以城区居民地为例,提出了一种面向跨比例尺新旧地图数据变化发现与更新方法。首先,从产生效应、发生源头、依附上下文关系、更新策略4个方面剖析大比例尺新数据与小比例尺旧数据间的变化;在此基础上,引入叠置运算与数据增强方法构建变化信息提炼与融合模型,形成"叠置分析与变化发现→增量提取→增量融合更新"的技术框架;最后,通过试验数据验证表明了方法的有效性,以及可扩展性强、适于图层级批处理更新等优点。
This study aims to develop a method of change detection and updating for urban building features at smaller-scale maps from updated larger-scale maps.Firstly,an in-deeper and comprehensive analysis of changes between maps at different times and scales was discussed.Then,a technical framework of change extraction and updating was proposed based on the functions of map overlap and data enrichment.Finally,real-life data were used to verify the effectiveness of the proposed method,and results also showed that our method is flexible and suitable for layer-level updates.