The International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
1402 
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 
Figure 1: The illustration of test area. The grid of 10 meter mesh 
is constructed using piles labeled alphabet and numeric charac 
ters. There are two flux towers to measure the exchanges of car 
bon dioxide between forest and atmosphere. The field measure 
ment area is 80 meter by 40 meter. 
; IKONOS satellite image ; • 
Field measured data 
\ 
Image segmentation 
! j The projected on-ground map j 
IPSS? 
Qï^rôëÆPO 
' Tree-to-tree matching 
Figure 3: The illustration of image-to-map rectification. 
Initial registration 
The range of 
affine transformation parameter' 
The maximum fitness value 
Optimum registration 
Figure 2: The IKONOS panchromatic image of the study area. 
This area is 180 meter by 150 meter. (C)Japan Space Imaging 
Co. 
whose radius is more 2 or 3 meter. The image was acquired on 
25 August 2003. Figure 2 shows the IKONOS image of the study 
area. The size of image is 180 meter by 150 meter. 
3 METHODS 
Figure 3 shows the illustration of image-to-map rectification. First, 
using the field measured data, we create the projected on-ground 
map which has the location and shape of canopy trees. Next, we 
detect the region of tree crown from satellite image. Then, we 
perform roughly registration of the satellite image and the pro 
jected on-ground map. This is initial registration. Finally, per 
forming tree-to-tree matching algorithm(Xiaowei et al., 2006), 
we obtain the optimum registration and identify individual tree 
crowns. 
3.1 The Projected On-Ground Map 
The projected on-ground map is a figure that represents the lo 
cation of canopy tree and the shape. The shape of tree crown in 
Figure 4: Flow diagram of tree-to-tree matching. 
this study is octagonal. We obtained the projected on-ground map 
from the measurement data of 102 canopy trees. 
3.2 Image Segmentation 
The IKONOS panchromatic image was segmented using water 
shed algorithm(Kubo and Muramoto, 2005). Then, the segmented 
regions were classified to discriminate tree crowns using the fea 
ture of spectral signature. 
3.3 Tree-to-Tree Matching 
Using the positional information of the east tower by GPS equip 
ment, we performed roughly registration of the satellite image to 
the on-ground map. This is initial registration. Then, using affine 
transformation, the projected on-ground map is translated, rotated 
and scaled in order to find the optimum registration. In each over 
lap of registration, we performed tree-to-tree matching algorithm 
and calculated fitness value. When the fitness value becomes the 
maximum, we obtain the optimum parameters of affine transfor 
mation for rectifying satellite image to the map coordinate, and 
identify tree crowns. Figure 4 shows the flow diagram of tree-to- 
tree matching.