基于多源数据的自然旅游地旅行者时空分布及其驱动因素

Study on spatio-temporal distribution characteristics and driving factors of travelers in natural tourist destinations based on multi-source data

为真实反映旅行者行为,优化自然旅游目的地的规划与管理,以“两步路”中的旅行者活动标记点作为数据源,根据标记点集中程度界定的自然旅游目的地为研究对象,借助GIS时空分析工具及地理探测器分析,总结旅行者的时空分布特征,并选取自然环境因子、人文社会因子作为驱动指标,探究旅行者空间分布的驱动因素。研究结果发现:(1)旅行者活动表现出明显的空间异质性特征,形成了27个旅行者活动热区。(2)旅行者年际分布处于集聚状态,最近邻指数呈现“U”型曲线形式,空间分布均比较集中,但热点区域年际变化明显,“单核心”集聚到“平行多核心”再到“双核心”“单核心”,说明该旅游目的地内部竞争格局处在变动中。(3)夏、秋2个季节旅行者活动集聚,旅行活动热区比较集中,但不同季节旅行者空间分布差异性明显。(4)景点、餐饮、住宿等服务设施是旅行者活动空间分异性的决定因素,其中景点是主导因素。综上所述,以旅行者标记点为主的时空大数据能更细致的刻画自然旅游地的旅游者行为特征。

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 according 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 distribution characteristics of travelers were summarized.The natural environment factors,human 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 agglomeration and the nearest neighbor index was in the form of a"U"-shaped curve.The spatial distribution was relatively concentrated,but the interannual changes in hotspot areas was obvious.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 destination was in change.(3)Travelers gathered in summer and autumn,the hot spots for travel 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.