1. Measuring Allocation Errors in Land Change Models in Amazonia Luiz Diniz, Merret Buurman, Pedro Andrade, Gilberto Câmara, Edzer Pebesma Merret Buurman GeoInfo, Campos do Jordão, 25 November 2013

2. Luiz Diniz Merret Buurman Pedro Andrade Gilberto Câmara Edzer Pebesma + Measuring Allocation Errors in Land Change Models in Amazonia

3. & 3 Merret Buurman, 26.11.2013 „Why?“

4. & 4 Merret Buurman, 26.11.2013 Land change modelling Simulation Observed reality 2001200220032004

5. & 5 Merret Buurman, 26.11.2013 Land change modelling Big responsability Need to evaluate results This can only be done afterwards! 2004

6. & 6 Merret Buurman, 26.11.2013 (1) Goodness of fit metric (2) Evaluation of models

7. & 7 Merret Buurman, 26.11.2013 (1) Goodness of fit metric

8. & 8 Merret Buurman, 26.11.2013 Two complementary views… Costanza: Multiple resolutions Pontius et al.: Need to consider persistence Pontius Jr, R.G., E. Shusas, and M. McEachern, Detecting important categorical land changes while accounting for persistence. Agriculture, Ecosystems & Environment, 2004. 101(2): p. 251-268. Costanza, R., Model Goodness of Fit - a Multiple Resolution Procedure. Ecological Modelling, 1989. 47(3-4): p. 199-215.

9. & 9 Merret Buurman, 26.11.2013 Two complementary views… Costanza: Multiple resolutions Pontius et al.: Need to consider persistence Pontius Jr, R.G., E. Shusas, and M. McEachern, Detecting important categorical land changes while accounting for persistence. Agriculture, Ecosystems & Environment, 2004. 101(2): p. 251-268. Costanza, R., Model Goodness of Fit - a Multiple Resolution Procedure. Ecological Modelling, 1989. 47(3-4): p. 199-215.

10. & 10 Merret Buurman, 26.11.2013 Multiple resolutions

11. & 11 Merret Buurman, 26.11.2013 Multiple resolutions

12. & 12 Merret Buurman, 26.11.2013 Multiple resolutions

13. & 13 Merret Buurman, 26.11.2013 Multiple resolutions

14. & 14 Merret Buurman, 26.11.2013 Multiple resolutions

15. & 15 Merret Buurman, 26.11.2013 Multiple resolutions

16. & 16 Merret Buurman, 26.11.2013 Multiple resolutions

17. & 17 Merret Buurman, 26.11.2013 Multiple resolutions

18. & 18 Merret Buurman, 26.11.2013 Two complementary views… Costanza: Multiple resolutions Pontius et al.: Need to consider persistence

19. & 19 Merret Buurman, 26.11.2013 Two complementary views… Costanza: Multiple resolutions Pontius et al.: Need to consider persistence

20. & 20 Merret Buurman, 26.11.2013 Need to consider persistence Many cases: Most of the area does not change Focus: Predicting the changed area Example: 99% of the area unchanged All the change predicted at wrong locations  98 % of the area is „correct“!

21. & 21 Merret Buurman, 26.11.2013 … Combined into one Change-focusing multiple- resolution goodness of fit

22. & 22 Merret Buurman, 26.11.2013 What do we evaluate?

23. & 23 Merret Buurman, 26.11.2013 What do we evaluate?

24. & 24 Merret Buurman, 26.11.2013 What do we evaluate? Equal total amount!

25. & 25 Merret Buurman, 26.11.2013 Goodness of fit metric (1) Inside sampling window: Compute the difference in amount of change between both grids

26. & 26 Merret Buurman, 26.11.2013 Goodness of fit metric (2) Sum this up for all sampling windows

27. & 27 Merret Buurman, 26.11.2013 Goodness of fit metric (3) Divide by twice the total amount of change – Why twice? In the previous steps, every „wrong“ allocation was counted twice, because too much change in one cell automatically means too little change in another, due to the equality of demand in both grids.

28. & 28 Merret Buurman, 26.11.2013 Goodness of fit metric (4) Subtract from one to get goodness … and repeat for all other resolutions

29. & 29 Merret Buurman, 26.11.2013 Goodness of fit metric F w = Goodness of fit at resolution w. t w = Number of sampling windows at resolution w. w= Resolution (a sampling window has w 2 cells). a refi = Percent of change in land cover in cell i in the reference cell space. a modj = Change in land use/land cover in cell j in the model cell space. i, j = Cells inside a sampling window. u = Cells inside the cell space. s = A sampling window. num = Number of cells in the cell space (t w * w 2 )

30. & 30 Merret Buurman, 26.11.2013 (2) Evaluation of models

31. & 31 Merret Buurman, 26.11.2013 Models SimAmazonia 2001  2050 BAU and GOV Soares-Filho, B., et al., Modelling conservation in the Amazon basin. Nature, 2006. 440(7083): p. 520-523.

32. & 32 Merret Buurman, 26.11.2013 Models SimAmazonia 2001  2050 BAU and GOV Soares-Filho, B., et al., Modelling conservation in the Amazon basin. Nature, 2006. 440(7083): p. 520-523. Laurance 2000  2020 Optimistic Non-Opt. Laurance, W., et al., The future of the Brazilian Amazon. Science, 2001. 291: p. 438-439.  Compare with PRODES 2011 (25x25km)

33. & 33 Merret Buurman, 26.11.2013

34. & 34 Merret Buurman, 26.11.2013

35. & 35 Merret Buurman, 26.11.2013 Why so weak? Neighborhood model: captures only existing regions (not new frontiers) Similarity Neighborhood model & SimAmazonia: Same reason?  Compare maps!

36. & 36 Merret Buurman, 26.11.2013

37. & 37 Merret Buurman, 26.11.2013 Why so weak? Neighborhood model: captures only existing regions (not new frontiers) Similarity Neighborhood model & SimAmazonia: Same reason?  Compare maps! Yes! Location of new frontiers difficult to predict

38. & 38 Merret Buurman, 26.11.2013 Why so weak? Laurance Overestimates roads Assumes same impact of roads everywhere Underestimates protected areas

39. & 39 Merret Buurman, 26.11.2013 Indigenous areas (FUNAI) Parque do Xingu

40. & 40 Merret Buurman, 26.11.2013 Conclusion Predicting the locations of future deforestation: More difficult than expected! Problem: Policy recommendation based on those predictions Our hope: Next generation of deforestation models will capture better the complex human decision-making

41. & 41 Merret Buurman, 26.11.2013 Conclusion Predicting the locations of future deforestation: More difficult than expected! Problem: Policy recommendation based on those predictions Our hope: Next generation of deforestation models will capture better the complex human decision-making Obrigada!