卢威, 艾廷华. 利用三角剖分骨架图提取简单多边形目标中心点[J]. 武汉大学学报 ( 信息科学版), 2020, 45(3): 337-343. DOI: 10.13203/j.whugis20180236
引用本文: 卢威, 艾廷华. 利用三角剖分骨架图提取简单多边形目标中心点[J]. 武汉大学学报 ( 信息科学版), 2020, 45(3): 337-343. DOI: 10.13203/j.whugis20180236
LU Wei, AI Tinghua. Center Point Extraction of Simple Area Object Using Triangulation Skeleton Graph[J]. Geomatics and Information Science of Wuhan University, 2020, 45(3): 337-343. DOI: 10.13203/j.whugis20180236
Citation: LU Wei, AI Tinghua. Center Point Extraction of Simple Area Object Using Triangulation Skeleton Graph[J]. Geomatics and Information Science of Wuhan University, 2020, 45(3): 337-343. DOI: 10.13203/j.whugis20180236

利用三角剖分骨架图提取简单多边形目标中心点

Center Point Extraction of Simple Area Object Using Triangulation Skeleton Graph

  • 摘要: 在地图学与地理信息科学领域,面状目标中心点的提取涉及空间关系计算、地图注记配置、地图综合等多个领域。几何形心作为面状目标的形状中心是领域内的常用方法,但在实际应用中由于面状目标形状特征的多样性,利用形心计算的中心点常常不能真实地表达区域中心,比如形心处于区域外部。利用面状目标三角剖分骨架图,考虑面状目标的几何特征与区域连接的拓扑特征,结合图论中的中心性度量方法,定义了面状目标的两种不同的中心点:邻近中心点和居间中心点,分析并讨论了所提出方法的相关特殊情形。利用中国448个地、市区域面要素进行认知实验,讨论了所提出的中心点计算方法的实用性和适用性。实验结果表明,所提出的两种中心点位置可以保证在多边形内部,同时也较好地体现了面状目标的拓扑和几何特征,符合形状特征的视觉认知,可以满足不同应用场景下中心点计算的需求。

     

    Abstract: In the area of cartography and geographic information science, the center points of area features are related to many fields. The centroid is a conventional choice for center point of area feature. However, it is not suitable for features with a complex shape for the center point may be outside the area or not fit the visual center so well. We propose a novel method to calculate the center point of area feature based on triangulation skeleton graph. We define two kinds of centrality of vertices in skeleton graph according to the centrality theory in graph and network analysis. Through the measurement of vertices centrality, the center points of polygon area features are defined as the vertices with maximum centrality. The complexity and special cases are discussed. A cognitive experiment is designed to test the usability of our method based on 448 districts and cities area features. The experimental result shows that the method is more suitable for complex area features than conventional centroid.

     

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