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A comparison of neighbourhood relations based on ordinary Delaunay diagrams and area Delaunay diagrams: an application to define the neighbourhood relations of buildings

机译:基于普通Delaunay图和区域Delaunay图的邻里关系的比较:用于定义建筑物邻居关系的应用程序

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The aim of this article is to describe a convenient but robust method for defining neighbourhood relations among buildings based on ordinary Delaunay diagrams (ODDs) and area Delaunay diagrams (ADDs). ODDs and ADDs are defined as a set of edges connecting the generators of adjacent ordinary Voronoi cells (points representing centroids of building polygons) and a set of edges connecting two centroids of building polygons, which are the generators of adjacent area Voronoi cells, respectively. Although ADDs are more robust than ODDs, computation time of ODDs is shorter than that of ADDs (the order of their computation time complexity isO(nlogn)). If ODDs can approximate ADDs with a certain degree of accuracy, the former can be used as an alternative. Therefore, we computed the ratio of the number of ADD edges to that of ODD edges overlapping ADDs at building and regional scales. The results indicate that: (1) for approximately 60% of all buildings, ODDs can exactly overlap ADDs with extra ODD edges; (2) at a regional scale, ODDs can overlap approximately 90% of ADDs with 10% extra ODD edges; and (3) focusing on judging errors, although ADDs are more accurate than ODDs, the difference is only approximately 1%.
机译:本文的目的是描述基于普通Delaunay图(odds)和区域Delaunay图(Adds)的建筑物中建筑物之间的邻居关系的方便但坚固的方法。赔率和增加被定义为连接相邻普通Voronoi细胞的发电机的一组边缘(表示构建多边形的质心的点)和连接两个建筑多边形的两个质心的边缘,它们分别是相邻区域Voronoi细胞的发电机。虽然添加比赔率更强,但计算时间比添加的计算时间短(其计算时间复杂度ISO(NLogn)的顺序)。如果赔率可以近似以一定程度的准确度增加,则前者可以用作替代方案。因此,我们计算了在构建和区域尺度的奇数边缘的添加边的数量与奇数边缘的比率。结果表明:(1)占所有建筑物的约60%,赔率可以完全重叠增加额外的奇数边缘; (2)在区域规模,赔率可以重叠大约90%的增加10%额外的奇数边缘; (3)专注于判断误差,尽管增加比赔率更准确,但差异仅为约1%。

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