【摘要】 为解决多源数据合并过程中数据二义性问题,降低已有算法由于未考虑"调整图"上线状要素位置的影响而带来的误差,提出基于多评价因素的线状要素合并变换算法.分析确定影响合并变换的三大主要评价因素,通过熵法衡量各自的重要性,并将其进行综合来确定要素的可信度;根据离散Fréchet距离来识别同名线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.对海陆图的部分线状要素的检验结果表明,该算法提高了线状要素空间位置合并变换的质量.更多还原

【Abstract】 To solve data ambiguity in the process of map conflation and reduce some errors caused by ignoring the influence of linear elements from adjusting map, the linear elements adjusting algorithm based on multi-evaluation factors was developed.Three major evaluation factors were analyzed,and their importance were given by using the method of entropy,and elements reliability was gained by integrating them.Then the same point pairs of same linear elements could be identified with Fréchet distance,and the adjusted position was obtained by using a weighted average algorithm.Tests on some same linear elements from a sea chart and a topographic map show that the proposed algorithm can improve the quality of linear elements adjusting.更多还原