Residential area selection method from the perspective of complex network

doi:10.11947/j.AGCS.2023.20220267

Abstract

Abstract: Multi-feature collaborative generalization is an important development direction of cartographic generalization. Aiming at the problem that the current residential area selection methods don't fully utilize the geographical correlation between the road network and residential areas, we integrate residential areas and road network as a whole, and propose the residential area selection method from the perspective of complex network. First, the measurement information, attribute information and topology information are integrated to construct a weighted residential area network with residential areas as nodes and traffic accessibility as edges. Then, the attraction ability and traffic flow control ability of the target residential area in the local network are evaluated, and the comprehensive importance is obtained by weighted summation. Finally, the residential areas are iteratively selected by Delaunay triangulation with distance constraints. The experiments indicate that the method can take into account the density characteristics of residential areas and network characteristics, and better maintain the geographical correlation between the road network and residential areas.

Key words: residential area selection, complex network, road network, collaborative generalization, geographical correlation

CLC Number:

P283

Lü Zheng, SUN Qun, MA Jingzhen, WEN Bowei. Residential area selection method from the perspective of complex network[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(5): 852-862.

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