A Composite Influence Domain Model for Automatically Selecting Islands in Nautical Charts
A Composite Influence Domain Model for Automatically Selecting Islands in Nautical Charts
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DOI：
10.1080/01490419.2019.1707335
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发表时间：
2020-01
期刊：
影响因子：
1.6
通讯作者：
Lulu Tang;Lihua Zhang;Weiming Xu;Shuaidong Jia;Jian Dong
中科院分区：
文献类型：
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作者：
Lulu Tang;Lihua Zhang;Weiming Xu;Shuaidong Jia;Jian Dong
摘要现有的海图自动选岛方法都是利用Voronoi图。然而，我们将表明，Voronoi图不能准确地表示地图综合中岛屿的密度和分布，这使得难以获得符合要求的选择结果。我们提出了一种新的方法来选择岛屿的影响域的基础上。首先，使用岛屿影响域（IID）模型的空间数据的Voronoi图表示的缺点进行了分析。其次，定义和构建模型，并根据岛屿的属性对岛屿的重要性进行加权。第三，通过选择具有最大IID面积的岛屿并删除IID与预选岛屿重叠较多的岛屿来自动选择若干岛屿。最后，选取了几组不同海域类型的海岛进行试验，确定并分析了所需的选择参数，推导出了参数设置的经验公式。实验结果表明：（1）该方法提高了孤岛选择的质量;（2）该经验公式可用于参数设置，获得可接受的结果。
Abstract Existing methods for automatically selecting islands for nautical charts utilize the Voronoi diagram. However, we will show that the Voronoi diagrams cannot accurately represent the density and distribution of islands in cartographic generalization, which makes it difficult to obtain selection results that meet requirements. We propose a novel method for selecting islands based on influence domains. First, the shortcomings of the Voronoi diagram representation of spatial data are analyzed using an island influence domain (IID) model. Second, the model is defined and constructed, and the importance of an island is weighed according to its attributes. Third, several islands are selected automatically by choosing those with the largest area of IID and deleting those whose IIDs overlapped more with pre-selected islands. Finally, several groups of islands with different types of sea areas are selected for experimentation, and the required selection parameters are determined and analyzed to derive an empirical formula for setting the parameters. The experimental results show that: (1) the proposed method improves the quality of island selection; (2) the empirical formula can be used in parameter setting to obtain acceptable results.