数据更新中要素变化检测与匹配方法

在要素类之间缺乏同名实体关联关系的情况下，通过空间分析自动识别出当前要素的同名实体及它们之间的变化信息。在查询当前要素的候选匹配集时，设计了一种基于自定义空间拓扑关系的空间查询方法，缩小了的空间查询范围并减少了查询次数，提高了空间分析的效率；在确定当前要素的同名实体时，提出了基于权重的空间要素相似性计算模型，基于该模型有效地对复杂空间关系下的要素进行了匹配，提高了匹配的准确性。

Methodology of feature change detection and matching in data updating

In the case of lack of correlation between identical entities in feature classes, the identical entity for the current feature and their change information was automatically identified by spatial analysis. When searching candidate matching collection for the current feature, a spatial query based on self-definition spatial topological relationship was designed, which narrowed the search scope, reduced the query time, and increased spatial analysis efficiency. When confirming the identical entity for the current feature, a weight-based similarity computing model was presented, and this effectively matched features in the circumstances of complex spatial relationships and improved the accuracy of matching.