复杂网络视角下的居民地选取方法

doi:10.11947/j.AGCS.2023.20220267

摘要/Abstract

摘要： 多要素协同综合是制图综合重要的发展方向。针对当前居民地选取方法对道路网与居民地间地理关联性利用不够深入的问题,将居民地与道路网融合为整体,本文提出了一种复杂网络视角下的居民地选取方法。首先,整合居民地与道路网的几何信息、属性信息与拓扑信息,构建以居民地为节点、以交通通达关系为边的含权居民地网络;然后,评价目标居民地在局部网络中的居民地吸引能力与交通流控制能力,并加权求和获得综合重要性;最后,利用距离约束Delaunay三角网进行迭代选取。试验表明,本文方法能够兼顾居民地的密度特征与网络特征,选取结果与道路网结构吻合良好,较好地保持了道路网与居民地的地理关联性。

关键词: 居民地选取, 复杂网络, 道路网, 协同综合, 地理关联性

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

中图分类号:

P283

吕峥, 孙群, 马京振, 温伯威. 复杂网络视角下的居民地选取方法[J]. 测绘学报, 2023, 52(5): 852-862.

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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