently connected scenic area account for about 1/5 of the total,while balanced accessible and limited constraint scenic area together account for about 70%of the total.3)Using the MGWR model to deeply analyze the influence of natural and human factors on the accessibility of self-driving tours,it is found that the comprehensive transportation convenience plays a decisive role in the development of the Golden Week self-driving travel accessibility,while the direct contribution of scenic area resource endowment is relatively weak.
Golden Week self-driving travelspace-time utility measureaccessibilitymulti-scale geographically weighted regressioninfluencing factors
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