4, 9-77 Nov. 1999
py surfaces from the top of
n cited as a key physical
nguishing them from the
mature stands (Spies and
d stand structure attributes
ngth of the relationships
omparison to other remote
favorably with allometric
aspects of individual tree
terplots indicates that the
iomass and LAI show no
remely large values (1200
quation predicting biomass
the total filled volume, and
han 55 m. The equation
correlation with the total
volume, and a negative
ne. This may be interpreted
surface area of leaves is
distributed in. Increases in
y surface tends to increase
^ 40 — 40
& SE
= =
E E
= % = 20
International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 3W14, La Jolla, CA, 9-11 Nov. 1999
LAI, and the presence of empty spaces within the canopy tends
to decrease LAI. Although both LAI and aboveground biomass
use the total filled volume variable in their equations,
scatterplots and regressions have shown that the predicted
values of each variable are no more highly correlated with each
other than the original data.
Young Stand (~20 years) Mature Stand (~100 years)
60 60
B
0 Volume 100% 0
Volume 100%
Old- growth Stand
(-250 years) Open Gap: Volume between
the upper canopy surface
and the height of the tallest
waveform.
60 |
| Euphotic Zone: Foliage or
A woody structure returned in
& the uppermost 65% of
> canopy closure.
=
en
£20
=== Oligophotic Zone:Foliage or
p
woody structure below the
Euphotic Zone
Closed Gap: No foliage or
woody structure detected
9 Volume 10077
Fig. 5. ^ Canopy Volume Profiles (Lefsky et al., 1999b)
v 140€ a! Lond. 14 did ee td uud i 1
2 "4 RR=909 o | R2=88% -
= 120d R2=90% E 6 ;
m Z- zw V. E
>= 800 o Fu s L
25 Dogs . t
2 8 600 Eo e
O &b 400] o [ Z -
> 200 s: R48 4 . -
= os bos od -
-20€ T 0 TDI
0.2 4 6 8 1012 14
Predicted LAI (m2/m2)
rrr
-200 200 600 1000 1400
Predicted Aboveground
Biomass (Mg/ha)
Fig. 6. Predictions of Stand Structure from Canopy Volume
Method
6. CONCLUSION
The development of forest ecology applications of lidar remote
sensing will depend on detailed knowledge of canopy
organization, and the interaction of lidar sensors with that
organization. Using data from the SLICER device, we have
made several introductory studies of the interaction of the
sensor with two very different canopy types, and developed
algorithms that relate lidar measurements to standard field
measurements of forest canopies. Additionally, we have shown
the utility of these measurements for the estimation of forest
stand structure attributes, such as aboveground biomass and
LAI, in both forest types.
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