Skip to main content

Table 3 Best fitted linear models for each aerial image block

From: Potential of remote sensing-based forest attribute models for harmonising large-scale forest inventories on regional level: a case study in Southwest Germany

 

Block A

Block B

Block C

Metrics selected (p values in parentheses)

meanCHM (0.10902)

npix (0.10902)

meanCHM*npix (0.00188)

meanDTM (1.61e-13)

meanCHM (0.009459)

meanCHM2 (0.0027)

npix (0.000442)

meanCHM*npix (1.26e-5)

meanDTM (5.01e-6)

Volin (< 2e-16)

npix (< 2e-16)

meanDTM (4.93e-9)

Weights

1/meanCHM

1/meanCHM

1/meanCHM

R 2

0.55

0.50

0.57

Standard error (m3/ha)

32.37

39.56

37.88

RMSE%

38.6

42.1

37.9

Number of plots

464

517

765