1128 
The first step displays the methodology of simulation tested at a high spatial resolution. We simulate 
the temporal profile of the canopy reflectances in the SPOT/HRV wavelengths. Radiative variables are 
obtained through the linkage of a production model with a reflectance model. Here we compare results that 
can be computed with several radiative transfer models. For each available acquisition day, we compare SPOT 
observations with predicted reflectances over the study site. It is a validation of the methodology applied to 
predict radiometric signal. The second step concerns the assimilation of satellite measurements into crop 
growth model. SPOT observations are used as a reference. Then, the sowing date is adjusted to obtain 
modelled reflectances as close as possible to remotely sensed measures. Retrieved sowing date is then 
introduced in growth model to estimate carbon fluxes. Here again, we compare results obtained with 4 
radiative transfer models. 
2 - MATERIALS AND METHODS 
We particularly consider the agricultural region of the Beauce, where wheat and barley are largely represented. 
Over this well-known crop region, growth models relative to many crops are available. Moreover, as many 
environmental factors can be controlled, the dependence of green cover growth and development with external 
parameters is limited. The study area concerns a 40km by 40km surface in the south-west of Paris. 
2.1. Satellite data : High spatial resolution 
High spatial resolution data acquired by SPOT/HRV are used for this field scale study (Table 1). SPOT/HRV 
observations are available for 5 clear days during the activity period of winter wheat Satellite measurements 
have been corrected to take into account calibration and atmospheric effects. Climatologies have been used for 
water vapour and ozone atmospheric contents. A constant value of optical depth is chosen to compute the 
aerosol effects. 
acquisition date 
view zenith angle 
view azimuth angle 
solar zenith angle 
solar azimuth angle 
09 April 
-6.6 
104.0 
42.2 
162.6 
13 May 
-16.8 
105.3 
30.9 
163.0 
18 May 
-22.7 
106.2 
29.6 
164.7 
19 May 
4.3 
282.6 
30.5 
155.4 
19 July 
30.3 
100.8 
29.8 
162.6 
Table 1 : SPOT/HRV data acquisition angles, in degrees, over the Beauce region, during activity period of 
winter cereals. 
As shown on Table 1, we have got 5 acquisitions dates, and we note that observations have been acquired in 
different angular configurations. This geometry has been taken into account to simulate reflectances. The 
observation dates are distributed over the winter cereals activity period. On April 9, it is the beginning of the 
crops growth period. In May (13, 18 and 19) winter vegetation reaches its maturity stage. On July 19, cereals 
have already been harvested. 
12. Land use occupation 
Many information about our study site can be available through a pilot project applying remote sensing to 
agricultural statistics (Sharman and Boissezon, 1992). We first have a land use classification performed over 
the 40km by 40km studied area which gives all the represented vegetal species and their respective surfaces. 
Then, a sampling has been carried out over 16 test-sites of 700m by 700m uniformly distributed over the site. 
Here, for most fields of the test-sites, we have got additional information like plant variety, sowing date and 
crop yield (estimated by farmers). 
23. Vegetation and radiative transfer models 
2.3.1 The crop growth model AFRCWHEAT2 
This functional model (Porter et al., 1992) can predict daily net assimilation of carbon dioxide by the 
vegetation, respiration, assimilates distribution in different plant organs, phenological development, and 
organic dry matter net production. The input parameters are : the meteorological data (minimum and 
maximum daily temperatures, solar irradiance, precipitation, wet bulb temperature, mean wind speed), the