测绘学报 ›› 2015, Vol. 44 ›› Issue (4): 453-461.doi: 10.11947/j.AGCS.2015.20130787

• 地图学与地理信息 • 上一篇    下一篇

道路网层次骨架控制的道路选取方法

何海威1, 钱海忠1, 刘海龙2, 王骁1, 胡慧明1   

  1. 1. 信息工程大学地理空间信息学院, 河南 郑州 450000;
    2. 95851部队, 江苏 南京 210046
  • 收稿日期:2013-12-23 修回日期:2014-07-07 出版日期:2015-04-20 发布日期:2015-04-27
  • 通讯作者: 钱海忠E-mail:qianhaizhong2005@163.com E-mail:qianhaizhong2005@163.com
  • 作者简介:何海威(1991—),男,硕士生,研究方向为自动制图综合、应急制图等.E-mail:adai928@126.com
  • 基金资助:

    国家自然科学基金(41171305; 41171354)

Road Network Selection Based on Road Hierarchical Structure Control

HE Haiwei1, QIAN Haizhong1, LIU Hailong2, WANG Xiao1, HU Huiming1   

  1. 1. Institute of Geospatial Information, Information Engineering University, Zhengzhou 450000, China;
    2. 95851 Troops, Nanjing 210046, China
  • Received:2013-12-23 Revised:2014-07-07 Online:2015-04-20 Published:2015-04-27
  • Supported by:

    The National Natural Science Foundation of China (Nos.41171305;41171354)

摘要:

提出了基于路网层次骨架控制的道路自动选取方法.首先,该方法以stroke为单位,利用中介中心性值对stroke进行层次结构划分;其次,采用结构特征识别完善道路层次骨架;第三,基于层次骨架间的连通关系建立逐层传递的stroke重要性计算模型;最后,通过该计算模型自上而下的逐层计算,得到stroke重要性,并据此完成道路网选取.采用3种典型道路网数据,对本方法与其他主要常规stroke选取方法进行对比,试验结果表明本方法不但对语义的依赖性极低,同时消除了中介中心性在评价道路重要性时对边缘道路的不利影响,在保持道路网整体结构和层次性上有较为明显的优势,可适用于各种形态的道路网选取.

关键词: 制图综合, 道路选取, 道路层次, stroke, 中介中心性

Abstract:

A new road network selection method based on hierarchical structure is studied. Firstly, road network is built as strokes which are then classified into hierarchical collections according to the criteria of betweenness centrality value (BC value). Secondly, the hierarchical structure of the strokes is enhanced using structural characteristic identification technique. Thirdly, the importance calculation model was established according to the relationships among the hierarchical structure of the strokes. Finally, the importance values of strokes are got supported with the model's hierarchical calculation, and with which the road network is selected. Tests are done to verify the advantage of this method by comparing it with other common stroke-oriented methods using three kinds of typical road network data. Comparision of the results show that this method had few need to semantic data, and could eliminate the negative influence of edge strokes caused by the criteria of BC value well. So, it is better to maintain the global hierarchical structure of road network, and suitable to meet with the selection of various kinds of road network at the same time.

Key words: map generalization, road selection, road hierarchical structure, road stroke, betweenness centrality

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