Mobile phone data provide a more complete and accurate description of tourism transportation demand than traditional and Internet data sources. In this paper, a framework is proposed to determine spatial correlations between tourism destinations, rest places, and transportation hubs based on mobile phone data. Firstly, nine rules for identifying visitors based on four spatial and temporal features are established. Then, the spatial correlations are analyzed from three aspects. A case study of Shanghai is carried out to verify the proposed methodology, and the addition of a tour bus network based on the evaluation of transportation accessibility is discussed. It is concluded that tourists tend to rest near next-day destinations and choose transportation hubs in the city center. The rest places that are sightseeing destinations, amusement parks, and convention centers exhibit polycentric characteristics. The research framework and results of this study are useful for tourism transportation planning.

与传统和Internet数据源相比，移动电话数据可以更完整，准确地描述旅游交通需求。本文提出了一个框架，用于基于手机数据确定旅游目的地，休憩场所和交通枢纽之间的空间相关性。首先，建立了基于四个时空特征识别访客的九种规则。然后，从三个方面分析了空间相关性。以上海为例，验证了所提方法的有效性，并讨论了基于交通可达性评估而增加的旅游巴士网络。结论是，游客倾向于在第二天的目的地附近休息，并选择市中心的交通枢纽。其余的观光景点，游乐园，会议中心表现出多中心的特征。本研究的研究框架和结果对旅游交通规划很有帮助。