一种面向道路要素更新的几何位置一致性处理方法

A Method of the Consistency Processing in Geometric Position for Road Features Updating

多源空间数据在生产和更新的过程中,由于不同的生产标准、不同的生产与更新方式和空间数据误差等因素的影响,常常会造成同名实体的几何位置差异。本文以影像与矢量数据中道路要素的几何位置差异处理为例,在识别矢量数据控制点的基础上,利用归一化相关系数匹配识别影像中的道路交叉口,并将其作为控制点;分别在影像和矢量数据中建立Delaunay三角网,基于同名点三角剖分的几何位置变换来实现两种数据中道路要素的几何位置一致性处理。

During the production and updating of multi-sources data, different production standards, different process of production and updating, different spatial data error can lead to differences of geometric position for name disambiguation inevitably. For the road features in spatial data, the normalized correlation coefficient was used for image recognition, and road intersections was matched in the image with the priori knowledges of vector, so two sets of road intersections were taken as control points, then it constructs Delauny triangle to realize the consistency processing of geometric position for the image and vector data.