多源地理空间矢量数据关联模型设计

多源地理空间矢量数据之间存在着隐含的关联关系，这些关联关系往往隐式存在，难以直观展示，也难以与空间数据映射交互展示，更无法进行查询分析，获取所需信息。针对这种情况，本文以多源地理空间矢量数据及统计数据为研究对象，首先定义了多源地理空间矢量数据关联的概念及分类，然后以此为基础设计了多源地理空间矢量数据关联模型，并将其分为3个子模型：基于自适应四叉树编码的空间关联子模型、基于几何匹配的空间关联子模型及基于语义匹配的空间关联子模型。该模型定义了多源地理空间矢量数据之间的关联方式，为关联关系的构建奠定了理论基础。

Designing association model for multi-source geospatial vector data

Implicit relevance is existed between multi-source geospatial vector data. However, the association relation often exists hidden, which is difficult to visualize directly as well as interactive presentation with spatial data, let alone query and analysis to obtain the required information. In view of this situation, multi-source geospatial vector data and statistical data is taken as research object. Firstly, the concept and classification of multi-source geospatial vector data association are defined. And then based on this, the multi-source geospatial vector data association model is designed, which can be divided into 3 sub-models:spatial association sub-model based on adaptive quadtree coding, spatial association sub-model based on geometric matching and spatial association sub-model based on semantic matching. The proposal of this model defines the association method between multi-source geospatial vector data, and lays theoretical foundation for the construction of association relations.