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Table 8 Green Hills inventory plots (1979 AC): comparison of methods

From: Application of LiDAR data to maximise the efficiency of inventory plots in softwood plantations

Inferential framework

Number of strata

Design variable

Estimation variables

Regression model

Relative bias

RMSE

PLE

Relative efficiency

Design-

-

-

Expansion

-

0.04

4.4

8.8

1.0

based

2

OV

Expansion

-

0.06

3.8

7.6

1.3

 

3

OV

Expansion

-

0.02

3.9

7.8

1.3

 

4

OV

Expansion

-

0.01

4.0

8.0

1.2

 

6

OV

Expansion

-

0.10

4.1

8.2

1.2

 

2

OV

Regression

Strata + OV

0.05

3.5

7.0

1.6

 

3

OV

Regression

Strata + OV

0.03

3.8

7.6

1.3

 

4

OV

Regression

Strata + OV

−0.01

3.9

7.8

1.3

 

6

OV

Regression

Strata + OV

0.10

4.1

8.2

1.2

 

4

OV + CC

Expansion

-

0.02

3.8

7.6

1.3

 

6

OV + CC

Expansion

-

−0.01

4.1

8.2

1.2

 

4

OV + CC

Regression

Strata + OV

0.03

3.5

7.0

1.6

 

6

OV + CC

Regression

Strata + OV

−0.01

4.0

8.0

1.2

Model-

-

OV

Model

OV

−0.01

3.5

7.0

1.6

based

-

OV + CC

Model

OV + CC

−0.01

3.5

7.0

1.6

  1. OV = the LiDAR metric 'occupied volume'; i.e. the sum of all pixel heights per plot.
  2. CC = the LiDAR metric 'canopy cover'; i.e. the % of pixels above 3 m in height.
  3. Expansion = estimator [4]; regression = estimator [5]; model = predictor [6].