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Polygon Aggregation Algorithm Using the Simple Feature Model

机译:简单特征模型的多边形聚合算法

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The aggregation of the topological neighbouring polygons developes well. There are some good algorithms, but the most are based on the topological spatial data model, it requests data build integrated topological relations. When the data is modified, we should vindicate the data's consistency, and it will cost so much time to rebuild the topological relations and even sometimes maybe failed. This paper presents a polygon- aggregation algorithm based on simple data model which have no topological relations. The simple data model doesn't need store topological relation, it can reduce the complicacy of operation. In the paper, it discusses finding the shared edges, evolving end points to nodes, linking continuous segments to arc and marking repeat edges for deletion, building topological relations between the node and edges, aggregating polygon using outlines at last. This method was used in practice, and it has good effect for large data quantity.
机译:拓扑相邻多边形的聚集发展良好。有一些好的算法,但是大多数算法是基于拓扑空间数据模型的,它要求数据建立集成的拓扑关系。修改数据后,我们应证明数据的一致性,这将花费大量时间来重建拓扑关系,甚至有时可能会失败。本文提出了一种基于简单数据模型的无拓扑关系的多边形聚合算法。简单的数据模型不需要存储拓扑关系,可以减少操作的复杂性。在本文中,它讨论了寻找共享边,将端点演变为节点,将连续段链接为弧以及标记重复边以进行删除,在节点和边之间建立拓扑关系,最后使用轮廓聚合多边形的问题。该方法已在实践中使用,对大数据量具有良好的效果。

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