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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.