无级比例尺GIS是数字地球和Web GIS的核心技术之一，但随着GIS的广泛应用和深入发展，现有的GIS技术已经不能满足信息社会的需要，其中一个需要解决的重要问题就是GIS的空间数据量如何随着比例尺的变化自动增减。针对无级比例尺GIS多边形综合中的选取与合并技术，在对选取的数量规律和质量原则以及合并的原则进行充分论述的基础上，提出了一种多边形图层数据组织策略C-Tree，并给出了基于C-Tree的多边形综合算法。对于给定的大给与大比例尺地图多边形图层数据，该算法可以高效率地完成多边形选取与合并的综合操作，输出小比例尺地图图层数据。该算法现已成功应用于时空一体化智能城建信息系统，并获得了满意的结果。

Scaleless GIS is one of the key technologies of digital earth and web gis. With the development of GIS, the current GIS techniques couldn't meet the requirements of the information society very well. The ability of deriving small scalem ap from large scale map automatically is very important in modern GIS. To derive small scale map from large scale map in scaleless GIS is related to cartographic map generalization technique. Based on the description of the amount rule of selection, quality principle of selection, combination principle and attribute data generalization. A hierarchical organization strategy of polygon map layer, C Tree, and the corresponding algorithm of generalization in scaleless GIS is presented in this paper. The algorithm based on C Tree can complete the polygon selection and combination operation in high efficiency for given large scale polygon map layer and small output scale. This strategy has been implemented into a 863 project of China and the experimental results show that it can complete polygon layer generalization with high efficiency and can maintain the appearance and the topological structure of map well.