The evolution of spatiotemporal patterns and influencing factors of high-level tourist attractions in the Yellow River Basin

Abstract

Introduction High-level tourist attractions (HLTAs) are essential components of high-quality tourism development in the Yellow River Basin. In the context of holistic tourism and mass tourism, it is necessary to re-examine the spatial pattern of HLTAs. Methods Selecting the Qing–Gan–Ning region of the Yellow River Basin as a case study site, based on the data on 590 high-level tourist attractions in 2009, 2015, and 2021, and with the help of ArcGIS10.8 spatial analysis tools, the nearest neighbor index, kernel density analysis, and standard deviation ellipse methods, such as ellipse and ESDA spatial exploratory analysis, were used to analyze the spatiotemporal pattern of the spatial distribution of high-level tourist attractions in the study area from the aspects of type, density, and spatial autocorrelation. Overlay analysis, buffer analysis, and other methods were used to select the influencing factors, and finally, the influencing factors were verified with the help of GeoDetector. Conclusions The conclusions are as follows: the NNI values for the Qing–Gan–Ning area of the Yellow River Basin are 0.699, 0.7, and 0.618, and the spatial structure type was clustered. The distribution density showed an evolutionary trend of point-like agglomeration and linear expansion, with the provincial capital as the core and the Yellow River as the axis. The distribution density of high-level tourist attractions is 27, 44, and 74 per 10,000 km 2 . In terms of the dynamic distribution direction of the center of mass, there was little interannual variation, showing a northeast–southwest direction, which is consistent with the flow direction of the Yellow River in the region. Furthermore, the analysis of Moran’s I index showed clear spatial autocorrelation at the county scale. HLTAs exhibited clustering and wider distribution in H–H and L–L zones, while the L–H and H–L zones displayed a more dispersed and narrower distribution. The order of factors affecting the spatial distribution of HLTAs was economic factors (0.5257) > social factors (0.5235) > natural factors (0.491), and interactive detection showed that there were two-factor enhancements and nonlinear enhancements in the factors. Dicussions This study contributes to the conservation development and sustainable development of ecotourism resources in the Yellow River Basin.

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