New Ways of Supporting Decision Making: Linking Qualitative Storylines with Quantitative Modelling

  • Hedwig van Delden
  • Alex Hagen-Zanker
Part of the The GeoJournal Library book series (GEJL, volume 95)

To explore how people will live and work in Europe, what the landscape will look like and what the environmental consequences will be in some 35 years from now, the PRELUDE project (EEA 2007) of the European Environment Agency developed five different land-use scenarios for Europe. The project was carried out according to a Story And Simulation (SAS) approach in which, iteratively, storylines developed in participatory sessions are underpinned by land-use models. Storylines in this context are defined as narratives about future developments in Europe. They provide qualitative information on a broad range of issues in an integrated context.


Heat Wave Cellular Automaton Gated Community Plan Support System High Nature Value 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. EEA (2001) Scenarios as tools for international assessments , Prospects and Scenarios No. 5, European Environment Agency, Copenhagen.Google Scholar
  2. EEA (2007) Land-use scenarios for Europe: Qualitative and quantitative analysis on a European scale (PRELUDE), Technical report No 9/2007, European Environment Agency, Copenhagen.Google Scholar
  3. Engelen, G., White, R. and De Nijs, T. (2003) Environment explorer: spatial support system for the integrated assessment of socio-economic and environmental policies in the Netherlands, Integrated Assessment, 4(2): 97–105.CrossRefGoogle Scholar
  4. Gallopín, G., Hammond, A., Raskin, P. and Swart, R. (1997) Branch Points: Global Scenarios and Human Choice, Pole Star Series Report No. 7, Stockholm Environment Institute, Boston.Google Scholar
  5. Hagen, A. (2003) Fuzzy set approach to assessing similarity of categorical maps, International Journal of Geographical Information Science, 17(3): 235–249.CrossRefGoogle Scholar
  6. Hagen-Zanker, A. (2006) Map comparison methods that simultaneously address overlap and structure, Journal of Geographical Systems, 8(2): 165–185.CrossRefGoogle Scholar
  7. Hagen-Zanker, A., van Loon, J., Maas, A., Straatman, B., de Nijs, T. and Engelen, G. (2005) Measuring performance of land use models: An evaluation framework for the calibration and validation of integrated land use models featuring cellular automata, Paper presented at the 14th European Colloquium on Theoretical and Quantitative Geography, Tomar, Portugal.Google Scholar
  8. Haines-Young, R. and Weber, J.-L. (2006) Land Accounts for Europe 1990–2000. Towards Integrated Land and Ecosystem Accounting, EEA Report No. 11/2006, European Environmental Agency, Copenhagen.
  9. Kok, K., Verburg, P.H. and Veldkamp, A. (2007) Integrated assessment of the land system: the future of land use, Editorial, Land Use Policy, 24: 517–520.CrossRefGoogle Scholar
  10. Kok, K. and Van Delden, H. (2007) Combining two approaches of integrated scenario development to combat desertification in the Guadalentín watershed, Spain, Environment and Planning B, forthcoming.Google Scholar
  11. Straatman, B., White, R. and Engelen, G. (2004) Towards an automatic calibration procedure for constrained cellular automata, Computers, Environment and Urban Systems, 28(1–2): 149–170.CrossRefGoogle Scholar
  12. Van Delden, H., Luja, P. and Engelen, G. (2007) Integration of multi-scale dynamic spatial models of socio-economic and physical processes for river basin management, Environmental Modelling and Software, 22(2): 223–238.CrossRefGoogle Scholar
  13. White, R. and Engelen, G. (1997) Cellular automata as the basis of integrated dynamic regional modelling, Environment and Planning B, 24: 235–246.CrossRefGoogle Scholar
  14. White, R. and Engelen, G. (2003) A calibration procedure for constrained large neighbourhood cellular automata based land use models, Paper presented at the 13th European Colloquium on Theoretical and Quantitative Geography, Lucca, Italy.Google Scholar
  15. White, R., Straatman, B. and Engelen, G. (2004) Planning scenario visualization and assessment: a cellular automata based integrated spatial decision support system, In Goodchild, M.F. and Janelle, D. (eds.) Spatially Integrated Social Science, Oxford University Press, New York, pp. 420–442.Google Scholar

Additional Reading

  1. Shearer, A.W. (2005) Approaching scenario-based studies: three perceptions about the future and considerations for landscape planning, Environment and Planning B, 32: 67–87.CrossRefGoogle Scholar
  2. Steelman, T.A. and Ascher, W. (1997) Public involvement methods in natural resource policy making: advantages, disadvantages and trade-offs, Policy Sciences, 30: 71–90.Google Scholar
  3. Vennix, J.A.M. (1999) Group-model building: tackling messy problems, System Dynamics Review, 15: 379–401.CrossRefGoogle Scholar
  4. Westhoek, H.J., Van Den Berg, M. and Bakkes, J.A. (2006) Scenario development to explore the future of Europe's rural areas, Agriculture, Ecosystems and Environment, 114 : 7–20.CrossRefGoogle Scholar
  5. Xiang, W-.N. and Clarke, K.C. (2003) The use of scenarios in land-use planning, Environment and Planning B, 30: 885–909.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Hedwig van Delden
    • 1
  • Alex Hagen-Zanker
    • 1
  1. 1.Research Institute for Knowledge Systems (RIKS)AL MaastrichtThe Netherlands

Personalised recommendations