bl
ble
low
ble
and
ure
SOT.
to
)7).
del
[he
are
ere,
ton
lay
3).
ie,
1d,
ICS
ne
ns
ar
he
he
savanna is a consequence of a strict cloud detection. Based upon
these comparisons, it is difficult to say which product is the best
over sites where large differences are observed.
The last step of the POLDER-2 validation will be the
comparison of LAI and FVC to the reference products
generated from the ground measurements collected by the
VALERI (VAlidation of Land European Remote Sensing
Instrument) project (www2). From April to October 2003, 6
sites were instrumented around the world. The data are still
under processing.
4. CONCLUSION
The Level 3 algorithms developed to process the POLDER-2
data are based upon the inversion of a linear reflectance model
to estimate directional-hemispherical reflectances and NDVI,
and upon a neural network inverting a radiative transfer model
to calculate LAI and FVC. Before these inversions, a filtering
module scans the bi-directional BRDF and removes the
contaminated observations.
Directional coefficients, DHR, NDVI, LAI and FVC are
generated from Arpil to October 2003. They are validated using
temporal and spatial criteria of consistency, comparison with
POLDER-1 products, comparison with concomitant MODIS
products and, finally comparison with ground measurements.
Considering the first three steps, the POLDER-2 biophysical
parameters are relevant to characterize the land surface. The
spatial distribution and temporal evolution of ecosystems are
well reproduced, and the values are realistic. Some
discrepancies appears with MODIS products. Final comparisons
with concomitant ground measurements from VALERI
reference products will be soon performed.
REFERENCES
Bréon, F.M., F. Maignan, M. Leroy and l. Grant, 2002,
Analysis of hot spot directional signatures measured from
space. J. Geophys. Res., 107 (16), 4,282-4,296.
Calvet, J.C., J. Noilhan, J.L. Roujean, P. Bessemoulin, M.
Cabelguenne, A. Olioso, and J.P. Vigneron, 1998, An
interactive vegetation SVAT model tested against data from six
contrasting sites, Agric. For. Meteorol., 92, 73-95.
Chen, J.M. and T. A. Black, 1992, Defining leaf area index for
non-flat leaves, Plant, Cell and Environment, vol. 15, 421-429.
Deschamps, P.Y., F.M. Bréon, M. Leroy, A. Podaire, A.
Bricaud, J.C. Buriez, and G. Sèze, 1994, The POLDER mission:
instrument characteristics and scientific objectives, /EEE Trans.
Geosci. Remote Sens., GE-32, 598-614.
Henderson-Sellers, A., and A.J. Pitman, 1992, Land-surface
schemes for future climate models: Specifications, aggregation,
and heterogeneity, J. Geophys. Res., 97, 2687-2696.
Jacquemoud, S., S. L. Ustin, J. Verdebout, G. Scmuck, G.
Andreoli and B. Hosgood, 1996, Estimating leaf biochemistry
using the PROSPECT leaf optical properties model, Remote
Sens. Environ., vol. 56, 194-202.
Knyazikhin, Y., J.V. Martonchik, R. B. Myneni, D.J. Diner and
S.W. Running, 1998, Synergetic algorithm for estimating
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part Bl. Istanbul 2004
vegetation canopy leaf area index and fraction of absorbed
photosynthetically active radiation from MODIS and MISR
data, J. Geophys. Res., vol. 103, 32,257-32,275.
Kuusk, A., 1995, A fast invertible canopy reflectance model,
Remote Sens. Environ., vol. 51, 342-350.
Lacaze, R., P. Richaume, O. Hautecoeur, T. Lalanne, A.
Quesney, F. Maignan, P. Bicheron, M. Leroy, F.M. Bréon,
2003, Advanced algorithms of the ADEOS-2/POLDER-2 Land
surface process line : application to the ADEOS-1/POLDER-1
data. Proceedings of the IEEE International Geoscience and
Remote Sensing Symposium, Toulouse, France, July 21* -25'^.
Leroy, M. et al., 1997, Retrieval of atmospheric properties and
surface bi-directional reflectances over the land from
POLDER/ADEOS, J. Geophys. Res., vol. 102, 17,023-17,037.
Lucht, W., C. Barker Schaaf and A. Strahler, 2000, An
algorithm for the retrieval of albedo from space using
semiempirical BRDF models, IEEE Trans. Geosci. Remote
Sens., 38, 977-988.
Maignan, F., F.M. Bréon and R. Lacaze, 2004, Bidirectional
reflectance of Earth targets: evaluation of analytical models
using a large set of spaceborne measurements with emphasis
with the hot spot, Remote Sens. Environ., vol. 90, 210-220.
Myneni, R. B., R. R. Nemani, and S. W. Running, 1997,
Estimation of global leaf area index and absorbed PAR using
radiative transfer model, /EEE Transaction on Geoscience and
Remote Sensing, 35, 1380-1393.
Nilson, T. and A. Kuusk, 1989, A reflectance model for the
homogeneous plant canopy and its inversion, Remote Sens.
Environ., vol. 27, 157-167.
Noilhan, J. and P. Lacarrére, 1995, GCM grid-scale evaporation
from meso-scale modeling, J. Clim., 8, 206-223.
Price, J.C, 1990, On the information content of soil reflectance
spectra, Remote Sens. of Environ., vol. 33, 113-121.
Roujean, J.L., M. Leroy and P. Y. Deschamps, 1992, A bi-
directional reflectance model of the Earth's surface for the
correction of remote sensing data, J. Geophys. Res., vol. 97,
20,455-20,468.
Sato, N., P.J. Sellers, D.A. Randall, E.K. Schneider, J. Shukha,
J.L. Kinter III, Y.T. Hou, and E. Albertazzi, 1989, Effects of
implementing the simple biosphere model (SiB) in a general
circulation model, J. Atmos. Sci., 46, 2757-2782.
Verhoef, W., 1984, Light scattering by leaf layers with
application to canopy reflectance modeling: the SAIL model,
Remote Sens. Environ., vol. 16, 125-141.
Walthall, C.L., J. M. Norman, J. M. Welles, G. Campbell and B.
L. Blad,1985, Simple equation to approximate the bi-directional
reflectance from vegetative canopies and bare soil surfaces,
Applied Optics, vol. 24, 383-387.
wwwl: ftp://ersa.bu.edu/pub/rmyneni/myneniproducts/MODIS/
Www2: http://www.avignon.inra.fr/valeri/