Formula for calculating spatial similarity degrees between point clouds on multi-scale maps taking map scale change as the only independent variable
Formula for calculating spatial similarity degrees between point clouds on multi-scale maps taking map scale change as the only independent variable
复制标题
以地图比例变化为唯一自变量的多比例尺地图上点云空间相似度计算公式
DOI：
10.1016/j.geog.2015.03.002
复制
发表时间：
2015
影响因子：
2.4
通讯作者：
Jonathan Li
中科院分区：
文献类型：
--
作者：
Weifang Yang;Haowen Yan;Jonathan Li
空间相似度在地图综合中起着重要的作用，但目前尚无定量研究。为了填补这一空白，本研究首先定义了多比例尺地图空间中的地图比例尺变化和空间相似度/关系，然后提出了一个计算一个比例尺点云与另一个比例尺广义点云空间相似度的模型。经过验证，新模型以地图比例尺变化为坐标，以空间相似度为坐标，以16个点为特征。最后，通过曲线拟合的应用，模型得到了以地图比例尺变化为唯一自变量计算空间相似度的经验公式，反之亦然。该公式可用于自动化点特征泛化算法，并确定在泛化过程中何时终止这些算法。
The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its generalized counterpart at another scale. After validation, the new model features 16 points with map scale change as thexcoordinate and the degree of spatial similarity as theycoordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.