摘要
数字地图合并是通过同名实体匹配和合并变换技术,调整相关地物实体的几何、属性等差异,实现同一地区不同来源地图数据的集成和融合。其中同名实体匹配是极为重要的第一步,也是一个存在大量不确定性的过程,匹配阈值的选取、实体非一对一的匹配关系是匹配中的关键难题,匹配效果不佳或出现错误匹配直接影响着后续合并结果的正确性。本文提出一种基于概率理论的匹配模型,该模型融合多种匹配指标,通过计算实体匹配概率大小来确定匹配实体。该方法避免了匹配指标精确阈值的选取,并且能够有效地解决匹配中非一对一的情况。
The conflation of geographic datasets is one of the key technologies in the front research area of spatial data capture and integration in Geographic Information Systems （GIS）. Map conflation is a complex process of matching and merging map data. Because various reasons relate to map data discrepancies, a great amount of uncertainties exist during the process. In the first step, selecting appropriate thresholds and handling one-many or many-many matching relationships are two difficulties in feature matching, which predetermines following map merging step. This paper proposed a probabilistic method for feature matching, which fuses a variety of criteria to calculate the matching probability. The feature pair with the highest probability can be determined to be matched. This method avoids selecting thresholds and attempts to resolve one-many and many-many matching relationship.
出处
《测绘学报》
EI
CSCD
北大核心
2007年第2期210-217,共8页
Acta Geodaetica et Cartographica Sinica
基金
国家自然科学基金项目(40301043)
上海市青年科技启明星计划项目(05QMX1456)
地理空间信息工程国家测绘局重点实验室经费项目(200618)
关键词
数字地图合并
概率理论
匹配
多指标融合
map conflation
probabilistic theory
feature matching
multi-indicators iusion
