轨迹发生于地理空间之中，蕴含丰富的信息与知识，已成为数据库与空间信息等众多领域的研究热点，并取得了丰硕的研究成果。针对已有研究在轨迹-要素间复杂时空关联关系的建模与分析方面的不足，课题将面向丰富的地理空间上下文信息，开展针对大规模轨迹数据的地理空间关联解译及分析挖掘研究，主要工作包括：1）研究时空关联于地理空间要素的轨迹模型，将轨迹从点串数据升华为语义对象；2）研究Stop/Move对象的提取算法和轨迹-要素时空关联语义的计算方法，以及时空关联轨迹库的构建技术；3）面向时空关联轨迹库，从轨迹->要素、要素->轨迹、轨迹->轨迹三方面开展涵盖时空拓扑特征、时空访问特征、时空相关特征的轨迹数据查询分析；4）围绕轨迹-要素时空关联语义，开展轨迹相似性计算与频繁访问序列挖掘研究。通过课题研究，从地理空间关联角度丰富轨迹数据的分析手段，为建立大规模轨迹数据的应用分析系统奠定技术基础。

With the maturity of GPS, telecommunication and Web technology, and the wide adoption of GPS device, it is now relatively easy and cost-efficient to collect movement data of moving objects (like human beings, vehicles and wild animals) in the form of trajectory. As a result, massive amounts of trajectory data have been created in various areas. As trajectories always occur in the geographical space and carry richful information/knowledge,they have deep implications in many applications, e.g., location-based service, traffic control, city planning and animal protection. Consequently, more and more reseachers,particularly from the fields of spatial information and database,are attracted in the study on trajectory data, which resulted in abundant research results. However, the spatio-temporal relationships between trajectories and geographical features and their analytical applications have not been investigated too much, and therefore introduce great exploring potential. By linking trajectory with the contextual geogrphical information, this proposal will conduct comprehensive studies on geographically associated interpretation, analysis and mining for large trajectory dataset.The main work of this proposal includes: 1) Develop a spatio-temprally associated trajectory model that orientes to geographical information, and consequently, a trajectory of point sequence could be evolved into a semantic object with geographical interpretation; 2) Investigate the methods for the extraction of Stop/Move objects and the computation of spatio-tempral trajectory-feature associations, and explore the methods for building the spatio-temporally associated trajectory database; 3) Conduct trajectory query processing and analysis against the spatio-temporally associated trajectory database from three different aspects, i.e., trajectory->feature, feature->trajectory and trajectory->trajectory,and therefore, trajectory analysis of spatio-temporal topological relationship, spatio-temporal accessing relationship and spatio-temporal correlated relationship will be investigated; 4) Based on the spatio-temporal trajectory-feature associations, study two trajectory-related classical data mining problems, i.e., the computation of trajectory similarity and the mining of frequent accessing sequences. The research of this proposal will enrich the analytical methods in the field of trajectory study from the pointview of geographical association, and will lay a solid technical foundation for building the geographically oriented trajectory applications.