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Table 4 R-squared (R2), root mean square error (RMSE), normalized root mean square error (NRMSE), mean absolute error (MAE), and the equation describing the relation

From: Comparing leaf area index estimates in a Mediterranean forest using field measurements, Landsat 8, and Sentinel-2 data

VI

R2

RMSE

NRMSE (%)

MAE

Equation

S-2 LAI

0.49

0.94

15.80

0.79

y = 1.917 + 1.005x

S-2 NDVI

0.49

0.94

15.75

0.78

y = − 2.034 + 8.474x

S-2 NBR

0.52

0.90

15.15

0.70

y = 0.448 + 6.895x

S-2 NDWI

0.50

0.92

15.48

0.72

y = 0.940 + 6.260x

S-2 SR56

0.49

0.94

15.77

0.77

y = 7.714 − 8.861x

S-2 SR57

0.49

0.93

15.65

0.78

y = 7.174 − 9.176x

S-2 SR67

0.34

1.07

18.01

0.89

y = 19.110 − 18.440x

L8 NDVI

0.55

0.88

14.74

0.70

y = 1.564 + 8.281x

L8 NBR

0.53

0.90

15.15

0.70

y = − 2.157 + 9.945x

L8 NDWI

0.52

0.91

15.15

0.72

y = 2.219 − 8.492x

  1. In the latter, y is the estimated LAI, and x is the considered VI