运用自组织映射识别街道网中的网格模式

提出了一种运用自组织映射识别网格模式的方法。首先,计算街道网中网眼的参数,这些参数是质心、面积、矩形度、延展度、是否含有平行边、边数、一阶邻居数和矩形度平均值;然后,将网眼作为自组织映射的向量进行训练,利用U-matrix可视化方法挖掘聚类得出结果。实验结果表明,该方法能有效地从不规则街道网中识别出网格模式。

Recognition of Grid Pattern in Street Network Using Self-organizing Maps

Pattern recognition has been a hot issue in the field of map generalization.Grid pattern can be regarded as consisting of cluster of meshes,which have similar properties in location,size,shape and relationship.We present an approach to the recognition of grid pattern in street network using self-organizing maps.Firstly,eight parameters,i.e.centroid,area,rectangularity,elongation,having parallel side,side number,number of 1st order neighbor,mean rectangularity are selected to describe meshes.Each mesh constitutes a vector in attribute space.These vectors then are used to train a SOM.The neurons of a SOM correspond to a set of meshes with similar properties.U-matrix is used to visualizing the SOM.Grid pattern recognition is based on the clusters identified by the SOM.Two experiments are conducted.The results show the proposed approach is valid in mining the grid pattern in irregular street networks.The limitation and future work are discussed.