Spatial Patterns of Chinese Inbound Tourist POI: an Analysis of Geographic Information from Web Pictures
利用Flickr照片的地理位置数据，通过DBScan聚类和GIS空间分析，揭示中国入境游客兴趣点的空间分布特征，发现从东向西递减的格局和不同客源地的偏好差异。
Through open data interface of a famous social photo websites(flickr.com), this paper first collected and sorted out photo data of inbound tourism in China which are uploaded by overseas tourists from 2008 to 2013 by using computer programs. Furthermore, information of geographical position coordinates involved in these pictures are analyzed by using DBScan clustering analysis method to calculate geographical points of interest(POI) of Inbound Tourists to China, and a further statistical analysis with classification was performed. Based on these previous data, paper made use of GIS spatial analysis methods, trying to figure out spatial distribution features of POI,and conducted a comparative analysis on preferential POI selection of tourists from different origins. The results show that: 1)The distribution of POI among inbound tourists to China has a significant feature of spatial differentiation with gradually decreasing trend from east to west, and has formed a basic spatial pattern of the firstclass central belt, secondary central area, tertiary dots enclave; 2)The first- class central belt contains three core areas, and inbound tourists' POI in each core area also has characteristics of spatial heterogeneity and imbalance;4)With high spatial aggregation of POI distribution in inbound tourism, time- series clustering has a tendency of gradually balanced development. 3)With high aggregation of POI in each tourist market, there is also a significant difference involved in spatial clustering due to discrepancies in preference of tourists from various markets.The paper aims to provide a new perspective and analysis method to explore spatial characteristics of inbound tourism market, and strives to obtain a more accurate and objective understanding of development status of inbound tourism in China, so as to provide some theoretical references for sustainable development of inbound tourism.