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Mesures physiques et signatures en télédétection

LERTS, UMR CNES-CNRS, 18, av. E. Belin
31055 Toulouse Cedex, France
The strong angular effects on reflectances implies the necessity to compose in a given period of time, called
the period of composition, the successive satellite observations of terrestrial reflectances, when monitoring
vegetation on regional or global scales. This paper reviews various techniques of data composition, with
emphasis given to recent work whose basic principle is to apply a regression between time series of observed
reflectances (corrected or not from atmospheric effects) and a model of bidirectional reflectance, which
expresses bidirectional reflectance as a function of Sun and view angles and a number of free parameters
related to the optical properties of the surface (and possibly of the atmosphere). As a result of the regression,
time profdes of observed reflectances are replaced by time profiles of reflectance corrected from angular
effects, this reflectance being in turn derived from the retrieved parameters of the regression.
Monitoring of terrestrial vegetation on regional or global scales from satellite measurements has an increasing
importance in several fields of science. In climate studies, an accurate and global description of vegetation is
necessary for an evaluation of energy, momentum and water fluxes at the interface biosphere-atmosphere,
since vegetation controls albedo, regulates the partition between sensible and latent heat fluxes, and decreases
air flow momentum. An accurate assessment of vegetation primary production is of prime importance for
agricultural surveys and predictions of cultures yields and biomass, and also for atmospheric chemistry studies
since primary production serves as an input for the evaluation of terrestrial sources and sinks of carbon dioxide
and trace gases. Analysis of vegetation cycles and phenology provides valuable informations on functioning of
either natural or cultivated vegetation, permits classification schemes and can be of great use in the field of
ecosystem dynamics.
Although various possibilities of spectral wavelengths combinations can be contemplated, the most
straightforward way to monitor vegetation from space on various scales is to observe the contrast between
visible and near infrared views of the Earth, which can be directly or indirectly related to the photosynthetic
activity of the vegetation, and from this to some description of the vegetation structure (Leaf Area Index,
vegetation cover, etc). The basic underlying requirements are to obtain accurate enough measurements of
reflectance in the visible and near infrared, at the best available spatial resolution, and with a temporal
resolution compatible with typical time scales of the vegetation evolution, that is about 10 days. Moreover,
these reflectance measurements should be comparable when taken at different places, separated from typically
1 to several thousands of kilometers, and also at different times, typically from a season to tens of years to
satisfy the needs of vegetation monitoring on regional or global scales.
The only satellite sensor series approaching these requirements has been so far the Advanced Very
High Resolution Radiometer (AVHRR) series embarked on the heliosynchronous polar platforms NOAA. The
AVHRR instruments have been extensively used in the last decade in vegetation monitoring applications (eg.,
Tucker et al., 1985; Townshend et al., 1987; Justice et al., 1985; Prince and Tucker, 1986; Prince, 1991; Fung
et al., 1987). The wide field of view of the instrument (+/- 56 ° across-track) permits a daily coverage of the
Earth, which leads on average to a few cloud-free measurements per decade. The raw measurements are not
directly comparable to each other in space and time, however. It is well-known (e.g., Duggin and Piwinski,
1984; Gutman, 1991; Goward et al., 1991) that the effects of calibration drifts, atmosphere variability and
composition, and Sun-target-sensor geometrical configurations must be taken care of by appropriate
corrections. Interannual calibration drifts can reach an amplitude of 10 to 20 % (Holben et al., 1990).
Atmospheric corrections have an important impact; inaccurate atmospheric corrections (for example due to