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

Entropy

Paul M. Torrens²  Ioannis Kevrekidis³  Roger Ghanem¹ 

[1] Department of Aerospace and Mechanical Engineering and Department of Civil and Environmental Engineering, University of Southern California; Los Angeles, CA, 90089, USA; E-Mail:;Department of Geographical Sciences and Institute for Advanced Computer Studies, University of Maryland, College Park; College Park, MD 20742, USA;Department of Chemical and Biological Engineering and Program in Applied and Computational Mathematics, Princeton University; Princeton, NJ 08544, USA; E-Mail:

关键词: urban simulation;    geosimulation;    agent-based model;    high-performance computing;    Equation-Free;    coarse projective integration;    complexity;   

DOI  :  10.3390/e15072606

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.