Abstract: The downtown area of Shanghai has rich tourism resources and numerous commercial, historical and cultural blocks, which attracts a lot of tourists every year. This paper touched on the method of mining data by grabbing the POI data from the social network Panoramio. According to the first law of geography, the paper aims to explore the tourists POI spatial static distribution and temporal and spatial dynamic variation by Arcgis, spatial trend surface modeling and so on. The study shows that the number and density distribution of POI is extremely uneven. The high level of the tourism area, large commercial, entertainment area, historic district area presents high degree of concentration, while the areas with dense residential areas gain very limited attention of oversea tourists. The number and distribution of tourists POI also changed greatly by month and time. The study aims to explore tourists' preference, provide guidance of the distribution and management of tourism services and tourist grooming.

摘要： 上海中心城区有着丰富的旅游资源及众多的商业区、历史文化街区等，每年都吸引大量的海内外游客造访。本文通过网络爬虫方式，从社交网络Panoramio获取海外游客相关兴趣点（POI）数据，在地理学第一定律的理论基础上，运用ArcGIS空间热点分析、空间趋势面建模等方法，探索上海中心城区海外游客兴趣点（POI）的时空分布特征。研究发现，上海中心城区各区POI的数量和密度分布极不均衡，高级别的旅游区、大型商业区、娱乐区、历史街区等区域POI集聚度较高，密集住宅区、缺乏游览场所、城市公园、商业设施、娱乐设施的区域密集度很低。随着月份与每日时段变化，游客POI数量分布也发生很大变化。研究旨在探索海外游客偏好空间行为特征，以期为上海世界著名旅游城市建设中目的地营销、公共服务布局、大游客疏导提供指导。