Joel Dearden

Phase transitions and path dependence in urban evolution

There is a long history of recognising and interpreting discontinuous change—phase transitions—in urban systems. In this paper, we use the aggregate retail model as an archetype to explore some new ideas. For example, we argue that the dependence of paths of development on initial conditions has been understudied, and we offer a new graphical analysis that demonstrates explicitly their influence on discrete change. We introduce an order parameter, and we plot this on a ‘results grid’ to facilitate the discovery of possible phase transitions. We illustrate the use of these new developments with an application to London. We show how retail developers can change the ‘initial conditions’ at a point in time and possibly bring about phase transitions by their actions. This also shows that it should be possible to account for the history of urban development as a sequence of initial conditions, illustrating path dependence. Secondly, the model could be deployed in relation to a new shopping zone, and the tools developed here used to calculate the minimum size of a new development in order for it to compete. We explore the ‘minimum size’ idea in relation to a new shopping zone in London.

Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection

In this paper we introduce Order of Magnitude Markers (OOMMs) as a new technique for number representation. The motivation for this work is that many data sets require the depiction and comparison of numbers that have varying orders of magnitude. Existing techniques for representation use bar charts, plots and colour on linear or logarithmic scales. These all suffer from related problems. There is a limit to the dynamic range available for plotting numbers, and so the required dynamic range of the plot can exceed that of the depiction method. When that occurs, resolving, comparing and relating values across the display becomes problematical or even impossible for the user. With this in mind, we present an empirical study in which we compare logarithmic, linear, scale-stack bars and our new markers for 11 different stimuli grouped into 4 different tasks across all 8 marker types.

Explorations in urban and regional dynamics : a case study in complexity science

This book presents mathematical and computer models of urban and regional dynamics and shows how advances in computer visualisation provide new insights.

The Relationship of Dynamic Entropy Maximising and Agent-Based Approaches in Urban Modelling

Entropy maximising models are well established within the field of urban modelling as a method for predicting flows of people or material within an urban system. The dynamic urban retail model (Harris and Wilson, Environ Plan A 10:371–388, 1978) is one of the most well known applications of this technique and is an example of a BLV (Boltzmann-Lotka-Volterra) model. We define an agent-based model (ABM) of urban retail and explore whether it can be made equivalent to a BLV model. Application of both models to the metropolitan county of South Yorkshire in the UK indicates that both models produce similar outputs. This direct comparison provides some insights into the differences and similarities of each approach, as well as highlighting the relative strengths and weaknesses. The ABM has the potential to be easier to disaggregate, while the entropy maximising model is more computationally efficient.

Using Participatory Computer Simulation to Explore the Process of Urban Evolution

When planners intervene in urban systems they seek in part to generate a positive response from those parts of a city outside of their control, namely the private market and private individuals. This response is difficult to predict due to the fact that the city is a nonlinear system of organized complexity. Models of cities which seek to explain this response are necessarily complicated and dynamic. Where an analytical solution is not possible we turn to computer simulation and interactive visualization in order to understand their output. Allowing human participation in such simulations provides a sandbox in which to experiment with the dynamic behaviour of an urban model and play a part in its evolution. Two possible options for structuring this participation are: (1) toy retail systems, which allow unconstrained experimentation, and (2) games, which impose rules and involve role-play and competition. To explore these ideas we construct a toy retail system and a two-player retail game, both of which are derived from an existing agent-based retail model. We explore the application of these systems to the metropolitan county of South Yorkshire in the UK.

Tracking the Evolution of the Populations of a System of Cities

The exploration of the evolution of systems of cities has a long history – illustrated by Berry’s (1964) classic paper. In this chapter we take a simple model that is usually used for modelling the evolution of retail centres within a city and re-interpret it as a model of a system of cities. The retail model is outlined initially and its ‘system’ interpretation thereafter. We then explain the idea of urban ‘DNA’ and its evolution. This is followed by a description of the current system of interest – the evolution of Chicago from 1790 to 1870 in the context of the development of the United States in that period with particular reference to railways. Some results are presented that explore the evolution of the populations of cities in this system and some of the many possible avenues for further research are discussed in the concluding section.

DynaMoVis: visualization of dynamic models for urban modeling

In association with Urban modelers, we have created DynaMoVis, a system for the visualization of dynamic models. The prediction of the evolution of urban and ecological systems is difficult because they are complex nonlinear systems that exhibit self-organization, emergence, and path dependence. Without a good understanding of the dynamics, interventions might have unintended side-effects. This study aims to make progress in the understanding of dynamic models in the application areas of urban modeling. Analyzing these simulations is challenging due to the large amount of data generated and the high-dimensional nature of the system. We present a visualization system for exploring the behavior of a simulation from many different points of view. The system contains a number of different modes which allow exploration of the simulation parameter space, the introduction and effect of noise on the simulation and the basins of attraction in the phase space of the simulation. Through the use of this system, it has been possible to develop a deeper understanding of the inter-dependencies in the models, their parameter spaces, and corresponding phase spaces.