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Map comparison methods for comprehensive assessment of geosimulation models ,[object Object],[object Object],[object Object],[object Object]
Assessing GeoSimulation models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],source: www.geosimulation.com
Cellular Automata land use model Time Loop Transition Rule Change cells to land-use for which they have the highest transition potential until Regional demands are met. & Stochastic perturbation Zoning & & Accessibility Transition-potential = & Suitability Land use & Interaction weights Land use at time T+1
Geographical scale ,[object Object],[object Object],[object Object],Local Global Focal Agreement 1 st  map pair 2 nd  map pair Geographical   scale Distinct Identical 1 st  map pair Moving window / kernel 2 nd  map pair
Structure & Presence ,[object Object],[object Object]
Comparison framework ,[object Object],[object Object],[object Object],[object Object],Cluster size distribution Moving Window Patch size - Structure - Moving Window Euclidean Kappa Presence Global Focal Local
Local presence: Kappa ,[object Object],[object Object],[object Object],Kappa = 0.38 2500 104 251 150 1995 Σ 75 19 0 8 48 233 0 96 18 119 165 11 1 92 61 2027 74 154 32 1767 Σ
Focal presence: Euclidean distance Mean  Euclidean Distance
Focal structure: Patch size Map Patch size Moving window Difference Root Mean Squared Error
Global structure: Cluster size distribution ,[object Object]
Reference level for the results ,[object Object],[object Object],[object Object],Before After Generated reference map +29 +18 -15 -32
Results: Local presence (Kappa) + - 0.90 0.91 0.91 0.92 Nature 0.81 0.73 0.77 0.77 Business 0.86 0.83 0.85 0.87 Residential 0.91 0.88 0.89 0.91 Agricultural 0.89 0.87 0.88 0.90 Overall Reference Model Reference Model Validation ’96-’00 Calibration ’89-’96
Results: Focal presence & structure Calibration period 1989-1996 Validation period 1996-2000 Presence Euclidean Structure Patch size + + - - +
Results: Global – Cluster size distribution Calibration ’89 - ’96 Validation ’96 - ’00 Long term  2000 - 2030 ,[object Object],[object Object],[object Object],+ + +
Results: Validation overview ,[object Object],[object Object],[object Object],++ -- - + Cluster size distribution Moving Window Patch size - Structure - Moving Window Euclidean Kappa Presence Global Focal Local
Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thanks for your attention  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Hagen Zanker Iccsa2008

  • 1.
  • 2.
  • 3. Cellular Automata land use model Time Loop Transition Rule Change cells to land-use for which they have the highest transition potential until Regional demands are met. & Stochastic perturbation Zoning & & Accessibility Transition-potential = & Suitability Land use & Interaction weights Land use at time T+1
  • 4.
  • 5.
  • 6.
  • 7.
  • 8. Focal presence: Euclidean distance Mean Euclidean Distance
  • 9. Focal structure: Patch size Map Patch size Moving window Difference Root Mean Squared Error
  • 10.
  • 11.
  • 12. Results: Local presence (Kappa) + - 0.90 0.91 0.91 0.92 Nature 0.81 0.73 0.77 0.77 Business 0.86 0.83 0.85 0.87 Residential 0.91 0.88 0.89 0.91 Agricultural 0.89 0.87 0.88 0.90 Overall Reference Model Reference Model Validation ’96-’00 Calibration ’89-’96
  • 13. Results: Focal presence & structure Calibration period 1989-1996 Validation period 1996-2000 Presence Euclidean Structure Patch size + + - - +
  • 14.
  • 15.
  • 16.
  • 17.