1X-B8, 2012 
: study, Tier 1 (basic), 
n stock were carried 
results of Tier 2 are 
1 forest carbon stock 
these results with the 
method is adopted as 
chnique does require 
lere based on forest 
ended forest carbon 
e height model that 
liscussed hereafter, 
for Forest Carbon 
1e aims of analyzing 
ree height, accuracy 
[SM, the correlation 
NDSAT/TM images, 
ethod was used to 
ires of 20 mx 20m 
0 m was used in the 
n 30 m. The forest 
total of 21 locations, 
ceut district in BLK 
d tree forest, all the 
mprised evergreen 
2 m minimum and 
148 cm maximum, 
from 450 to 1,600. 
ed from 452 m to 
and Tree Height 
arbon stock at each 
is with the actually 
rder to construct the 
ometry equation for 
tated in the IPCC 
tions were assumed 
diameter at DBH of 
fall of 2,000-4,000 
t the above-ground 
3D) are calculated, 
stock. Using these 
st survey plots was 
carbon stock and 
re 4. Applying this 
ck from upper tree 
  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
height obtained from satellite images, aerial photos, etc. 
  
ENT 
R?= 0.922 
    
  
  
  
'=0.0959 TH 
?2092 
  
  
  
  
  
  
  
0 5 10 15 20 25 30 35 40 
Tree Height (m) 
  
  
Figure 4. Relationship between forest carbon stock and upper tree 
height obtained from forest survey data 
44 Tree Height Measurement based on ALOS/PRISM Images 
4.4.1 Stereo Photogrammetry for PRISM Tree Height 
Measurement: A total of 74 ALOS/PRISM scenes with RPC model 
data covering LPB province and Khamkuet district (BLK) were 
prepared for making the measurements of tree height and forest 
compartments, preparation of basic map for forest GIS, and to produce 
orthophoto maps, etc. using a gidital stereo plotter. Average tree heights 
(PRISM tree height) of small areas of Current Forest at the 4 km and 2 
km grid intersection points (as discussed in Section 3.1.4) for LPB and 
BLK provinces, respectively, were obtained by operators. As the 
results, 1042 points of 4 km grid points and 529 points of 2 km grid 
points were measured for the PRISM tree heights. Figure 5 shows the 
results of PRISM tree heights. In LPB province, the most frequent tree 
height level was 15 - 20 m, whereas in Khamkeut district (BLK) 
the most frequent level was 30 - 35 m. 
    
    
   
   
   
   
   
     
[Tree height(m)] 
+ 485-500 
& 50:-:0m 
* 160r 1500 
150: - 2000 
200: - 2500 
2501 - 3000 
300: - 3500 
3801 - 4000 
400: - 4500 
p kk 
Trae height (m) 
Figure 5. PRISM tree heights (LPB province and Khamkuet district) 
45 Wall-to-wall Forest Carbon Stock Estimation using Forest 
Biomass Classes 
45.1 Mean Tree Heights of Each Biomass Class: In view of high 
correlation between biomass and tree heights, the results of biomass 
classing based on ALOS/AVNIR2 and PRISM tree height 
measurements were aggregated in order to seek the mean tree height 
according to each biomass class (Figure 6). The mean values of 
PRISM tree height and the biomass class indicate a positive 
relationship. 
  
o 
£t 
o 
o 
= 
o 
High. 26.8 
M 
£n 
o 
Medium, 24.1 
M 
o 
o 
Low, 184 | 
PRISM Measured Tree Height (m) 
28 
eo 
  
10.0 
AVNIR2 Interpreted Biomass Class 
  
  
Figure 6 PRISM measured tree height and biomass class 
4.5.2 Estimation of Mean Forest Carbon Stock from the Biomass 
Class: Finally, the mean forest carbon stock for each biomass class 
was configured upon applying the mean tree heights of biomass class 
to the model shown in Figure 4 and Table 3. 
  
  
  
  
  
  
  
Biomass PRISM Measurement 
Class Mean tree height | Corresponding forest | Measured 
(m) carbon stock (Tc/ha) | points 
High 26.8 404.4 138 
Medium 24.1 306.6 286 
Low 18.4 1553 588 
Mean 212 |» y 1012 
  
  
  
  
  
Table 3. Biomass classes and forest carbon stocks 
4.5.3 Preparation of Wall-to-wall Forest Carbon Stock Estimation 
Map: Through applying the biomass class vs. forest carbon stock 
model, forest carbon stock estimation maps of Khamkuet district 
(BLK) were prepared as shown in Figure 7. On visually comparing the 
maps, it can be seen that the area of high forest carbon stock around the 
border with Vietnam in the north-east declined between 1993, 2000, 
and 2007. The rate of decline in forest carbon stock from 1993 to 2007 
(152%) is higher than that of the forest area (12.5%) indicating the 
possible forest degradation of the area. It is also shown that the forest 
carbon stock estimated from the biomass classing and upper tree height 
and IPCC's allometry equation based on DBH of forest survey are 
comparable. This may indicate that the forest survey data are sampled 
reasonably well in distribution of the forest carbon stock. It also shows 
that the forest carbon stock estimated from the biomass classing and 
upper tree height has a certain advantage if the forest survey data have 
some bias due to for example accessibility, etc. 
  
   
Figure 7. Forest carbon stock estimation map of Khamkuet district 
(BLK) based on biomass classification