Quantifying and Analysing Neighbourhood Characteristics Supporting Urban Land-Use Modelling

  • Henning Sten Hansen
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Land-use modelling and spatial scenarios have gained increased attention as a means to meet the challenge of reducing uncertainty in the spatial planning and decision-making. Several organisations have developed software for land-use modelling. Many of the recent modelling efforts incorporate cellular automata (CA) to accomplish spatially explicit land-use change modelling. Spatial interaction between neighbour land-uses is an important component in urban cellular automata. Nevertheless, this component is calibrated through trial-and-error estimation. The aim of the current research project has been to quantify and analyse land-use neighbourhood characteristics and impart useful information for cell based land-use modelling. The results of our research is a major step forward, because we have estimated rules for neighbourhood interaction from really observed land-use changes at a yearly basis. This higher temporal granularity gives a more realistic foundation for estimating neighbourhood interaction rules to be applied in for example land-use cellular automata.

Keywords

cellular automata land use modelling spatial patterns spatial planning 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Barredo J.I., Kasanko, M., McCormick, N. and Lavalle, C. Modelling dynamic spatial processes: Simulation of urban future scenarios through cellular automata. Landscape and Urban Planning, vol. 64, pp. 145-160. (2003)CrossRefGoogle Scholar
  2. Batty, M.: Urban evolution on the desktop: simulation with the use of extended cellular automata. Environment and Planning A, vol. 30, pp. 1943-1967, (1998)CrossRefGoogle Scholar
  3. Christaller, W.: Central Places of Southern Germany (Edition 1966). Prentice Hall, London, (1933)Google Scholar
  4. Daugbjerg, P. and Hansen, K.V. Property Data. The Danish National Survey and Cadastre. Copenhagen, 2000. (in Danish) (2000)Google Scholar
  5. Engelen, G., White, R. and Uljee, I. (2002). The MURBANDY and MOLAND models for Dublin. Final report, RIKS, 2002.Google Scholar
  6. Hagoort, M., Geertman & Ottens, H. Spatial externalities, neighbourhood rules and CA land-use modelling. Annals of Regional Science. Special Issue. (2008)Google Scholar
  7. Hansen, H.S.: An Adaptive Land-use Simulation Model for Integrated Coastal Zone Planning, Lecture Notes in Geoinformation and Cartography, The European Information Society, pp. 35 – 53. (2007a)Google Scholar
  8. Hansen, H. S.: LUCIA – a tool for land use change impact analysis. In (Eds. Bjørke, J.T. & Tveite, H) Proceedings ScanGIS’2007. The 11 th Scandinavian Research Conference on Geographical Information Science. 5 - 7 September 2007, Ås, Norway. pp. 157 – 168. (2007b)Google Scholar
  9. Kok, K. and A. Veldkamp. “Evaluating impact of spatial scales on land use pattern analysis in Central America.” Agriculture, Ecosystems and Environment, vol.85, pp. 205-221. (2001)CrossRefGoogle Scholar
  10. Krugman, P.: The role of geography in development. International Regional Science Review vol. 22, pp. 142-161, (1999)CrossRefGoogle Scholar
  11. Mandelbrot, B.B.: The fractal geometry of nature. New York, NY: W.H. Freeman and Company, (1983).Google Scholar
  12. O’Sullivan, D. & Torrens, P.M.: Cellular models of urban systems. CASA Working Paper 22. University College London, Centre for Advanced Spatial Analysis. (2000)Google Scholar
  13. Shannon, C., & Weaver, W.: The mathematical theory of communication. Urbana: Univ. Illinois Press, (1964).Google Scholar
  14. Straatman, B., White, R. & Engelen, G: Towards an Automatic Calibration Procedure for Constrained Cellular Automata, Computers, Environment and Urban Systems, vol. 28, pp.149-170, (2004)CrossRefGoogle Scholar
  15. Torrens P.M. How cellular models of urban systems work: 1. Theory. Centre for Advanced Spatial Analysis, University College London, Paper 28, (2000)Google Scholar
  16. Veldkamp, A. and Lambin, E.F. Predicting land-use change. Editorial. Agriculture Ecosystems and Environment, vol. 85, pp. 1 – 6. (2001)CrossRefGoogle Scholar
  17. Verburg PH, de Nijs TCM, van Ritsema Eck J, Visser H, de Jong K.: A method to analyse neighbourhood characteristics of land use patterns. Computers Environment Urban Systems, vol. 28, pp. 667–690, (2004)CrossRefGoogle Scholar
  18. Verburg, P.H., Soepboer, W., Veldkamp, A., Limpiada, R., Espaldon, V. and Mastura, S. Modelling the spatial dynamics of regional land use: The CLUE-S model. Environmental Management, vol. 30, pp. 391 – 405. (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Henning Sten Hansen
    • 1
  1. 1.Department of Development and Planning National Environmental Research InstituteAalborg UniversityDK-9200 Aalborg East

Personalised recommendations