Skip to main content

Table 8 Regression models between UAV-derived biovolume and stem carbon dry weight (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

0.86

< 0.001

135.73

7194.41

Second-order polynomial regression

0.87

< 0.001

129.86

7145.16

Third-order polynomial regression

0.87

< 0.001

130.46

7150.47

Fourth-order polynomial regression

0.87

< 0.001

131.11

7156.05

Logarithmic regression

0.49

< 0.001

262.64

7944.33

Inverse exponential regression

0.64

< 0.001

221.04

7748.45

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