Measuring allocation errors in land change models in amazonia
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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. Measuring Allocation Errors in Land Change Models in Amazonia. Luiz Diniz

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Measuring Allocation Errors in Land Change Models in Amazonia

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Measuring allocation errors in land change models in amazonia

Measuring Allocation Errors in Land Change Models in Amazonia

Luiz Diniz, MerretBuurman, Pedro Andrade, Gilberto Câmara, EdzerPebesma

MerretBuurmanGeoInfo, Campos do Jordão, 25 November 2013


Measuring allocation errors in land change models in amazonia

Measuring Allocation Errors in Land Change Models in Amazonia

LuizDiniz

MerretBuurman

Pedro Andrade

Gilberto Câmara

EdzerPebesma

+


Measuring allocation errors in land change models in amazonia

„Why?“


Land change modelling

Land changemodelling

  • Simulation

  • 2001

  • 2002

  • 2003

  • 2004

  • Observed reality


Land change modelling1

Land changemodelling

  • 2004

Bigresponsability

Need toevaluateresults

This canonlybedoneafterwards!


Measuring allocation errors in land change models in amazonia

(1) Goodnessof fit metric

(2) Evaluation ofmodels


Measuring allocation errors in land change models in amazonia

(1) Goodnessof fit metric


Two complementary views

Twocomplementaryviews…

Costanza:Multiple resolutions

Pontius et al.:Need toconsiderpersistence

Costanza, R., Model Goodness of Fit - a Multiple Resolution Procedure.

EcologicalModelling, 1989. 47(3-4): p. 199-215.

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.


Two complementary views1

Twocomplementaryviews…

Costanza:Multiple resolutions

Pontius et al.:Need toconsiderpersistence

Costanza, R., Model Goodness of Fit - a Multiple Resolution Procedure.

EcologicalModelling, 1989. 47(3-4): p. 199-215.

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.


Multiple resolutions

Multiple resolutions


Multiple resolutions1

Multiple resolutions


Multiple resolutions2

Multiple resolutions


Multiple resolutions3

Multiple resolutions


Multiple resolutions4

Multiple resolutions


Multiple resolutions5

Multiple resolutions


Multiple resolutions6

Multiple resolutions


Multiple resolutions7

Multiple resolutions


Two complementary views2

Twocomplementaryviews…

Costanza:Multiple resolutions

Pontius et al.:Need toconsiderpersistence


Two complementary views3

Twocomplementaryviews…

Costanza:Multiple resolutions

Pontius et al.:Need toconsiderpersistence


Need to consider persistence

Need toconsiderpersistence

Manycases: Most oftheareadoes not change

Focus: Predictingthechangedarea

Example:

99% oftheareaunchanged

All thechangepredictedatwronglocations

 98 % oftheareais „correct“!


Combined into one

… Combinedintoone

Change-focusing multiple-resolution goodnessof fit


What do we evaluate

What do weevaluate?


What do we evaluate1

What do weevaluate?


What do we evaluate2

What do weevaluate?

Equaltotal

amount!


Goodness of fit metric

Goodnessof fit metric

  • (1) Inside samplingwindow: Computethedifference in amountofchangebetweenbothgrids


Goodness of fit metric1

Goodnessof fit metric

(2) Sumthisupfor all samplingwindows


Goodness of fit metric2

Goodnessof fit metric

  • (3) Dividebytwicethe total amountofchange

    • Whytwice? In theprevioussteps, every „wrong“ allocation was countedtwice, becausetoomuchchange in onecellautomaticallymeanstoolittlechange in another, due totheequalityofdemand in bothgrids.


Goodness of fit metric3

Goodnessof fit metric

(4) Subtractfromonetogetgoodness

… andrepeatfor all otherresolutions


Goodness of fit metric4

Goodnessof fit metric

Fw= Goodness of fit at resolution w.

tw= Number of sampling windows at resolution w.

w= Resolution (a sampling window has w2cells).

arefi= Percent of change in land cover in cell i in the reference cell space.

amodj= 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 (tw * w2)


Measuring allocation errors in land change models in amazonia

(2) Evaluation ofmodels


Models

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.


Models1

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.

 Comparewith PRODES 2011 (25x25km)


Why so weak

Why so weak?

Neighborhoodmodel: capturesonlyexistingregions (not newfrontiers)

SimilarityNeighborhoodmodel & SimAmazonia: Same reason?  Comparemaps!


Why so weak1

Why so weak?

Neighborhoodmodel: capturesonlyexistingregions (not newfrontiers)

SimilarityNeighborhoodmodel & SimAmazonia: Same reason?  Comparemaps!

Yes! Location ofnewfrontiersdifficulttopredict


Why so weak2

Why so weak?

  • Laurance

    • Overestimatesroads

    • Assumes same impactofroadseverywhere

    • Underestimatesprotectedareas


Measuring allocation errors in land change models in amazonia

Parque

do Xingu

Indigenousareas (FUNAI)


Conclusion

Conclusion

Predictingthelocationsoffuturedeforestation:More difficultthanexpected!

Problem: Policyrecommendationbased on thosepredictions

Ourhope: Next generationofdeforestationmodels will capturebetterthecomplex human decision-making


Conclusion1

Conclusion

Predictingthelocationsoffuturedeforestation:More difficultthanexpected!

Problem: Policyrecommendationbased on thosepredictions

Ourhope: Next generationofdeforestationmodels will capturebetterthecomplex human decision-making

Obrigada!


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