SPATIAL CLUSTERING HOTSPOT DETECTION,SPATIAL CLUSTERING HOTSPOT DETECTION,DISTRIBUTION AND INFLUENCING FACTORS OF RURAL HOMESTAY INNS——A CASE FROM GUIZHOU PROVINCE
It is of great importance to explore the distribution and influencing factors of spatial clustering hotspots of rural homestay inns to promote the clusterization and high-quality development of rural homestay inns.Taking 6319 rural homestay inns in Guizhou province as the research sample and applying the Density Based Hotspots Detector and Geodetector to investigate the spatial clustering hotspots and influencing factors of rural homestay inns.The results were found as follows.(1) Rural homestay ins in Guizhou formed 361 spatial clustering hotspots,including 40 large-scale hotspots,136 mid-scale hotspots,and 185 small-scale hotspots.(2) Rural homestay inn hotspots were mainly located in areas with rich tourism resources,favorable ecological status,convenient transportation facilities,good natural resources,clustering of related industries,and low-medium socio-economic performance.(3) The spatial heterogeneity of rural homestay inn hotspots was co-dominated by tourism resources and relevant industries,and strongly affected by ecological environment and transportation conditions,while the influence of the remaining factors was weak.(4) The clustering distribution of rural homestay inns in areas with rich tourism resources,clustering of related industries,favorable ecological environment,and convenient transportation conditions,and these were the main reasons for the formation of rural homestay hotspots.In the future,we should firmly grasp the distribution characteristics of rural homestays,further enhance the concentration degree of tourism resources and the concentration degree of related business forms,continue to improve the ecological environment and infrastructure,promote the development of rural homestays and the construction of agglomeration areas,andpromote the high-quality development of rural homestays.
rural homestay innsclustering hotspot detectionspatial hotspotsinfluencing factorsGuizhou province
NETL
NSTL
万方数据
