Skip to main content

Map Comparison Methods for Comprehensive Assessment of Geosimulation Models

  • Conference paper
Computational Science and Its Applications – ICCSA 2008 (ICCSA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5072))

Included in the following conference series:

Abstract

A crucial task in the calibration and validation of geosimulation models is to measure the agreement between model and reality. In recent years many map comparison methods have been developed for this purpose. This paper presents a framework to systematically assess different aspects of model performance and express the results relative to a common reference level. Application on a constrained cellular automata model of the Netherlands demonstrates that the framework gives an in-depth account of model performance. It also shows that any performance assessment that does not follow a multi-criteria approach or lacks a reference level results in an unbalanced account and ultimately false conclusions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Benenson, I., Torrens, P.M.: Geosimulation: object-based modeling of urban phenomena. Comput. Environ. Urban Syst. 28, 1–8 (2004)

    Article  Google Scholar 

  2. Refsgaard, J.C., Henriksen, H.J.: Modelling guidelines: terminology and guiding principles. Adv. Water Resour. 27, 71–82 (2004)

    Article  Google Scholar 

  3. Costanza, R.: Model goodness of fit: a multiple resolution procedure. Ecol. Model 47, 199–215 (1989)

    Article  Google Scholar 

  4. Hagen, A.: Fuzzy set approach to assessing similarity of categorical maps. Int. J. Geog. Inf. Sci. 17, 235–249 (2003)

    Article  Google Scholar 

  5. Hagen-Zanker, A.: Map comparison methods that simultaneously address overlap and structure. J. Geogr. Syst. 8, 165–185 (2006)

    Article  Google Scholar 

  6. Kuhnert, M., Voinov, A., Seppelt, R.: Comparing raster map comparison algorithms for spatial modeling and analysis. Photogramm. Eng. Remote Sens. 71, 975–984 (2005)

    Google Scholar 

  7. Pontius Jr., R.G.: Quantification error versus location error in comparison of categorical maps. Photogramm. Eng. Remote Sens. 66, 1011–1016 (2000)

    Google Scholar 

  8. Power, C., Simms, A., White, R.: Hierarchical fuzzy pattern matching for the regional comparison of land use maps. Int. J. Geog. Inf. Sci. 15, 77–100 (2001)

    Article  Google Scholar 

  9. Remmel, T.K., Csillag, F.: Mutual information spectra for comparing categorical maps. Int. J. Remote Sens. 27, 1425–1452 (2006)

    Article  Google Scholar 

  10. Turner, M.G., Costanza, R., Sklar, F.H.: Methods to evaluate the performance of spatial simulation-models. Ecol. Model. 48, 1–18 (1989)

    Article  Google Scholar 

  11. White, R.: Pattern based map comparisons. J. Geogr. Syst. 8, 145–164 (2006)

    Article  Google Scholar 

  12. Batty, M., Torrens, P.M.: Modelling and prediction in a complex world. Futures 37, 745–766 (2005)

    Article  Google Scholar 

  13. Schelling, T.C.: Dynamic models of segregation. J. Math. Sociol. 1, 143–186 (1971)

    Google Scholar 

  14. Benenson, I., Omer, I., Hatna, E.: Entity-based modeling of urban residential dynamics: the case of Yaffo, Tel Aviv. Environ. Plann. B 29, 491–512 (2002)

    Article  Google Scholar 

  15. White, R., Engelen, G., Uljee, I.: The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics. Environ. Plann. B 24, 323–343 (1997)

    Article  Google Scholar 

  16. Engelen, G., White, R., Uljee, I., Drazan, P.: Using cellular automata for integrated modelling of socio-environmental systems. Environ. Monit. Assess. 34, 203–214 (1995)

    Article  Google Scholar 

  17. White, R., Engelen, G.: High-resolution integrated modelling of the spatial dynamics of urban and regional systems. Comput. Environ. Urban Syst. 24, 383–400 (2000)

    Article  Google Scholar 

  18. Engelen, G., White, R., de Nijs, T.: Environment Explorer: spatial support system for the integrated assessment of socio-economic and environmental policies in the Netherlands. Integr. Assess. 4, 97–105 (2003)

    Article  Google Scholar 

  19. de Nijs, T.C.M., de Niet, R., Crommentuijn, L.: Constructing land-use maps of the Netherlands in 2030. J. Environ. Manage. 72, 35–42 (2004)

    Article  Google Scholar 

  20. Barredo, J.I., Demicheli, L.: Urban sustainability in developing countries’ megacities: modelling and predicting future urban growth in Lagos. Cities 20, 297–310 (2003)

    Article  Google Scholar 

  21. Takeyama, M., Couclelis, H.: Map dynamics: integrating cellular automata and GIS through geo-algebra. Int. J. Geog. Inf. Sci. 11, 73–91 (1997)

    Article  Google Scholar 

  22. Monserud, R.A., Leemans, R.: Comparing global vegetation maps with the Kappa statistic. Ecol. Model. 62, 275–293 (1992)

    Article  Google Scholar 

  23. Batty, M., Longley, P.: Fractal cities: a geometry of form and function. Academic Press Professional, Inc., San Diego (1994)

    MATH  Google Scholar 

  24. Dungan, J.L.: Focusing on feature-based differences in map comparison. J. Geogr. Syst. 8, 131–143 (2006)

    Article  Google Scholar 

  25. Kok, K., Farrow, A., Veldkamp, A., Verburg, P.H.: A method and application of multi-scale validation in spatial land use models. Agricult. Ecosys. Environ. 85, 223–238 (2001)

    Article  Google Scholar 

  26. Pontius Jr., R.G.: Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions. Photogramm. Eng. Remote Sens. 68, 1041–1049 (2002)

    Google Scholar 

  27. McGarigal, K., Cushman, S.A., Neel, M.C., Ene, R.: FRAGSTATS: spatial pattern analysis program for categorical maps. Computer software program produced by the authors at the University of Massachusetts, Amherst (2002), http://www.umass.edu/landeco/research/fragstats/fragstats.html

  28. Foody, G.M.: Status of land cover classification accuracy assessment. Remote Sens. Environ. 80, 185–201 (2002)

    Article  Google Scholar 

  29. Cohen, J.A.: Coefficient of agreement for nominal scales. Educ. Psychol. Meas. 20, 37–46 (1960)

    Article  Google Scholar 

  30. Heidke, P.: Berechnung des Erfolges und der Gute der Windstarkevorhersagen im Sturmwarnungsdienst. Geogr. Ann. 8, 301–349 (1926)

    Article  Google Scholar 

  31. de Keersmaecker, M.L., Frankhauser, P., Thomas, I.: Using fractal dimensions for characterizing intra-urban diversity: the example of Brussels. Geogr. Anal. 35, 310–329 (2003)

    Article  Google Scholar 

  32. Benguigui, L., Blumenfeld-Lieberthal, E., Czamanksi, D.: The dynamics of the Tel Aviv morphology. Environ. Plann. B 33, 269–284 (2006)

    Article  Google Scholar 

  33. Schweitzer, F., Steinbink, J.: Urban cluster growth: analysis and computer simulations of urban aggregations. In: Schweitzer, F. (ed.) Self-organization of complex structures: from individual to collective dynamics, pp. 501–518. Gordon & Breach, London (1997)

    Google Scholar 

  34. Pontius Jr., R.G., Huffaker, D., Denman, K.: Useful techniques of validation for spatially explicit land-change models. Ecol. Model. 179, 445–461 (2004)

    Article  Google Scholar 

  35. Hagen-Zanker, A., Lajoie, G.: Neutral models of landscape change as benchmarks in the assessment of model performance. Landscape Urban Plann (in press, 2008)

    Google Scholar 

  36. van Vliet, J.: Validation of land use change models: a case study on the Environment Explorer. Centre for geo-information, Master’s thesis. Universiteit Wageningen, Wageningen, 65 (2006)

    Google Scholar 

  37. Jantz, C.A., Goetz, S.J.: Analysis of scale dependencies in an urban land-use-change model. Int. J. Geog. Inf. Sci. 19, 217–241 (2005)

    Article  Google Scholar 

  38. Kocabas, V., Dragicevic, S.: Assessing cellular automata model behaviour using a sensitivity analysis approach. Comput. Environ. Urban Syst. 30, 921–953 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Osvaldo Gervasi Beniamino Murgante Antonio Laganà David Taniar Youngsong Mun Marina L. Gavrilova

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hagen-Zanker, A., Martens, P. (2008). Map Comparison Methods for Comprehensive Assessment of Geosimulation Models. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69839-5_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-69839-5_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69838-8

  • Online ISBN: 978-3-540-69839-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics