Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

From meta-studies to modeling: Using synthesis knowledge to build broadly applicable process-based land change models

Magliocca, Nicholas R. ; van Vliet, Jasper ; Brown, Calum ; Evans, Tom P. ; Houet, Thomas ; Messerli, Peter ; Messina, Joseph P. ; Nicholas, Kimberly LU orcid ; Ornetsmuller, Christine and Sagebiel, Julian , et al. (2015) In Environmental Modelling & Software 72. p.10-20
Abstract
This paper explores how meta-studies can support the development of process-based land change models (LCMs) that can be applied across locations and scales. We describe a multi-step framework for model development and provide descriptions and examples of how meta-studies can be used in each step. We conclude that meta-studies best support the conceptualization and experimentation phases of the model development cycle, but cannot typically provide full model parameterizations. Moreover, meta-studies are particularly useful for developing agent-based LCMs that can be applied across a wide range of contexts, locations, and/or scales, because meta-studies provide both quantitative and qualitative data needed to derive agent behaviors more... (More)
This paper explores how meta-studies can support the development of process-based land change models (LCMs) that can be applied across locations and scales. We describe a multi-step framework for model development and provide descriptions and examples of how meta-studies can be used in each step. We conclude that meta-studies best support the conceptualization and experimentation phases of the model development cycle, but cannot typically provide full model parameterizations. Moreover, meta-studies are particularly useful for developing agent-based LCMs that can be applied across a wide range of contexts, locations, and/or scales, because meta-studies provide both quantitative and qualitative data needed to derive agent behaviors more readily than from case study or aggregate data sources alone. Recent land change synthesis studies provide sufficient topical breadth and depth to support the development of broadly applicable process-based LCMs, as well as the potential to accelerate the production of generalized knowledge through model-driven synthesis. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Land use change, Model development, Meta-analysis, Synthesis, Model, validation, Agent-based models
in
Environmental Modelling & Software
volume
72
pages
10 - 20
publisher
Elsevier
external identifiers
  • wos:000361906400002
  • scopus:84936888122
ISSN
1364-8152
DOI
10.1016/j.envsoft.2015.06.009
language
English
LU publication?
yes
id
0620edf2-f070-46d6-ad7e-ad1345c9a975 (old id 8221437)
date added to LUP
2016-04-01 11:06:33
date last changed
2022-02-10 08:53:33
@article{0620edf2-f070-46d6-ad7e-ad1345c9a975,
  abstract     = {{This paper explores how meta-studies can support the development of process-based land change models (LCMs) that can be applied across locations and scales. We describe a multi-step framework for model development and provide descriptions and examples of how meta-studies can be used in each step. We conclude that meta-studies best support the conceptualization and experimentation phases of the model development cycle, but cannot typically provide full model parameterizations. Moreover, meta-studies are particularly useful for developing agent-based LCMs that can be applied across a wide range of contexts, locations, and/or scales, because meta-studies provide both quantitative and qualitative data needed to derive agent behaviors more readily than from case study or aggregate data sources alone. Recent land change synthesis studies provide sufficient topical breadth and depth to support the development of broadly applicable process-based LCMs, as well as the potential to accelerate the production of generalized knowledge through model-driven synthesis. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).}},
  author       = {{Magliocca, Nicholas R. and van Vliet, Jasper and Brown, Calum and Evans, Tom P. and Houet, Thomas and Messerli, Peter and Messina, Joseph P. and Nicholas, Kimberly and Ornetsmuller, Christine and Sagebiel, Julian and Schweizer, Vanessa and Verburg, Peter H. and Yu, Qiangyi}},
  issn         = {{1364-8152}},
  keywords     = {{Land use change; Model development; Meta-analysis; Synthesis; Model; validation; Agent-based models}},
  language     = {{eng}},
  pages        = {{10--20}},
  publisher    = {{Elsevier}},
  series       = {{Environmental Modelling & Software}},
  title        = {{From meta-studies to modeling: Using synthesis knowledge to build broadly applicable process-based land change models}},
  url          = {{http://dx.doi.org/10.1016/j.envsoft.2015.06.009}},
  doi          = {{10.1016/j.envsoft.2015.06.009}},
  volume       = {{72}},
  year         = {{2015}},
}