Simple Urban simulation atop complicated models: Multi-scale Equation-Free computing of sprawl using geographic automata

Paul M. Torrens, Ioannis Kevrekidis, Roger Ghanem, Yu Zou

Research output: Contribution to journalArticle

6 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)2606-2634
Number of pages29
JournalEntropy
Volume15
Issue number7
DOIs
StatePublished - Jul 2013

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

Keywords

  • Agent-based model
  • Coarse projective integration
  • Complexity
  • Equation-Free
  • Geosimulation
  • High-performance computing
  • Urban simulation

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