基于几何与属性匹配的地理信息数据融合更新方法

A geographic data fusion and update method based on geometric and attribute matching

针对多源地理信息数据在尺度、几何位置和属性等方面存在不一致性而造成难以融合更新这一现状,探讨了一种基于几何与属性匹配技术的地理信息数据融合更新方法。该方法首先通过广义Voronoi图获取候选集,有效地提高候选集的获取效率并减少不相关目标对候选集的影响;接着,基于几何和属性匹配等关键技术实现点、线、面3种不同几何类型数据的匹配分析;最后,基于匹配结果从参考地理信息数据中提取增量数据,并完成目标数据的融合更新。实验结果表明,采用几何与属性匹配的地理信息数据融合更新方法,能够高效识别并提取增量数据,对监测数据更新模式的创新探索有一定的借鉴意义。

The inconsistency of multi-source geographic data in scale,geometric position,and attribute cause difficult data fusion and update.This study proposed a fusion and update method for geographic data based on geometric and attribute matching.First,the candidate set was acquired using the generalized Voronoi diagram,thus effectively improving the acquisition efficiency and reducing the impact of unrelated targets on the candidate set.Then,the matching analysis of point,line,and plane data was made using key techniques such as geometric and attribute matching.Finally,based on the matching results,the incremental data were extracted from the reference geographic information data,followed by fusion and update of target data.The experimental results show that the method proposed in this study can efficiently identify and extract incremental data and serves as a reference for the innovative exploration into the update mode of monitoring data.