Monitoring Agricultural Drought in Mainland Portugal - Monitoring and Predicting Agricultural Drought: A Global Study - page 191

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4 and channel 5 of the AVHRR. The temporal variation in the FFRI is
analyzed for different test sites and compared with the temporal variation
at each respective site for a representative year to detect drought conditions.
Satellite Application Facilities (SAFs) are specialized centers within the
European Organization for Exploitation of Meteorological Satellites
Applications Ground Segment and are hosted by the European National
Meteorological Services in member states. The Portuguese Institute of Me-
teorology ( www.meteo.pt) is responsible for the development of the SAF
for land surface analysis in Portugal ( www.meteo.pt/landsaf). The main
purpose of this SAF is to enhance the benefits of the EUMETSAT satel-
lite systems, Spinning Enhanced Visible and InfraRed Imager/Meteosat
Second Generation and EUMETSAT Polar System related to land, land-
atmosphere interactions, and biophysical applications by developing the
techniques, products, and algorithms for more effective use of the satellite
data. The land SAF involves the near real-time generation, archiving, and
distribution of a coherent set of products that characterize the land sur-
face by surface temperature, albedo, evapotranspiration, snow/ice cover,
soil moisture, and vegetation parameters that are especially relevant to
drought management. Some of these products include the leaf area in-
dex (LAI), the fractional vegetation cover (FVC), and the fraction of ab-
sorbed photosynthetic active radiation (fAPAR) or the fraction of green
vegetation (FGV). The quality of these products depends to a large ex-
tent on the sensor characteristics (spectral, radiometric, and geometric),
cloud detection, atmospheric correction, and angular distribution of the
observations.
The algorithms used to estimate biophysical parameters in the land
SAF depend on empirical relationships for vegetation indices (Asrar et al.,
1985), inversion models (Roujean et al., 1992; Knyazikhin et al., 1998;
Bicheron and Leroy, 1999), and physical and empirical models (Qin and
Goel, 1995; Weiss and Baret, 1999; Lacaze and Roujean, 2001). Two
complementary inversion approaches for the retrieval of FVC and LAI
include kernel-driven reflectance models (Roujean et al., 1992) that ob-
tain nadir-zenith reflectance as an input, before applying a more robust
technique—namely, variable multiple endmember spectral mixture anal-
ysis (VMESMA; García-Haro et al., 2002a). With VMESMA it will be
possible to estimate the subpixel abundance of vegetation, soils, and other
spectrally distinct materials that fundamentally contribute to the spectral
signal of the mixed pixels. Although the primary output is FVC, some
empirical relationships can be then used to derive LAI (Lacaze and Rou-
jean, 2001). The application of a directional strategy relates the Bidirec-
tional Reflectance Distribution Function of the surface with the directional
signatures of vegetation and soil and meaningful biophysical parameters
(García-Haro et al., 2002b). Reflectance of an individual pixel is assumed
to consist of an area-weighted linear combination of the soil and vegeta-
tion radiances. Canopy geometrical effects are considered in the first-order
scattering. The model makes a simple treatment of the multiple scattering

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