大伦敦建筑几何中的比例和异速生长
Scaling and allometry in the building geometries of Greater London
摘要：
许多城市活动的总体分布，如城市规模揭示了尺度，但几乎没有任何工作存在于单个城市的空间分布的属性，尽管相当多的知识，其分形结构。我们纠正这一点，在这里通过检查在一个世界城市使用数据的几何属性的个别建筑物的缩放关系。我们首先总结了如何使用幂律来近似建筑物的大小分布，在类比城市规模分布已被广泛研究的秩大小和对数正态分布Zipf和Gibrat。然后，我们将这种分析扩展到建筑物之间的异速生长关系，在其不同的几何尺寸属性。我们提出了一些初步的分析，从Emporis数据库，这表明非常强大的缩放世界城市的建筑高度。然后介绍了大伦敦的数据库，从中我们提取了360万建筑物的缩放特性，我们探索。我们研究这些不同属性之间的关键异速生长关系，说明建筑形状如何根据大小变化，我们将这种分析扩展到根据土地利用类型对建筑物进行分类。最后，我们分析了两点关联函数的建筑物的几何形状，支持我们的非空间分析的缩放。
英文摘要：
Many aggregate distributions of urban activities such as city sizes reveal scaling but hardly any work exists on the properties of spatial distributions within individual cities, notwithstanding considerable knowledge about their fractal structure. We redress this here by examining scaling relationships in a world city using data on the geometric properties of individual buildings. We first summarise how power laws can be used to approximate the size distributions of buildings, in analogy to city-size distributions which have been widely studied as rank-size and lognormal distributions following Zipf and Gibrat. We then extend this analysis to allometric relationships between buildings in terms of their different geometric size properties. We present some preliminary analysis of building heights from the Emporis database which suggests very strong scaling in world cities. The data base for Greater London is then introduced from which we extract 3.6 million buildings whose scaling properties we explore. We examine key allometric relationships between these different properties illustrating how building shape changes according to size, and we extend this analysis to the classification of buildings according to land use types. We conclude with an analysis of two-point correlation functions of building geometries which supports our non-spatial analysis of scaling.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
