提出并实现了一种针对近似平行沟渠群的典型化方法。首先,建立沟渠的方位关系图,通过生成关系图中各连通分量的极大完全子图,提取近似平行的沟渠;然后,依据视觉认知规律定义沟渠间的认知距离,并基于最小生成树的剪枝对沟渠进行分组;接着,运用K-means++算法对分组后的沟渠进行重新表达;最后,通过比较综合前后沟渠群的外轮廓相似性以及沟渠分布密度的差异,对典型化结果进行了评价。对广州市数据进行了实验,结果表明该方法能有效进行近似平行的沟渠群的典型化。
This paper proposes and implements a new method for typification of ditches with almost parallel pattern.In this method,azimuth relation graph of ditches is established first,by generating the maximum complete subgraph of the connected components in which ditches having almost parallel pattern are extracted then.Next,cognition distance between ditches is defined according to the laws of visual cognition and then ditches are grouped based on the edge-cutting of the minimal spanning tree of ditches.Afterwards,ditches in each group are re-represented based on K-means++algorithm.Finally,typification result is evaluated through comparing the similarity between the contour of ditches and the variation of ditch density before and after typification.Experiment using data of Guangzhou city validates that the proposed method can implement the typification of ditches effectively.