Scaling and allometry in the building geometries of Greater London.
(CASA Working Paper
Centre for Advanced Spatial Analysis: London, UK.
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 [Human Behavior and the Principle of Least Effort (Addison-Wesley, Cambridge, 1949)] and Gibrat [Les Inegalites Economiques (Librarie du Recueil Sirey, Paris, 1931)]. 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.
|Type:||Working / discussion paper|
|Title:||Scaling and allometry in the building geometries of Greater London|
|Dates:||2007-10-01 - 2007-10-06|
|Open access status:||An open access version is available from UCL Discovery|
|Keywords:||SPATIAL STRUCTURE, POWER LAWS, ZIPFS LAW, NETWORKS, CITIES, NUMBER|
|UCL classification:||UCL > School of BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis|
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