顾及功能语义特征的建筑物空间分布模式识别方法

A method for recognizing building clusters by considering functional features of buildings

本文从空间-语义双重约束角度,提出一种顾及空间邻近和功能语义相似的建筑物空间分布模式识别方法。首先,基于建筑物的空间位置邻近性(即建筑物间的最小距离)约束进行聚类,获得建筑物的空间分布模式和建筑物间的空间邻近关系;然后,根据建筑物的功能语义相似性约束进行分割,获得建筑物的初步聚类结果;最后,考虑簇内相似性与簇间差异性进行整体优化,获得最终聚类结果。试验验证表明,本文方法比现有方法能够更有效地识别空间邻近与功能语义一致的建筑物群,服务于智慧城市建设中对建筑物进行语义层次综合和对城市结构进行深入研究的需求。

From the perspective of space-semantic dual constraints,a method for building spatial distribution pattern recognition considering spatial proximity and functional similarity is proposed.Firstly,under the space-semantic divide and conquer strategy,buildings are clustering based on the spatial proximity of the building(i.e.the minimum distance between buildings),and the spatial distribution pattern of the building and the spatial proximity between the buildings are constructed.Then,the clusters are divided into partition according to the functional semantic similarity constraint of the building,the preliminary clustering results of the building are obtained.Finally,the overall clustering results are optimized based on intra-cluster similarity and inter-cluster differences.The experimental results show that the proposed method is able to recognize the building groups with spatial proximity and functional semantics similarity by comparison of the existing methods,and the recognition result is more in line with the need for semantic level generalization of buildings and research on urban structure in smart city applications.