摘要
空间数据匹配是地理空间数据库进行变化探测和数据更新的重要前提,不同尺度的数据匹配是其非常重要的一个部分。对于尺度差异较大的空间数据而言,同名实体在几何、属性和拓扑结构等方面存在较大差异,已有的融合多指标的匹配算法并不适用。在进行数据匹配时,非匹配对象还会对同名实体形成干扰,匹配效果不能满足要求。针对多尺度数据匹配存在的问题和难点,在分析不同Hausdorff距离算法适用性的基础上,提出加权临近边中位数Hausdorff距离算法。利用宿城区不同尺度的道路网数据对所提算法进行验证,结果表明,所提算法能够适应不同尺度的数据匹配,具有较高的匹配准确率。
Spatial data matching is an important premise for the change detection and data update of geospatial database,in which data matching at different scales is a very important part.For spatial data with large scale differences,the same objects have great differences in geometry,attributes,topological structure and so on,the existing multi-indicators fusion matching algorithm is not applicable.When data matching is carried out,the mismatched object will interfere with the same object,and the matching effect cannot meet the requirements.Aiming at the problems and difficulties in multi-scale data matching,a weighted Hausdorff distance algorithm for the median of adjacent edges is proposed based on the analysis of the applicability of different Hausdorff distance algorithms.The proposed algorithm is validated by using road network data at different scales in Sucheng District.The results show that the proposed algorithm can adapt to data matching at different scales and has a high matching accuracy.
作者
秦育罗
郭冰
孙小荣
QIN Yuluo;GUO Bing;SUN Xiaorong(Suqian College,Suqian 223800,China)
出处
《测绘科学技术学报》
北大核心
2020年第3期313-318,共6页
Journal of Geomatics Science and Technology
基金
宿迁市指导性科技计划项目(Z2018102)。
作者简介
秦育罗(1989-),男,江苏宿迁人,讲师,硕士,主要研究方向为空间数据融合。E-mail:19110@sqc.edu.cn。
