Developer was carried out. Next, training data for each biomass class 
were prepared in reference to the results of visual interpretation, and 
the biomass classes were classified by the maximum-likelihood 
method based on the training data. The results of LPB and BLK are 
shown in Figure 2 and 3, respectively. 
  
  
  
  
  
  
  
  
  
   
    
  
  
  
  
  
* #| | Biomass 
; Classes 
High | 10% 
Med | 24% 
Low | 65% 
Total: 1802 
points 
  
  
  
: = ] z 
Figure 2. Biomass classing results (2007, LPB province) 
  
ol 
Year (Area) | 1993 (ha) 2000(ha) 2007(ha) 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Bio- | H 76,414 58,196 49,541 
mass | M 136,412 142,817 132,875 
class | L 76,820 65,963 71,074 
Total 289,646 266,976 253,490 
  
  
Figure 3. Biomass classing results (1993,2000, and 2007, Khamkeut 
district( BLK)) based on 491 visual interpretation data 
Overall accuracy of matching of biomass classification was 
approximately 6096 in both LPB province and Khamkeut district. 
Targeting Khamkeut district where the accuracy of each biomass class 
was relatively high, biomass classing was implemented on Current 
Forest from two past periods (1993 and 2000) utilizing same method 
that was used in 2007. The results of biomass classing in 2007 were 
referred to as training data for the maximum-likelihood method. Figure 
3 shows the results of Current Forest biomass classing from three 
periods, and statistics of forest covers and biomass changes over time. 
The high biomass area decreased (including transition to the lower 
class) due deforestation and forest degradation. 
The results of the biomass classing were used to evaluate wall-to-wall 
above-ground forest carbon stocks as discussed in Section 4. 
4. ESTIMATION OF FOREST CARBON STOCK 
4.1 Tier Levels for Forest Carbon Stock Estimation 
Tier levels have been defined according to the IPCC tier requirements 
stated in the GOFC-GOLD SOURCE BOOK (COPI7 Version). 
According to the definitions, data availability is an important item to 
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 
   
  
   
   
    
  
  
  
  
     
     
      
   
  
  
   
     
          
   
        
   
   
   
   
    
  
  
  
   
    
   
   
  
   
    
  
  
    
consider when selecting the appropriate tier. In the study, Tier 1 (basic), 
Tier 2 and Tier 3 level estimations of forest carbon stock were carried 
out for test and pilot study areas. However, only results of Tier 2 are 
shown hereafter. 
Tier 2 (intermediate, called Tier 2-1 hereafter) level forest carbon Stock 
estimation was implemented through combining these results with the 
land use/cover maps and forest survey data. This method is adopted as 
the common technique of Tier 2. However, this technique does require 
alot of plot surveys. 
Thus, Tier 2-2 level method was also studied here based on forest 
biomass classes, forest survey, the IPCC recommended forest carbon 
stock model and the forest carbon stock vs. tree height model that 
applies stereo satellite image analysis, and will be discussed hereafter. 
4.2 Forest Survey for Obtaining Basic Data for Forest Carbon 
Stock Estimation 
Forest survey was carried out several times with the aims of analyzing 
the relationship between forest carbon stock and tree height, accuracy 
of tree height measurements based on ALOS/PRISM, the correlation 
between ALOS/AVNIR2 biomass classes and LANDSAT/TM images 
and so on. 
The widely adopted standard forest survey method was used to 
conduct forest survey at the pilot study areas. Squares of 20 m x 20 m 
were adopted as the standard plots, while 30 m x 30 m was used in the 
areas where the mean tree height was higher than 30 m. The forest 
surveys were implemented over seven weeks at a total of 21 locations, 
specifically 10 in LPB province and 11 in Khamkeut district in BLK 
province. Apart from one deciduous broad-leaved tree forest, all the 
tree species that were confirmed locally comprised evergreen 
broad-leaved forest. The upper tree height was 5.2 m minimum and 
48.0 m maximum, DBH was 3 cm minimum and 148 cm maximum, 
and the number of standing trees per hectare range from 450 to 1,600. 
Moreover, elevation of the survey locations ranged from 452 m to 
1,319 m and the slope ranged from 0 to 35 degrees. 
, 
43 Relationship between Forest Carbon Stock and Tree Height 
From the results of the forest survey, the forest carbon stock at each 
survey plot was calculated, and the correlation of this with the actually 
measured mean upper tree heights was sought in order to construct the 
forest carbon stock vs. tree height model. As the allometry equation for 
calculating forest carbon stock, the equations stated in the IPCC 
GPG-LULUCF were used (IPCC, 2010). The equations were assumed 
being applicable to all the tropical tree species with diameter at DBH of 
5-148 cm in tropical lowland area with annual rainfall of 2,000-4,000 
mm. From the diameter at breast height (DBH), first the above-ground 
biomass and then the below-ground biomass (BBD) are calculated, 
and the combined total gives the living biomass stock. Using these 
equations, the forest carbon stock for all the forest survey plots was 
calculated. Then, relationship between the forest carbon stock and 
upper tree height was analyzed as shown in Figure 4. Applying this 
model, it is possible to estimate forest carbon stock from upper tree 
  
4.4.1 
Meas 
data 
prepa 
comp 
ortho 
(PRI 
BLK 
resuli 
point 
resul 
heigl 
them 
EET M 
Figu 
45 
Bioi 
45.