The International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beiiing 2008
1404
Table 2: The affine transformation parameters at optimum image-
to-map rectification
Translation:^, dy
-2.7, 16.2 meter
Rotation :6
-1.0 degree
Scaling :s
1.01
Figure 8: The initial registration of tree-to-tree matching and the
histogram of tree overlap. P = 0.437
Figure 9: The optimum registration of tree-to-tree matching and
the histogram of tree overlap. P = 0.509
Figure 10: Rendering the satellite image on the octagonal shapes
of crown.
f
1/ 2 3 4 5 6 7 8 9 10 11 12 13 U 15
Figure 11: Perspective projection of canopy 3D model using
OpenGL.
5 CONCLUSION
In this study, we proposed the method to identify tree crown from
satellite image by image-to-map rectification. The tree-to-tree
matching algorithm was performed using the fitness value of the
location and octagonal shape of both tree crown in satellite image
and field measurement map. We could obtain the optimum reg
istration by affine transformation of highest fitness value without
ground control points.
Furthermore, it became possible to obtain the spectral informa
tion such a normalized difference vegetation index (NDVI) from
multi-spectral satellite data, about individual trees. This method
is useful for forest management and monitoring.
ACKNOWLEDGEMENT
This research was supported in part by Grant-in-Aid for Scientific
Research (C) from Japan Society for the Promotion of Science
(No. 18580259).
REFERENCES
F.A.Gougeon and D.G.Leckie, 2006. The individual tree crown
approach applied to IKONOS images of a coniferous plantation
area. Photogrammetric Engineering & Remote Sensing, vol.72,
no.ll.pp. 1287-1297.
Xiaowei Yu, Juha Hyyppa, Antero Kukko, Matti Maltamo, and
Harri Kaatinen, 2006. Change detection techniques for canopy
height growth measurements using airborne laser scanner data.
Photogrammetric Engineering & Remote Sensing, vol.72, no. 12,
pp. 1339-1348.
M. Kubo. K. Muramoto, 2005. Tree crown detection and classifi
cation using forest imagery by IKONOS. IGARSS Proceedings,
vol.6, pp.4358-4361.
