Acta Geodaetica et Cartographica Sinica ›› 2020, Vol. 49 ›› Issue (5): 622-631.doi: 10.11947/j.AGCS.2020.20190222

• Cartography and Geoinformation • Previous Articles     Next Articles

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

LIU Huimin, HU Wenke, TANG Jianbo, SHI Yan, DENG Min   

  1. Department of Geo-informatics, Central South University, Changsha 410083, China
  • Received:2019-06-04 Revised:2019-11-07 Published:2020-05-23
  • Supported by:
    The National Natural Science Foundation of China (Nos. 41771492;41901406);The Natural Science Foundation of Hunan Province(No. 2018JJ3639);The National Key Research and Development Program of China(No. 2017YFB0503600)

Abstract: 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.

Key words: building clustering, spatial distribution pattern, functional and semantic features, minimum spanning tree, map generalization

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