Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/61029
Title: Comparison of empirical methods for building agent-based models in land use science
Authors: Derek T. Robinson
Daniel G. Brown
Dawn C. Parker
Pepijn Schreinemachers
Marco A. Janssen
Marco Huigen
Heidi Wittmer
Nick Gotts
Panomsak Promburom
Elena Irwin
Thomas Berger
Franz Gatzweiler
Cécile Barnaud
Authors: Derek T. Robinson
Daniel G. Brown
Dawn C. Parker
Pepijn Schreinemachers
Marco A. Janssen
Marco Huigen
Heidi Wittmer
Nick Gotts
Panomsak Promburom
Elena Irwin
Thomas Berger
Franz Gatzweiler
Cécile Barnaud
Keywords: Earth and Planetary Sciences;Environmental Science;Social Sciences
Issue Date: 1-Jan-2007
Abstract: 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. © 2007, Taylor & Francis Group, LLC.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84907435668&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/61029
ISSN: 17474248
1747423X
Appears in Collections:CMUL: Journal Articles

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