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Title
Mesures physiques et signatures en télédétection

BACKWARD ANGLE (deg) FORWARO REFLECTANCE (per cent) and NOVI*100
Fipiire 1 : Top: Variation of visible (o), near infrared (x) and
NDVI (*) calculated from cloud-screened data in JulyAugust
JulyAugust 1986. Bottom: variation of solar zenith (o) and offnadir
offnadir viewing (*) angles during July-August 1986. (from
Gutman, 1987)
Figure 2 : Time series of TOA reflectances (full curves) and
surface reflectances (dotted curves), (a) and (b): visible
band; (c) and (d): near infrared band, bars stand for the
standard deviation of errors of the atmospheric correction,
(from Roujean el al., 1992a).
time profiles of ref
retrieved paramete
Data com
emphasize that apf
satellite optical se
channels, such as 1
elevation during
MERIS/ENVIS AT
will require simi
heliosynchronous
additional capacit;
techniques, in an ii
2 - MAXIMUM V
JULIAN DAY
erroneous estimates of water vapor and aerosols) can result in extreme conditions in errors of the retrieved
reflectances commensurable with the actual value of surface reflectances (Tanré et al., 1992). Moreover, the
variations of Sun-target-sensor configurations between consecutive measurements can induce large
fluctuations of observed reflectances, in phase with the orbit cycle of AVHRR (Gutman, 1987; Fig. 1). These
effects may originate from the atmosphere or from the surface. The dominant effect seems to be that of the
surface, however; atmospheric corrections do not alter significantly the saw-tooth like pattern which is the
characteristic signature of directional effects (Roujean et al., 1992a; Fig.2). The peak-to-peak signal variations
may be very large, about 100 % and 50 % of the average reflectance in the visible and in the near infrared
respectively (Fig. 2). These findings are consistent with ground truth measurements of surface bidirectional
effects (e.g., Kriebel, 1978; Kimes, 1983).
There is a qualitative difference between atmospheric corrections and surface bidirectional reflectance
corrections. While atmospheric corrections are generally performed with ancillary data from various sources
(climatology, other sensors data), it is difficult to conceive a correction of surface bidirectional effects which
would not extract the directional information from the reflectance data themselves. The directional reflectance
signature of a surface depends in a complicated way of the optical and structural properties of the surface, and
is therefore hardly predictable from external sources. This is the primary reason why some kind of data
compositing over a given period of time, and associated losses of temporal resolution, seem unavoidable. A
second advantage of data compositing is that it statistically removes the high frequency temporal variations
due to inaccuracies in the atmospheric correction procedure.
The aim of this paper is to briefly review existing methods of data composition, and discuss recent
work where data composition is conceived as a fitting procedure between a time series of reflectances,
corrected or not from atmospheric effects, during a given period (called here a period of composition), and a
parameterized model of bidirectional reflectance. The original time series of reflectances is then replaced by
The data composit
technique (Tarple;
AVHRR data wh
difference betweei
composition may \
cover conditions. '
vegetation monitoi
Vegetation Index (
this method is that
the Sun-target or tt
of the AVHRR d:
effects.
The adeqi
and Hendcrson-Se
an erroneous meat
(1991) has noticedirection,
noticedirection, a conclu
South-East of Fran
angles obtained bj
during the month c
obvious. Moreovei
(Fig. 3). It is appt
results in errors sir
NADIR ANC
22 -
20 -
V7\ 10-QAY
Other mei
viewing geometry
22