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Table 4 Multiple regression models for the stand characteristics described in this study

From: Use of LiDAR to estimate stand characteristics for thinning operations in young Douglas-fir plantations

Dependant Model coefficients Model statistics
Variable Model term Estimate RMSE Partial R2 Overall R2
Mean top height Intercept 2.381    
  H 75 1.151 1.02 m 0.85*** 0.85
Green crown height Intercept 0.789    
  H 01 0.0125 0.497 m 0.71***  
  H 01 2 0.108 0.462 m 0.76***  
  Elev skewness -0.680 0.427 m 0.03*** 0.79
Volume Intercept -1.442    
  H 10 9.017 22.1 m3 ha-1 0.83***  
  H 10 2 2.215 21.8 m3 ha-1 0.01*  
  PCzero -0.7102 20.9 m3 ha-1 0.01**  
  Age 2.994 20.2 m3 ha-1 0.01** 0.86
Mean Intercept 76.09    
Diameter at breast height H 95 8.465 18.9 mm 0.74***  
  stand density -0.02407 17.2 mm 0.04***  
  Age 3.189 15.8 mm 0.03***  
  PCzero -0.9579 13.9 mm 0.05*** 0.86
Basal area Intercept -9.353    
  H 10 3.683 4.87 m2 ha-1 0.72***  
  PCzero -0.1117 4.32 m2 ha-1 0.06***  
  Stand density 4.975 x 10-3 4.12 m2 ha-1 0.02***  
  Age 0.9880 3.81 m2 ha-1 0.03*** 0.84
Stand density Intercept 2986    
  Elev IQ -314.9 430 stems ha-1 0.33***  
  PCzero -22.94 371 stems ha-1 0.17***  
  Age -64.26 355 stems ha-1 0.05*** 0.55
  1. Shown are the estimated coefficients for each term included in the six models. Model statistics shown include the root mean square error (RMSE), partial R2 and significance category for each variable included in the model, with asterisks ***, **, * denoting significance at P = 0.001, P = 0.01 and 0.05 respectively. Also shown is the overall model R2.