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Table 5 Regression models between UAV-derived biovolume and total aboveground biomass (n = 571)

From: Estimation of aboveground biomass and carbon stocks of Quercus ilex L. saplings using UAV-derived RGB imagery

Model

R 2 adjusted

p-value

RMSE

AIC

Lineal

0.88

< 0.001

404.21

8434.10

Second-order polynomial regression

0.89

< 0.001

381.50

8369.42

Third-order polynomial regression

0.89

< 0.001

385.75

8381.99

Fourth-order polynomial regression

0.89

< 0.001

388.87

8391.15

Logarithmic regression

0.52

< 0.001

800.69

9210.61

Inverse exponential regression

0.65

< 0.001

687.17

9036.92

  1. RMSE, root-mean-square error; AIC, Akaike information criterion