4.3 Article

Spatial Distribution Characteristics of the Rural Tourism Villages in the Qinghai-Tibetan Plateau and Its Influencing Factors

Publisher

MDPI
DOI: 10.3390/ijerph19159330

Keywords

rural tourism; spatial distribution; influencing factor; geographic detector; Qinghai Tibetan plateau

Funding

  1. Second Tibetan Plateau Scientific Expedition and Research Program [2019QZKK1004]

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This paper analyzes the spatial distribution characteristics and influencing factors of rural tourism villages in the Qinghai-Tibetan Plateau using various spatial analysis methods. The results show that there is an agglomeration distribution tendency of rural tourism villages in the southeast and a sparse distribution in the northwest. The villages are mainly distributed in areas with favorable topographic and climate conditions, near roads and water sources, around cities, and close to tourism resources. Social-economic factors and tourism resources are the dominant factors influencing the distribution.
The development of rural tourism (RT) has great significance in reducing poverty and achieving rural vitalization. Qinghai-Tibetan Plateau (QTP) is a depressed area with rich RT resources due to its unspoiled nature and diverse culture. For future sustainable development of RT in QTP, this paper analyzes the spatial distribution characteristics and its influencing factors of RT villages using various spatial analysis methods, such as nearest neighbor index, kernel density estimation, vector buffer analysis, and geographic detectors. The results show the following. First, the RT villages present an agglomeration distribution tendency dense in the southeast and spare in the northwest. The inter-county imbalance distribution feature is obvious and four relatively high-density zones have been formed. Second, the RT villages have significant positive spatial autocorrelation, and the area of cold spots is larger and of hot spots is smaller. Third, the RT villages are mainly distributed with favorable topographic and climate conditions, near the road and water, around the city, and close to tourism resources. Fourth, the spatial distribution is the result of multifactor interactions. Socio-economic and tourism resource are the dominant factor in the mechanism network. Fifth, based on the above conclusions this study provides scientific suggestions for the sustainable development of the RT industry.

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