中国A级旅游景点空间分布特征与可达性

以A级景点为例，基于GIS 技术，通过最近邻指数、K指数、热点聚类等方法分析中国2 424 个A级旅游景点的空间分布特征；运用栅格成本加权距离算法，计算中国A级旅游景点的空间可达性，并测算县域单元的整体可达性；利用空间关联方法分析了县域可达性的空间差异。结果表明：中国A级景点的空间分布总体上呈现出聚集分布的特点，所有景点的平均可达时间为125.88 min，60%的景点可达时间在90 min 以内；可达性在全国的分布差异十分明显，可达性空间分布具有明显的交通指向性。景点的县域可达性呈强集聚格局，可达性热点区域的分布呈现明显的热点—次热点—次冷点—冷点自东向西带状分布的格局。

Spatial Distribution Characteristics and Accessibility of A-grade Tourist Attractions in China

Scenic spot is a very important carrier of tourism activities. The study of the spatial structure of tourism is receiving increasing attention but methodology so far has used qualitative rather than quantitative methods. The A-grade tourist attraction is a tourist ranking classifiable system with Chinese characteristics and is a national standard of comprehensive evaluation about scenic spot quality and grade in China. Besides the attraction of scenic spots, enhancing accessibility and perfecting infrastructure in scenic spots are very important for their tourism development. Therefore, the research on spatial distribution structure and accessibility of A-grade scenic spots are meaningful. Based on an investigation of 2424 National A-grade tourist attractions and using GIS and some quantitative analysis methods, such as Nearest Neighbor Index (NNI), Ripley's K function, hot spot clustering, the spatial structure of tourist attractions were investigated, with their characteristics and distribution for different strategies being discussed. Based on matrix raster data covering the whole space, this paper calculates spatial accessibility of all counties in China using cost weighted distance method and ArcGIS as platforms. Then we discuss spatial differences of county accessibility of scenic spots by using ESDA (Exploratory Spatial Data Analysis). The results show that general scenic spots exhibit an aggregated distribution. Considering the accessibility, we find that the human scenic spots are more centralized. The average accessibility is about 125.88 minutes, and the area where the accessibility of scenic spots is within 90 minutes reaches 60%, while the area where the accessibility is within 30 minutes accounts for 26.65% and the longest time needs 1260 minutes which is located at central Tibetan Plateau. Distribution of the accessibility has pointed to traffic line. At county level, the estimated values of Moran's I is positive numbers using analysis of spatial association. All the test results indicate that tourist attractions and adjacent areas show strong positive correlation. Distribution of hot spots regarding the accessibility shows an obvious hot spots－sub-hotspots－sub-cold spots－cold spots zonal distribution pattern from east to west. Cold spots are distributed in the border zone of Tibet, Xinjiang and Qinghai. On the basis of the above results, we identify five factors which impact the spatial structure and accessibility of scenic spots: natural environment, economic development, traffic condition, population and rating system. Finally, some recommendations are given for optimization of the spatial structure of scenic spots, involving quickening the development of edge district's tourism, coordinating the development of the tourism industry for each region, and enhancing basic infrastructure of transportation especially that of the provincial border-regions.