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

PSC In The News

RSS Feed icon

Lam says tightening global labor market good for American workers

Johnston says e-cigs may reverse two-decades of progress on smoking reduction

Mueller-Smith finds incarceration increases the likelihood of committing more, and more serious, crimes

Highlights

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

David Lam is new director of Institute for Social Research

Elizabeth Bruch wins Robert Merton Prize for paper in analytic sociology

Elizabeth Bruch wins ASA award for paper in mathematical sociology

Next Brown Bag

PSC Brown Bags will be back fall 2015


Comparison of empirical methods for building agent-based models in land use science

Publication Abstract

Robinson, D.T., Daniel Brown, D.C. Parker, P. Schreinemachers, M.A. Janssen, M. Huigen, H. Wittmer, N. Gotts, P. Promburom, E. Irwin, T. Berger, F. Gatzweiler, and C. Barnaud. 2007. "Comparison of empirical methods for building agent-based models in land use science." Journal of Land Use Science, 2:31-55.

The use of agent-based models (ABMs) for investigating land-use science questions has been increasing dramatically over the last decade. Modelers have moved from ‘proofs of existence’ toy models to case-specific, multi-scaled, multi-actor, and data-intensive models of land-use and land-cover change. An international workshop, titled ‘Multi-Agent Modeling and Collaborative Planning—Method2Method Workshop’, was held in Bonn in 2005 in order to bring together researchers using different data collection approaches to informing agent-based models. Participants identified a typology of five approaches to empirically inform ABMs for land use science: sample surveys, participant observation, field and laboratory experiments, companion modeling, and GIS and remotely sensed data. This paper reviews these five approaches to informing ABMs, provides a corresponding case study describing the model usage of these approaches, the types of data each approach produces, the types of questions those data can answer, and an evaluation of the strengths and weaknesses of those data for use in an ABM.

DOI:10.1080/17474230701201349 (Full Text)

Browse | Search : All Pubs | Next