My research interests are in dynamic simulation modelling of geographical phenomena. A particular focus of my recent work has been on the shifting residential locations of different socio-economic groups, with Auckland's increasing social and ethnic diversity providing an ideal setting for these interests. More recently I have also become interested in urban ecology.
Technically, I focus on new approaches to simulation models that capture the complexity of how human actors in urban settings perceive their surroundings. For example in many urban simulations, the city is represented as a grid of cells, and change occurs with respect to the characteristics of grid cells and their immediate neighbouring cells in the grid. This is an unsatisfactory way to represent urban systems. In current work, I am developing the idea of neighbourhoods to include more complex basic units (such as city blocks, land parcels, school zones, etc.) and the complicated spatial relationships among them. In time, I hope that simulations using this sort of framework may enable us to understand better the effects on urban change of how neighbourhoods are defined and perceived. A prime example is the role that the changing perception of a neighbourhood has on the process of gentrification.
I have worked in the past with cellular automata models, but have recently become more interested in agent-based models. Agent-based models are particularly appropriate for studying phenomena such as urban property markets, residential segregation by race, ethnicity and class, transportation problems, and health.
All of this work is set within two broader themes:
First, is the potential impact of ideas from 'complexity science' on an interdisciplinary field such as geography. Complexity science focuses attention on many characteristic behaviours of dynamic systems such as self-organization, emergence, path dependence, sensitivity to initial conditions, which had previously been ignored or 'simplified' out of existence in science. Geographers have long recognized these phenomena. I therefore feel that there is room for productive exchanges between geographers of all persuasions (human, physical, qualitative, quantitative) and complexity studies more generally.
Second, and related to the previous theme, is the importance of understanding the role of simulation models in contemporary science. Models play an increasingly important role in understanding the behaviour of the complex interconnected social, ecological and physical environments in which we live. Therefore, it is important that we understand both the limitations and potential of simulation models as decision-making tools
