preliminary correction should provide a better consistency of the data, both in time and space. Corrected 
global data sets are to be further analyzed, either for quantitative studies (e.g. Maisongrande et al. 1994) or in 
order to assess their accuracy, for example using well-documented test sites. 
In the future, atmospheric effects could be accounted for in a better way by using additional data sets 
either from atmospheric global circulation model analysis or provided by existing (e.g. TOMS) or new sensors 
(e.g. MODIS, POLDER). Pr omising methods are now being developed to normalize bidirectional reflectances 
(Cabot and Dedieu, 1993, Leroy and Roujean, 1994). More work is needed to improve compositing techniques 
(Qi and Kerr, 1994), since it is well known that MVC favours large scan angles. Also MVC is not well suited 
to fit bidirectional reflectance models with satellite measurements. Finally, improvements of system features 
such as orbit control, constant resolution over the whole field of view, and of preprocessing performance 
(geometric corrections, cloud screening, calibration monitoring) is a prerequisite to higher level corrections 
(atmosphere, surface anisotropy). 
ACKNOWLEDGEMENTS 
This work is a contribution to the ESCOBA project "The global carbon cycle and its perturbation by man and 
climate n. Part B: terrestrial biosphere", supported by the Environment Program of the Commission of the 
European Communities. 
REFERENCES 
Cabot, F. and G. Dedieu, Surface albedo from space: coupling bidirectional models and remotely sensed 
measurements. Submitted to J. Geophys. Res., 1993. 
Edwards, M.O., 1989, Global Grideded Elevation and Bathymetry (ET0P05), NOAA/NGDC, can be found 
on the CD-ROM : Global Ecosystems Database Version 1.0, 1992. 
Faizoun, C. A. and G. Dedieu, Atmospherical effects on NOAA/AVHRR shortwave measurements: 
Sensitivity study and use of atmospherical climatologies to correct AVHRR tima series, 6th AVHRR data 
users'meeting, Belgirate, Italy, 29th June- 23nd July 1993. 
Faizoun C.A., A. Podaire and G. Dedieu, 1994, Monitoring of sahelian aerosol and atmospheric water vapor 
content from sunphotometer measurements. Submitted to J. Appl. Meteorol. 
Goward, S.N., B. Marthaux, D.G. Due, W. Dukney, and J. Yan g , 1991, Normalized Difference Vegetation 
Index measurements drom AVHRR, Remote Seng. Envir. , 35,251-277. 
Kaufman Y.J. and B. N. Holben, 1993, Calibration of the AVHRR visible and near IR bands by atmospheric 
scattering, ocean glint and desert reflection. Int. J. Remore Sensing, 14,21-52. 
Kidwell K.B., Global Vegetation Index User's Guide. National Oceanic and Atmospheric Administration, 
World Weather Building, Washington, D.C., 1990. 
Leroy, M. and J.L. Roujean, 1994, Sun and view angle correction on reflectances derived from NOAA- 
AVHRR data. IEEE Trans. Geosci. Remote Sensing, In press. 
London, J., Bojkov R.D., Oltsmans S., Kelley J.I., 1976, Atlas of the global distribution of the total ozone 
july 1957-June 1967, NCAR/TN : 113 p + STR. 
Loudjani, P„ F. Cabot, V. Gond, and N. Viovy, Improving NDVI time series Using Imposed Threshold cm Irt, 
Ir and Visible Values (INTUlTlV): A method for reducing cloud con tamina tion on noise in NDVI time series 
over tropical and subtropical regions, this issue. 
Maisongrande, P. A. Ruimy, G. Dedieu, and B. Saugier, 1994, Comparison at global scale of C02 
concentration measurements with result of terrestrial biosphere model driven by remote sensing: some 
teachings about the required quality for the signal.. This issue. 
Oort. A. H., 1983, Global atmospheric circulation statistics: 1958-1973, NOAA Professional papers, 14, 
Rockville. MD. 
Qi, J. and Y.H. Kerr, On current algorithms, this issue. 
Rahman, H. and Dedieu G., 1994, SMAC: A Simplified Method for the Atmospheric Correction of Satellite 
Measurements in the Solar Spectrum., Int. J. of .Remote Sensing, in press. 
Tanr6 D„ C. Deroo, P. Duhaut, M. Herman, J.J. Morcrette, J. Perbos and P.Y. Deschamps. 1990: A 
description of a computer code to simulate the satellite signal in the solar spectrum: The 5S code. Intern. J. 
Remote Sens., 11,659-668. 
Tarn*, D.. Holben, B.N., and Y.J. Kaufman, 1992 : Atmospheric correction algorithm for NOAA-AVHRR 
products: theory and applications. IEEE Trans. Geosci. Remote Sensing, 30,2, 231-248. 
Teillet P.M. and R.P. Santer, 1991, Terrain elevation and sensor altitude dependance in a semi-analytical 
atmospheric code. Can. J. of Remote. Sensing., vol.17,1, p36-44. 
MONITORING P 
LERTS, Unité ] 
Monitoring of the calil 
various studies, involv 
Nevertheless, most of 
particularly the need f< 
monitoring of the gain ( 
The method that we de 
contribute to the mea; 
evolution. Directional e 
the season. At last, one 
cyclical behavior and 
describing atmospheric 
over long term period, 
atmospheric water vapc 
This method has been 
considering each senses 
1. INTRODUCTION 
Throughout the last ye! 
problems and gain dri 
especially in shortwave 
In order to solve such a 
get a realistic gain va 
approximately), atmosp 
The atmospheric and di 
effectively to the g ain d 
effects is their time peri 
of the non-lambertian 
expected to follow quiti 
The method presented 1 
time period, and whei 
continuously monitor tl 
been selected and obse 
stability. Some of thes 
complete an intercalibri 
2. DATA SET 
The data set we used v 
Atmospheric Administ 
infrared channels, brig] 
satellites, subsampled t 
launched in September 
40