bul 2004 
(12) 
(13) 
(14) 
(15) 
2K 
ated from 
n of the 
hows the 
e surface 
hows the 
ature. We 
nospheric 
erature of 
(d, vapor 
from the 
was used 
ata used. 
  
  
ecem ber 
ib 
384 
636 
  
  
  
  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
  
    
  
  
  
o 
& e 
4 
> ^ 
/ E 
6 125 25 5 75 124 5 
d Lirrrzbrirarzlrrragjigngg] 5 AU Lu 
Figure 12. Spatial distribution of evapotranspiration 
Next, we summed up precipitation each grid on the down slope 
angle for the estimate of discharge. We carried out the 
regression analysis between the estimated discharge and the 
actual observed discharge. These are applied for spatial 
distribution of flow in the watershed. Figure 13 shows estimated 
discharge. 
  
Figure 13. Added precipitation to down slope 
Groundwater infiltration was calculated using precipitation, 
evapotranspiration, and, discharge and equation (9). The figure 
14 shows calculated groundwater infiltration. The ground water 
infiltration was mostly effected from precipitation, because the 
discharge made by precipitation. 
855 
Figure 14. Spatial distribution of infiltration rate 
4. DISCUSSION 
In estimating forest volume, the correlation coefficients between 
land cover ratio in mixed pixels and estimated tree height was 
very high. Thus, forest volume might be estimated in higher 
accuracy. 
The forest volume was almost independent from vegetation 
types, but forest volume was affected by the distribution of the 
vegetation types each watershed. At present, mixed forest of 
confusions trees and broad-leave trees seems to have the most 
material volume. 
Vegetation types are also affected by the temperature and the 
precipitation. Moreover, the precipitation is affected by the 
forest and its evapotranspiration. 
5. CONCLUSION 
The mixed pixel decomposition method for remote sensing data 
could estimate forest volumes precisely. We obtained a spatial 
distribution of hydrological data in the forest using remote 
sensing, GIS, and meteorological data. The forest volume was 
mainly influenced by forest types. 
ACKNOWLEDGEMENTS 
This study used the ASTER data provided by ASTER 
announcement of research opportunity (ARO). The forest 
volume data and metrological data were provided by the Water 
Resource Management Office of the Waterworks Bureau of the 
Tokyo metropolitan government. We greatly appreciate for 
these organizations corporation. 
REFERENCES 
K, Saito, 2003. Estimated groundwater recharge including water 
pipes leakage in Kumagaya city. ACRS 2003 ISRS (The 24th 
Asian Conference on Remote Sensing & 2003 International 
symposium on remote sensing) 
W. Takeuchi, 2000. Estimation of Land Cover Mixing Ratio 
within a Pixel by Scaling between NOAA/AVHRR and 
LANDSAT/TM Data. 22nd Asian Conference of Remote 
Sensing