Table 4 Effect of using mixed-effects models at the large scale: 1) Variability of the random effects, shown as the estimated standard deviation of the random effect (\({\hat{\sigma}}_b\)) and a 95% confidence interval for this estimate in parenthesis. 2) Differences in RMSE between using a mixed-effects model, and an ordinary least squares model, ∆RMSE = RMSE (ordinary least squares model) – RMSE (mixed model). The ∆RMSE is also given as a percentage of the mean field measured value, in parenthesis. More details in section “Quantifying the effect of using mixed-effects models”
Main species | Volume | Lorey’s height | Basal area | Biomass | |
|---|---|---|---|---|---|
Spruce | \({\hat{\sigma}}_b\) | 4.9 (4.3–5.5) | 0.26 (0.22 − 0.34) | 0.52 (0.46–0.58) | 2.9 (2.6–3.2) |
∆RMSE | 2.5 m3∙ha−1 (1.4%) | 0.17 m (1.2%) | 0.26 m2∙ha− 1 (1.1%) | 1.53 t∙ha− 1 (1.3%) | |
Pine | \({\hat{\sigma}}_b\) | 4.2 (3.8–4.8) | 0.37 (0.95–0.45) | 0.50 (0.44–0.57) | 2.21 (1.95–2.51) |
∆RMSE | 1.1 m3∙ha−1 (1.0%) | 0.27 m (2.3%) | 0.05 m2∙ha− 1 (0.3%) | 0.41 t∙ha− 1 (0.6%) | |
Deciduous | \({\hat{\sigma}}_b\) | 4.8 (4.2–5.3) | 0.62 (0.53–0.73) | 0.59 (0.51–0.67) | 3.10 (2.74–3.51) |
∆RMSE | 3.0 m3∙ha−1 (3.9%) | 0.60 m (6.3%) | 0.21 m2∙ha− 1 (1.6%) | 1.57 t∙ha− 1 (2.8%) |