The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
3.3.2 Parameter inversion techniques study: Guided by 
theories on energy flow and materials exchange with in Soil, 
Atmosphere, Plant Continuant (SPAC), based on the thermal 
infrared and visible light information extracted from FY 
satellites, multiple kinds of energy and water balance 
parameters could be retrieved, such as land surface temperature, 
evaporation, vegetable transpiration, etc,. 
Land surface energy allocation and water balance’s formulas 
are listed as below (McAneney K.J., et al. 1995). 
I„ = H + LE + G (1) 
P = E + I + R 
where /„ = land surface net radiation flux 
H = heat flux from land surface to atmosphere 
LE = real transpiration 
G = heat flux in soil layer from ground 
P = precipitation 
E = Transpiration including ground evaporate and 
vegetation leaf area transpiration 
/ = ground water infiltration 
R = ground water run off 
Water parameters of SPAC can be achieved through the remote 
sensing image reflection. SPAC includes 2 water parameters, 
i.e., precipitation and ground transpiration. Traditional method 
based on field survey restricts the large area soil moisture 
monitoring in real time because of limited in-situ observation 
sites. Remote sensing makes the precipitation and transpiration 
data available quickly complemented with ground survey data. 
Transpiration includes two parts, i.e., ground evaporation and 
vegetation leaf transpiration. Its calculation based on the 
formula (1) and (2). We can get these data from FY-2 images 
through 5 steps as below. 1 2 3 4 5 
1. Correspondents 
2. Atmosphere correction 
3. Net radiation calculate 
4. Heat flux calculate 
5. Real transpiration calculate 
=(<*«+a, Xr.-r„) (2) 
where CC c , (X r = surface and atmosphere impedance (4~6) 
T Q , T a = surface and atmosphere temperature 
3.4 Conclusions 
In general, Chinese satellite images have their unique features 
respectively. According to different research targets, these 
satellite images can be selected and mixed use. For example, 
Beijing-1 image is suitable for local area land use/cover 
classification and mapping because of its high spatial resolution. 
CBERS image is suitable for regional resources monitoring 
because of its multi spectrum and middle-high spatial resolution. 
FY image is suitable for land surface energy and water balance 
parameter reflection because of its high temporal resolution and 
thermal channel. While, more and more practices should be 
experimented in the near future to discover the monitoring, 
information inversion and regional ecological evaluation 
techniques based on Chinese satellites. 
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ACKNOWLEDGEMENTS 
Thanks Nature Science Founding (40771146) of China, and 
Front Field project for new personality of Knowledge 
Innovation Program of the IGSNRR, CAS, and MOST funding 
(2005DKA32300) of China for their support. Thanks the data 
resources supported by Data Sharing Network of Earth System 
Science in China (http://www.geodata.cn). 
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