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

PSC In The News

RSS Feed icon

Thompson says America must "unchoose" policies that have led to mass incarceration

Axinn says new data on campus rape will "allow students to see for themselves the full extent of this problem"

Frey says white population is growing in Detroit and other large cities


Susan Murphy to speak at U-M kickoff for data science initiative, Oct 6, Rackham

Andrew Goodman-Bacon, former trainee, wins 2015 Nevins Prize for best dissertation in economic history

Deirdre Bloome wins ASA award for work on racial inequality and intergenerational transmission

Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

Next Brown Bag

Monday, Oct 5 at noon, 6050 ISR
Colter Mitchell: Biological consequences of poverty

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