Dynamic Simulation of Land-Use Change Trajectories with the Clue-S Model

Part of the The GeoJournal Library book series (GEJL, volume 90)


The CLUE(Conversion of Land Use and its Effects) model is one of the most widely applied models with approximately 30 applications in different regions of the globe focusing on a wide range of land-use change trajectories including agricultural intensification, deforestation, land abandonment and urbanisation. The model is a tool to better understand the processes that determine changes in the spatial pattern of land use and to explore possible future changes in land use at the regional scale. This chapter describes the functioning of the model and illustrates the potential of the model for scenario-based simulation of land-use change trajectories with two case studies, one which is a rural landscape in the eastern part of the Netherlands and one which is a strongly urbanized watershed surrounding Kuala Lumpur in Malaysia.


Land use modelling competition Achterhoek allocation cellular automata Kuala Lumpur. 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Agarwal, C., Green, G.M., Grove, J.M., Evans, T.P. and Schweik, C.M. (2001) A Review and Assessment of Land Use Change Models. Dynamics of Space, Time, and Human Choice.Center for the Study of Institutions, Population, and Environmental Change, Indiana University and USDA Forest Service, Bloomington and South Burlington.Google Scholar
  2. Alcamo, J., Leemans, R. and Kreileman, E. (1998) Global Change Scenarios of the 21st Century, Results from the IMAGE 2.1 Model, Elsevier, London.Google Scholar
  3. Anselin, L. (2002) Under the hood: issues in the specification and interpretation of spatial regression models, Agricultural Economics, 27: 247–267.CrossRefGoogle Scholar
  4. Bousquet, F. and Le Page, C. (2004) Multi-agent simulations and ecosystem management: a review, Ecological Modelling, 176: 313–332.CrossRefGoogle Scholar
  5. Briassoulis, H. (2000) Analysis of land use change: theoretical and modelling approaches, in Loveridge, S. (ed) The Web Book of Regional Science, at regscweb.htm. West Virginia University, Morgantown.Google Scholar
  6. Castella, J.-C., Boissau, S., Trung, T.N. and Quang, D.D. (2005) Agrarian transition and lowland-upland interactions in mountain areas in northern Vietnam: application of a multi-agent simulation model, Agricultural Systems, 86: 312–332.CrossRefGoogle Scholar
  7. Castella, J.-C., Pheng Kam, S., Dinh Quang, D., Verburg, P.H. and Thai Hoanh, C. (2007) Combining top-down and bottom-up modelling approaches of land use/cover change to support public policies: Application to sustainable management of natural resources in northern Vietnam, Land Use Policy, (in press). doi:10.1016/j.landusepol.2005.09.009Google Scholar
  8. Clarke, K.C. and Gaydos, L.J. (1998) Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore, International Journal of Geographical Information Science, 12: 699–714.CrossRefGoogle Scholar
  9. Costanza, R. (1989) Model goodness of fit: a multiple resolution procedure, Ecological Modelling, 47: 199–215.CrossRefGoogle Scholar
  10. de Koning, G.H.J., Verburg, P.H., Veldkamp, A. and Fresco, L.O. (1999) Multi-scale modelling of land use change dynamics for Ecuador, Agricultural Systems, 61: 77–93.CrossRefGoogle Scholar
  11. Dietzel, C., Herold, M., Hemphill, J.J. and Clarke, K.C. (2005) Spatio-temporal dynamics in California’s Central Valley: empirical links to urban theory, International Journal of Geographical Information Science, 19: 175–195.CrossRefGoogle Scholar
  12. Dietzel, C. and Clarke, K. (2006) The effect of disaggregating land use categories in cellular automata during model calibration and forecasting, Computers, Environment and Urban Systems, 30: 78–101.CrossRefGoogle Scholar
  13. Hilferink, M. and Rietveld, P. (1999) LAND USE SCANNER: An integrated GIS based model for long term projections of land use in urban and rural areas, Journal of Geographical Systems, 1: 155–177.CrossRefGoogle Scholar
  14. Huigen, M.G.A. (2004) First principles of the MameLuke multi-actor modelling framework for land use change, illustrated with a Philippine case study, Journal of Environmental Management, 72: 5–21.CrossRefGoogle Scholar
  15. Klijn, J.A., Vullings, L.A.E., van de Berg, M., van Meijl, H., van Lammeren, R., van Rheenen, T., Eickhout, B., Veldkamp, A., Verburg, P.H. and Westhoek, H. (2005) EURURALIS 1.0: A scenario study on Europe’s Rural Areas to support policy discussion. Background document. Alterra report 1196, Wageningen University and Research Centre/Environmental Assessment Agency (RIVM).Google Scholar
  16. Lambin, E.F. (1997) Modelling and monitoring land-cover change processes in tropical regions, Progress in Physical Geography, 21: 375–393.Google Scholar
  17. Lambin, E.F., Rounsevell, M.D.A. and Geist, H.J. (2000) Are agricultural land-use models able to predict changes in land-use intensity? Agriculture, Ecosystems and Environment, 82: 321–331.CrossRefGoogle Scholar
  18. Moody, A. and Woodcock, C.E. (1994) Scale-dependent errors in the estimation of land-cover proportions: implications for global land-cover data sets, Photogrammetric Engineering & Remote Sensing, 60: 585–594.Google Scholar
  19. Munroe, D.K., Southworth, J. and Tucker, C.M. (2002) The dynamics of land-cover change in western Honduras: exploring spatial and temporal complexity, Agricultural Economics, 27: 355–369.CrossRefGoogle Scholar
  20. Overmars, K.P., Verburg, P.H. and Veldkamp, A. (2007) Comparison of a deductive and an inductive approach to specify land suitability in a spatially explicit land use model, Land Use Policy, (in press). doi:10.1016/j.landusepol.2005.09.008Google Scholar
  21. Parker, D.C., Manson, S.M., Janssen, M.A., Hoffman, M. and Deadman, P. (2003) Multi-agent systems for the simulation of land-use and land-cover change: a review, Annals of the Association of American Geographers, 93: 314–337.CrossRefGoogle Scholar
  22. Pontius, R.G., Cornell, J.D. and Hall, C.A.S. (2001) Modelling the spatial pattern of land-use change with GEOMOD2: application and validation for Costa Rica, Agriculture, Ecosystems and Environment, 85: 191–203.CrossRefGoogle Scholar
  23. Pontius, R.G., Huffaker, D. and Denman, K. (2004) Useful techniques of validation for spatially explicit land-change models, Ecological Modelling, 179: 445–461.CrossRefGoogle Scholar
  24. Pontius, R.G., Boersma, W., Castella, J.-C., Clarke, K., de Nijs, T., Dietzel, C., Duan, Z., Fotsing, E., Goldstein, N., Kok, K., Koomen, E., Lippitt, C.D., McConnell, W., Pijanowski, B., Pithadia, S., Sood, A.M., Sweeney, S., Trung, T.N. and Verburg, P.H. (2007) Comparing the input, output, and validation maps for several models of land change, Annals of Regional Science, (in press).Google Scholar
  25. Pontius, R.G. and Cheuk, M.L. (2006) A generalized cross-tabulation matrix to compare soft-classified maps at multiple resolutions, International Journal of Geographical Information Science, 20: 1–30.CrossRefGoogle Scholar
  26. Schmit, C., Rounsevell, M.D.A. and La Jeunesse, I., (2006). The limitations of spatial land use data in environmental analysis, Environmental Science and Policy, 9(2): 174–188.CrossRefGoogle Scholar
  27. Veldkamp, A. and Fresco, L.O. (1996) CLUE-CR: an integrated multi-scale model to simulate land use change scenarios in Costa Rica, Ecological Modelling, 91: 231–248.CrossRefGoogle Scholar
  28. Veldkamp, A. and Fresco, L.O. (1997) Exploring land use scenarios, an alternative approach based on actual land use, Agricultural Systems, 55: 1–17.CrossRefGoogle Scholar
  29. Verburg, P.H., Veldkamp, A. and Fresco, L.O. (1999) Simulation of changes in the spatial pattern of land use in China, Applied Geography, 19: 211–233.CrossRefGoogle Scholar
  30. Verburg, P.H., Soepboer, W., Limpiada, R., Espaldon, M.V.O., Sharifa, M. and Veldkamp, A. (2002) Land use change modelling at the regional scale: the CLUE-S model, Environmental Management, 30: 391–405.CrossRefGoogle Scholar
  31. Verburg, P.H. and Veldkamp, A. (2004a) Projecting land use transitions at forest fringes in the Philippines at two spatial scales, Landscape Ecology, 19: 77–98.CrossRefGoogle Scholar
  32. Verburg, P.H., Schot, P., Dijst, M. and Veldkamp, A. (2004b) Land use change modelling: current practice and research priorities, Geojournal, 61: 309–324.CrossRefGoogle Scholar
  33. Verburg, P.H., de Nijs, T.C.M., Ritsema van Eck, J., Visser, H. and de Jong, K. (2004c) A method to analyse neighbourhood characteristics of land use patterns, Computers, Environment and Urban Systems, 28: 667–690.CrossRefGoogle Scholar
  34. Verburg, P.H., Ritsema van Eck, J., de Nijs, T., Dijst, M.J. and Schot, P. (2004d) Determinants of land use change patterns in the Netherlands, Environment and Planning B, 31: 125–150.CrossRefGoogle Scholar
  35. Verburg, P.H., Schulp, C.J.E., Witte, N. and Veldkamp, A. (2006) Downscaling of land use change scenarios to assess the dynamics of European landscapes, Agriculture, Ecosystems & Environment, 114(1): 39–56.CrossRefGoogle Scholar
  36. Wassenaar, T., Gerber, P., Verburg., P.H., Ibrahim, M. and Steinfeld, H. (2007) Projecting land-use changes in the neotropics: the geography of pasture expansion into forest, Global Environmental Change, (in press). doi:10.1016/j.gloenvcha.2006.03.007Google Scholar
  37. White, R., Engelen, G. and Uijee, I. (1997) The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics, Environment and Planning B, 24: 323–343.CrossRefGoogle Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  1. 1.Department of Environmental SciencesWageningen UniversityThe Netherlands

Personalised recommendations