Study on spatial differences and driving factors of tourism economy in Wuling Mountain area.

Taking 71 counties (cities and districts) in the Wuling Mountain area as the research object and with the help of the GeoDA software, in this work, we revealed the spatial differentiation of the total tourism income in 2018. On the basis of this result, the GWR model was employed to subsequently analyze the economic development level, resource endowment conditions and tourism infrastructure. The driving factors of tourism economy were analyzed from three angles. Our results are as follows. (1) The total tourism revenue of Wuling Mountain is spatially normal, but Moran s I value is only 0.153, indicating that the existing spatial agglomeration effect is weak. (2) From the LISA map, it can be seen that high-value hotspots are mainly distributed in Wulingyuan District, Lichuan City and Songtao Miao Autonomous County with good traffic locations and endowment of tourism resources. The radiation driving effect is weak; low-value cold spot areas are mainly distributed in areas with low economic development levels in the south, suggesting that there is a high spatial correlation between poverty and low tourism economic development levels. (3) GDP per capita, the proportion of tertiary industry in GDP, the number of scenic spots above 3A level, the number of national intangible cultural heritage, the density of highways. and the number of hotels above 3 stars are the main factors impacting the spatial pattern of tourism economy in the Wuling Mountain area.