中文摘要：

为解决空间数据库增量更新过程中空间实体变化类型识别困难、判别方法复杂度高、判别因子冗余度高以及识别过程自动化程度低等问题,提出一种基于实体特征匹配模型的面状实体变化类型检测方法。该方法在新旧版本面状空间数据库增量实体集合基础上,构建实体变化类型评判规则,设计并集成面状要素属性及几何特征算子,对单一面状实体9种变化类型进行检测和提取,最大限度地降低判别算法复杂度和判别因子冗余度,实现面状实体增量信息提取过程中变化类型的判别、提取、入库,以及判别过程与增量实体提取过程的紧密联系和有机耦合。

英文摘要：

In order to solve the problems such as the difficulties of identifying the spatial entities change types,high complexity of discrimination methods,redundancy of discrimination factors,low automation degree of the identification process,et al,in the process of incremental updating,an automatic detection method for entity change type on the foundation of entity features matching model has been presented.The method builds the discriminant rules for entity change type based on incremental entity sets of old and new versions′area spatial databases,designs and integrates attribute and geometric feature operators of area entities to detect and extract nine change types of single area entity,minimizes complexity of the algorithm and redundancy of detection factors,achieves identification,extraction,storage of change types in the process of incremental information extraction,and achieves close connection,organic coupling with the process of discrimination and increment entities extraction.Experimental results show that the method has good feasibility and applicability,and the method could be well applied to change type discrimination of area entities.