基于多评价因素的面状要素合并变换算法

Areal Elements Adjusting Algorithm Based on Multi-evaluation Factors

为解决同一地物数据被重复采集而导致的数据二义性问题,综合不同来源数据的点位精度差异的影响,提出一种基于多评价因素的面状要素合并变换算法.首先分析确定影响合并变换的三大主要评价因素,通过熵法决定其重要性,并将其综合来确定要素的可信度;然后根据离散Fréchet距离识别同名面状要素上的同名点对,进而使用位置加权平均来获得合并变换后的位置.结合海陆图的部分面状要素对该算法进行检验的结果表明,其提高了面状要素的空间位置合并变换质量.

To solve data ambiguity caused by repeatedly collecting the same elements, and synthesize the influence of elements precision on different source maps, an areal element adjusting algorithm based on multi-evaluation factors is proposed. First, three primary evaluation factors are analyzed, with the importance given by the entropy method. The element reliability is obtained by integrating the three factors. Then the same point pairs of same areal elements could be identified with Frechet distance, and the adjusted position is obtained by a weighted average algorithm. The areal elements from a sea chart and a topographic map are utilized shows that the method can he nicely used to improve to test the proposed algorithm, and the result the quality of areal element adjustment.