Urban Spaces

 

The Scales and Structures of Intra-Urban Spaces

 


 

M
Methods

Cities are often purported to be scale-free. City sizes, for example, are apparently universally logarithmically
distributed, and are thus exponentially more likely to be small than big. Such properties are referred to as
“scale-free” because there is no “average” size or scale. In contrast, the interiors of urban spaces very
generally have intrinsic scales and common
structures. How scale-free behaviour can emerge through processes acting over intrinsically defined scales
remains a generally open question.

B
Background

The urban spaces project aims to understand the origins and properties of intrinsic scales in both one and two
dimensions. One dimensional scales are examined in terms of distance decay functions, both in fundamental
theoretical terms and through empirical analyses of several major world cities. Two dimensional scales are
examined in terms of processes leading to the agglomeration or fragmentation of “neighbourhoods” delineated by
spatial discontinuities.

R
Results

In order to implement comparative analyses of some of the world’s largest cities, initial phases of this project
have focussed on methodological development, including high-performance software. This software will be applied
to a highly detailed, global-scale analysis of distance decay functions. Extending from a firm theoretical
basis, this will provide a uniquely rich and detailed consideration of the origins, forms, and empirical
properties of distance decay functions. The project’s second phase will furnish similarly detailed analyses of
spatial discontinuities, extending from theoretical models for their origins, and ultimately providing a
similarly detailed global-scale empirical analysis.

 


Key Publications
Mark Padgham, Robin Lovelace, Maëlle Salmon, and Bob Rudis (2017).
osmdata
. Journal of Open Source Software 2(14): 305. DOI: 10.21105/joss.00305

Mark Padgham, Richard Ellison (2017). bikedata. Journal of Open Source Software
(forthcoming).

Mark Padgham (2017).
Data from Public Bicycle Hire Systems
. rOpenSci blog (invited contribution), October 17.

Team
Bernd Resch (project lead)
Mark Padgham