Study on spatio-temporal distribution characteristics and driving factors of travelers in natural tourist destinations based on multi-source data
In order to truly reflect the behavior of travelers and optimize the planning and management of natural tourism destinations,this study took the traveler marker points in the"two-step road"as the data source and the natural tourism destination was defined ac-cording to the concentration degree of the marker points as the research object.With the help of GIS spatio-temporal analysis tools and geographic detector,the spatio-temporal dis-tribution characteristics of travelers were summarized.The natural environment factors,hu-man and social factors were selected as driving indicators to explore the driving factors of the spatial distribution of travelers in the study area.The results of the study showed that:(1)Traveler activities showed obvious spatial heterogeneity characteristics,forming 27 hot areas of traveler activities.(2)The interannual distribution of travelers was in a state of agglomer-ation and the nearest neighbor index was in the form of a"U"-shaped curve.The spatial dis-tribution was relatively concentrated,but the interannual changes in hotspot areas was obvi-ous.The agglomeration of"single core"to"parallel multi-core"and then to"double core"and"single core",which indicated that the internal competition pattern of the tourist desti-nation was in change.(3)Travelers gathered in summer and autumn,the hot spots for trav-el activities were relatively concentrated,but the spatial distribution of travelers in different seasons was obviously different.(4)Attractions,catering,accommodation and other service facilities were the determinants of the spatial differentiation of travelers activities,among which the attractions were the dominant factors.In conclusion,the spatio-temporal big data mainly based on traveler marked points could describe the tourist behavior characteristics of natural tourist destinations in more detail.
multi-source datanatural tourism destinationsspatio-temporal distribution char-acteristicsgeographical detectors
NETL
NSTL
万方数据
维普
