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Alexandre C. Coutinho Embrapa Monitoramento por Satélite PROCAM - USP BURNINGS OCCURENCY DYNAMCS IN THE STATE OF MATO GROSSO.

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Presentation on theme: "Alexandre C. Coutinho Embrapa Monitoramento por Satélite PROCAM - USP BURNINGS OCCURENCY DYNAMCS IN THE STATE OF MATO GROSSO."— Presentation transcript:

1 Alexandre C. Coutinho Embrapa Monitoramento por Satélite PROCAM - USP BURNINGS OCCURENCY DYNAMCS IN THE STATE OF MATO GROSSO

2 ACCURACY ESTIMATION OF BURNING DATA MUNICIPALITY BASED ANALYSIS MULTIVARIATED ANALYSIS - PRINCIPAL COMPONENTS FIRST COMPONENT CLASSIFICATION DYNAMICS CHARACTERIZATION PROCEDURES

3 ACCURACY ESTIMATION OF BURNING DATA of 47 images spatial resolution - 60m geometrical resolution - 90m (1,5 pixel) 2000 / images spatial resolution - 30m geometrical resolution - 50m

4 burnings confidence level of 95% confifdence interval of 5% 2000 / burnings confidence level of 95% confifdence interval of 5% SAMPLE de de NOAA - 12 ACCURACY ESTIMATION OF BURNING DATA

5 Stratified analysis based on distance Identify geometric correction and commission errors radius 1,5km; 3,0km and 6,0km around the coordinate ACCURACY ESTIMATION OF BURNING DATA

6 1,5km 6,0km 3,0km 6,0km ACCURACY ESTIMATION OF BURNING DATA

7 COMMISION ERROR ? ACCURACY ESTIMATION OF BURNING DATA

8 COMMISION ERROR ?

9 ACCURACY ESTIMATION OF BURNING DATA COMMISSION ERROR ?

10 MUNICIPALITY BASED ANALYSIS

11 MUNICIPALITY BASED ANALYSIS

12 MUNICIPALITY BASED ANALYSIS

13 MUNICIPALITY BASED ANALYSIS

14 MUNICIPALITY BASED ANALYSIS

15 MUNICIPALITY BASED ANALYSIS

16 MUNICIPALITY BASED ANALYSIS

17 MUNICIPALITY BASED ANALYSIS

18 MUNICIPALITY BASED ANALYSIS

19 MULTIVARIATED ANALYSIS - PRINCIPAL COMPONENTS data normalization Factor 1 explains 77,59%

20 Din. progressiva acelerada Inc. de qmd. extremamente alta Din. progressiva moderada Inc. de qmd. alta Din. estável Inc. de qmd. moderada Din. estável Inc. de qmd. baixa Din. Regressiva fraca Inc. de qmd.muito baixa LEGENDA DYNAMICS CHARACTERIZATION


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