Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Shapiro says Twitter-based employment index provides real-time accuracy

Xie says internet censorship in China often reflects local officials' concerns

Cheng finds marriage may not be best career option for women

Highlights

Jeff Morenoff makes Reuters' Highly Cited Researchers list for 2014

Susan Murphy named Distinguished University Professor

Sarah Burgard and former PSC trainee Jennifer Ailshire win ASA award for paper

James Jackson to be appointed to NSF's National Science Board

Next Brown Bag


PSC Brown Bags will return in the fall

Daniel G. Brown photo

Exurbia from the bottom-up: Confronting empirical challenges to characterizing a complex system

Publication Abstract

Brown, Daniel, D.T. Robinson, L. An, J.I. Nassauer, M. Zellner, W. Rand, R. Riolo, S.E. Page, Bobbi Low, and Z.F. Wang. 2008. "Exurbia from the bottom-up: Confronting empirical challenges to characterizing a complex system." Geoforum, 39(2): 805-818.

We describe empirical results from a multi-disciplinary project that support modeling complex processes of land-use and land-cover change in exurban parts of Southeastern Michigan. Based on two different conceptual models, one describing the evolution of urban form as a consequence of residential preferences and the other describing land-cover changes in an exurban township as a consequence of residential preferences, local policies, and a diversity of development types, we describe a variety of empirical data collected to support the mechanisms that we encoded in computational agent-based models. We used multiple methods, including social surveys, remote sensing, and statistical analysis of spatial data, to collect data that could be used to validate the structure of our models, calibrate their specific parameters, and evaluate their output. The data were used to investigate this system in the context of several themes from complexity science, including have (a) macro-level patterns; (b) autonomous decision making entities (i.e., agents); (c) heterogeneity among those entities; (d) social and spatial interactions that operate across multiple scales and (e) nonlinear feedback mechanisms. The results point to the importance of collecting data on agents and their interactions when producing agent-based models, the general validity of our conceptual models, and some changes that we needed to make to these models following data analysis. The calibrated models have been and are being used to evaluate landscape dynamics and the effects of various policy interventions on urban land-cover patterns. (C) 2007 Elsevier Ltd. All rights reserved.

DOI:10.1016/j.geoforum.2007.02.010 (Full Text)

Browse | Search : All Pubs | Next