Simple Urban Simulation Atop Complicated Models: Multi-Scale Equation-Free Computing of Sprawl Using Geographic Automata

Paul Torrens,Roger Ghanem,Yu Zou,Yannis Kevrekidis

doi:10.3390/e15072606

Paul Torrens, Roger Ghanem + Show 2 more

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https://doi.org/10.3390/e15072606

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Abstract

Reconciling competing desires to build urban models that can be simple and complicated is something of a grand challenge for urban simulation. It also prompts difficulties in many urban policy situations, such as urban sprawl, where simple, actionable ideas may need to be considered in the context of the messily complex and complicated urban processes and phenomena that work within cities. In this paper, we present a novel architecture for achieving both simple and complicated realizations of urban sprawl in simulation. Fine-scale simulations of sprawl geography are run using geographic automata to represent the geographical drivers of sprawl in intricate detail and over fine resolutions of space and time. We use Equation-Free computing to deploy population as a coarse observable of sprawl, which can be leveraged to run automata-based models as short-burst experiments within a meta-simulation framework.

Highlights

In modeling cities, there is often a debate about whether simple or complicated representations of urban processes and phenomena are most appropriate for simulation [7,9]
The geographic model is designed to treat space-time drivers of sprawl, as spatial processes. The geography of these processes may have particular meaning in environmental, engineering, policy, sociological, and economic settings, but here we focus on their geographic form, as we regard population and geography as being sufficient indicators of sprawl, as discussed above
A near-standard argument in agent-based modeling is that models should be simple

Summary

Introduction

There is often a debate about whether simple or complicated representations of urban processes and phenomena are most appropriate for simulation [7,9]. Simplified models have long had a place in urban simulation. Some of the most popular, longstanding, and elegant urban models are simple [25]. Considered practically, it is often desirable to reduce model results to a few degrees of control, i.e., outcomes or recommendations that can guide urban planners and managers in their decision-making [26]. The desire for simplicity in urban simulation from earlier traditions seems to have persisted into a recent era of agent-based modeling (ABM). ABM was pioneered as a new approach to urban modeling because of its ability to support detailed and massively interactive simulation [7]

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