ISPRS Commission III, Vol.34, Part 3A „Photogrammetric Computer Vision“, Graz, 2002
Further investigations have shown that the mean differences in
Table 1 significantly depend on the crown closure of the stands.
The identified correlation is shown in Figure 1 for both test
sites. In cases where the crown closure is below 65 % the laser-
derived tree heights (h) are significantly lower than the top
heights from the forest inventory.
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h max Laser
Figure 1: Top heights vs. laser-derived tree heights in two
crown closure classes.
Hence, the assessment of top heights can be improved by using
both laser-derived tree heights (h) and crown closure (c). The
relationship of the predicted top height (hy), average height (h)
and crown closure (c) can be depicted from the following for-
mulas.
predicted top height = 16.16 + 1.35 * h—29.3 * ¢ ,
(1) Hohentauern test site
predicted top height = 12.366 + 1.619 * h — 31.889 * c,
(2) Ilz test site
predicted top height = 15 + 1.43 * h > 29.5 * c
(3) both test sites together
Table 2 shows the statistics for the fitted top height models and
figure 2 shows the predicted top heights for both test sites using
equation (3).
R Square Std. error of esti-
mation
Hohentauern 0.633 3.9833
Ilz 0.8323 3.0045
both test sites 0.715 3.8018
Table 2: Statistics for the fitted top height models
A - 304
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Top Heights
Figure 2: Predicted top heights vs. top heights for both test sites
using equation (3)
The statistics show that 72 % (R square 0.715) of forest inven-
tory top heights can be predicted by laser-derived mean tree
heights and crown closure using the same model for different
test site conditions concerning tree species mixture and terrain.
4.1.2 Assessment of timber volume using a statistical ap-
proach
The assessment of timber volume was only carried out at the Ilz
test site. The predicted timber volume was calculated as a func-
tion of the predicted top heights derived from equation (2) (hy)
as statistical analyses have shown that this parameter is the best
predictor for timber volume. The regression model based on this
predictor was formed and the obtained model, coefficient of
determination (R square) and standard error (SE) of the model
are shown in Figure 3.
800— E
> predicted timber volume = ,
© -139.386 + 18.9021 * hr
£ 600- :
E R square = 0.72 7
€ SE-75.86 m/ha ° s 8
© 400-— Sun ze
a at 7 D P B D
D en fon
E 200- So noma
© OA o
> =
5 es
r- 0 | | I
= 0 200 400 600 800
predicted timber volume
Figure 3: Timber volume from forest inventory vs. pre-
dicted timber volume — Ilz
