基于核密度和Voronoi算法的点选取模型

为了清晰有效表达不同尺度下的点状应急态势符号,使其能够适应尺度变化,提出了一种基于核密度和Voronoi算法的点选取模型,通过核密度分析、建立Voronoi图的方法对同类点进行选取。实验表明,该模型有效保持了应急态势符号的空间分布特征和属性信息,解决了因比例尺缩小而导致的压盖、重叠等问题;同时降低了大数据量下符号选取的计算难度,提高了选取效率,保证了应急态势图的清晰易读性。

Point Selection Model Based on Kernel Density and Voronoi Algorithm

In order to express the point emergency situation symbols at different scales clearly and effectively,a point selection model based on kernel density and Voronoi algorithm is proposed to make them adapt to scale change.By means of kernel density analysis and Voronoi diagram,the structure of points is selected,the spatial distribution characteristics and information attributes of similar symbols are effectively maintained,and the problems such as capping and overlapping caused by scale reduction are solved.At the same time,it reduces the difficulty in calculating the symbol selection of point emergency situation under large data amount,improves the selection efficiency,and ensures the clarity and readability of emergency situation diagram.