. En-eeet, N. /. Dans-la-mesure, M. Avhrr, . Polder, and . Prism, entr ee des r eseaux de neurones sont normalis ees, l'utilisation conjointe de donn ees multi-capteurs n'est pas exclue (VEGETATION Op erationnel , notre algorithme de suivi de la v eg etation pourrait ^ etre coupl e avec des mod eles de fonctionnement de culture pour am eliorer la gestion de la production agricole mondiale par la pr evision de rendement ou le diagnostic de situation culturale en temps r eel

S. Ahmad, V. Tresp, S. J. Hanson, J. D. Cowan, and C. Giles, Some solutions to the missing feature problem in vision, 1993.

B. Albers, A. Strahler, X. Li, S. Liang, and C. K. , Radiometric measurements of gap probability in conifer tree canopies, Remote Sensing of Environment, vol.34, issue.3, pp.179-192, 1990.
DOI : 10.1016/0034-4257(90)90067-V

B. Andrieu, F. Baret, S. Jacquemoud, and T. Malthus, Evaluation of an improved version of SAIL model to simulate bidirectional reeectance of sugar beet canopies, pp.247-257, 1997.

B. Andrieu and H. Sinoquet, Evaluation of structure description requirements for predicting gap fraction of vegetation canopies, Agricultural and Forest Meteorology, vol.65, issue.3-4, pp.207-227, 1993.
DOI : 10.1016/0168-1923(93)90005-3

G. Asrar, M. Fuchs, E. Kanemasu, and J. Hatfield, Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1, Agronomy Journal, vol.76, issue.2, pp.300-306, 1984.
DOI : 10.2134/agronj1984.00021962007600020029x

G. Asrar and E. T. Kanemasu, Estimates of leaf area index from spectral reeectance of wheat under diierent cultural practices and solar angle, pp.1-11, 1985.

M. Chelle, D eveloppement d'un mod ele de radiosit e mixte pour simuler la distribution du rayonnement dans les couverts v eg etaux, 1997.

J. Chen and S. Leblanc, A four-scale bidirectional reflectance model based on canopy architecture, IEEE Transactions on Geoscience and Remote Sensing, vol.35, issue.5, pp.1316-1337, 1997.
DOI : 10.1109/36.628798

. Choudhuryb, Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis, Remote Sensing of Environment, vol.22, issue.2, pp.209-233, 1987.
DOI : 10.1016/0034-4257(87)90059-9

J. Clevers, Application of a weighted infrared-red vegetation index for estimating leaf Area Index by Correcting for Soil Moisture, Remote Sensing of Environment, vol.29, issue.1, pp.25-37, 1989.
DOI : 10.1016/0034-4257(89)90076-X

R. Del-ecolle, B. Loubet, and M. Tchamitchian, Calibration , sensibilit e, validation des mod eles, Actes de l' ecole chercheurs INRA en bioclimatologie, pp.285-303, 1995.

P. Deschamps, F. Br-eon, M. Leroy, A. Podaire, A. Bricaud et al., The POLDER mission: instrument characteristics and scientific objectives, IEEE Transactions on Geoscience and Remote Sensing, vol.32, issue.3, pp.598-611, 1994.
DOI : 10.1109/36.297978

R. Dickinson, Land Surface Processes and Climate???Surface Albedos and Energy Balance, Advanced Geophysics, vol.25, pp.305-353, 1983.
DOI : 10.1016/S0065-2687(08)60176-4

R. Dickinson, T. Hansen, and . Takahashi, Modeling evapotranspiration for three-dimensional global climate models, pp.58-72, 1984.
DOI : 10.1029/GM029p0058

G. Drago and S. Ridella, Statistically controlled activation weight initialization (SCAWI), IEEE Transactions on Neural Networks, vol.3, issue.4, pp.627-631, 1992.
DOI : 10.1109/72.143378

O. Engelsen, B. Pinty, M. Verstraete, and M. J. , Parametric bidirectional reeectance factor models : evaluation, improvements and applications, 1996.

M. Espa~-na, Simulation de la variation temporelle, directionnelle et spectrale de la r eeectance des cultures de ma s a partir d'un mod ele dynamique de la structure 3D du couvert, 1997.

J. Everitt, A. Richardson, and H. Gausman, Leaf reeectance-chlorophyll relations in buuelgrass, Photogrammetric Engineering and Remote Sensing, vol.51, pp.463-466, 1985.

L. Finschi, An implementation of the Levenberg- Marquardt Algorithm Eidgenn ossische Technische Hochschule ZZ urich, ZZ urich. Disponible sur le web a l'adresse, 1996.

T. Fourty and F. Baret, Vegetation water and dry matter contents estimated from top of atmosphere reeectance data : a simulation study, pp.34-45, 1997.

N. Gobron, B. Pinty, M. Verstraete, and Y. Govaerts, Presentation and application of an advanced model for the scattering of lightbyvegetation in the solar domain, Physical Measurements and Signatures in Remote Sensing, pp.267-273, 1997.

N. Goel, Models of vegetation canopy reeectance and their use in estimation of biophysical parameters from reeectance data, 1{213. ISBN, pp.3-7186, 1988.

N. Goel and D. Deering, Evaluation of a canopy reeectance model for LAI estimation through its inversion, IEEE Transactions on Geoscience and Remote Sensing, pp.674-684, 1989.

N. Goel and R. Thompson, Inversion of a vegetation canopy reeectance model for estimating agronomic variables. III : Estimating using only canopy reeectance data as illustrated by the Suits model, pp.223-236, 1984.

N. Goel and R. Thomson, Inversion of a vegetation canopy reeectance model for estimating agronomic variables. V. Estimation of leaf area index and average leaf angle using measured canopy reeectance, pp.77-111, 1984.

M. Gu, D. Courault, and N. Brisson, Assimilation de donn ees de t el ed etection dans les mod eles de fonctionnement des cultures, Actes de l' ecole-chercheurs INRA en bioclimatologie, pp.169-191, 1995.

F. Hall, J. Townshend, and E. Engman, Status of remote sensing algorithms for estimation of land surface state parameters, Remote Sensing of Environment, vol.51, issue.1, pp.138-156, 1995.
DOI : 10.1016/0034-4257(94)00071-T

B. Hapke, Bidirectional reflectance spectroscopy: 1. Theory, Journal of Geophysical Research: Solid Earth, vol.16, issue.B4, pp.3039-3054, 1981.
DOI : 10.1029/JB086iB04p03039

URL : http://hdl.handle.net/2060/19870014000

B. Hosgood, S. Jacquemoud, G. Andreoli, J. Verdebout, G. Pedrini et al., Leaf Optical Properties EXperiment 93 (LOPEX93), 1995.

A. Huete, A soil adjusted vegetation index (SAVI) Remote Sensing of Environment, pp.285-309, 1988.

A. R. Huete and H. Liu, An error and sensitivity analysis of the atmospheric- and soil-correcting variants of the NDVI for the MODIS-EOS, IEEE Transactions on Geoscience and Remote Sensing, vol.32, issue.4, pp.897-905, 1994.
DOI : 10.1109/36.298018

J. Iron, R. Weismiller, and G. Petersen, Theory and applications of optical remote sensing,Wileyinterscience, chapter Soil reectance, pp.66-106, 1989.

R. Jackson, Spectral response of architecturally different wheat canopies, Remote Sensing of Environment, vol.20, issue.1, pp.43-56, 1986.
DOI : 10.1016/0034-4257(86)90013-1

S. Jacquemoud, Mod elisation des propri et es optiques des feuilles. M emoire de dipl^ ome d' etudes approfondies, 1989.

S. Jacquemoud, Inversion of the PROSPECT+SAIL canopy reeectance model from AVIRIS equivalent spectra : Theoretical study, Remote Sensing of Environment, vol.44, pp.282-292, 1993.

S. Jacquemoud and F. Baret, PROSPECT: A model of leaf optical properties spectra, Remote Sensing of Environment, vol.34, issue.2, pp.75-91, 1990.
DOI : 10.1016/0034-4257(90)90100-Z

S. Jacquemoud, F. Baret, and J. Hanocq, Validation d'un mod ele de r eeectance spectrale et directionnelle du sol, Proceedings of the 5th Colloquium -Physical Measurements and Signatures in Remote Sensing. ESA 319, pp.427-430, 1991.

S. Jacquemoud, F. Baret, and J. , Modeling spectral and bidirectional soil reflectance, Remote Sensing of Environment, vol.41, issue.2-3, pp.123-132, 1992.
DOI : 10.1016/0034-4257(92)90072-R

Y. Jin and C. Liu, Biomass retrieval from high-dimensional active/passive remote sensing data by using artificial neural networks, International Journal of Remote Sensing, vol.18, issue.4, pp.971-979, 1997.
DOI : 10.1080/014311697218863

Y. Kaufman and C. Sendra, Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery, International Journal of Remote Sensing, vol.41, issue.8, pp.1357-1381, 1988.
DOI : 10.1175/1520-0450(1968)007<0484:SCIOTH>2.0.CO;2

Y. Kaufman and D. Tanr-e, Atmospherically resistant vegetation index (ARVI) for EOS-MODIS, IEEE Transactions on Geoscience and Remote Sensing, vol.30, issue.2, pp.261-270, 1992.
DOI : 10.1109/36.134076

Y. H. Kerr, J. Lagouarde, and I. J. , Accurate land surface temperature retrieval from AVHRR data with use of an improved split window algorithm, Remote Sensing of Environment, vol.41, issue.2-3, pp.197-209, 1992.
DOI : 10.1016/0034-4257(92)90078-X

D. Kimes, K. Ranson, and S. G. , Inversion of a forest backscatter model using neural networks, International Journal of Remote Sensing, vol.18, issue.10, pp.182181-2199, 1997.
DOI : 10.1080/014311697217828

Y. Knyazikhin, J. Martonchik, D. Diner, R. Myneni, M. Vertraete et al., Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere-corrected MISR data, Journal of Geophysical Research: Atmospheres, vol.30, issue.7, pp.32239-32256, 1998.
DOI : 10.1029/98JD02461

Y. Knyazikhin, J. Martonchik, R. Myneni, D. Diner, and S. Running, Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data, Journal of Geophysical Research: Atmospheres, vol.95, issue.D24, pp.32257-32275, 1998.
DOI : 10.1029/98JD02462

P. Koepke and H. Quenzel, Turbidity of the atmosphere determined from satellite: Calculation of optimum viewing geometry, Journal of Geophysical Research, vol.13, issue.C12, pp.7847-7855, 1979.
DOI : 10.1029/JC084iC12p07847

P. Kubelka and F. Munk, Ein betrag zur optik der farbanstriche, Ann. Tech. Phys, vol.11, pp.593-61, 1931.

A. Kuusk, The hot spot eeect of a uniform vegetative cover, Sovietic Journal of Remote Sensing, vol.3, issue.4, pp.645-658, 1985.

A. Kuusk, R. B. Myneni, and J. Ross, chapter The hot spot eeect in plant canopy reeectance, Photon-Vegetation interactions, pp.139-159, 1991.

A. Kuusk, A multispectral canopy reflectance model, Remote Sensing of Environment, vol.50, issue.2, pp.75-82, 1994.
DOI : 10.1016/0034-4257(94)90035-3

A. Kuusk, A fast, invertible canopy reflectance model, Remote Sensing of Environment, vol.51, issue.3, pp.342-350, 1995.
DOI : 10.1016/0034-4257(94)00059-V

R. Lawrence and W. Ripple, Comparisons among Vegetation Indices and Bandwise Regression in a Highly Disturbed, Heterogeneous Landscape: Mount St. Helens, Washington, Remote Sensing of Environment, vol.64, issue.1, pp.91-102
DOI : 10.1016/S0034-4257(97)00171-5

M. Leroy and J. Roujean, Sun and view angle corrections on reflectances derived from NOAA/AVHRR data, IEEE Transactions on Geoscience and Remote Sensing, vol.32, issue.3, pp.684-697, 1994.
DOI : 10.1109/36.297985

X. Li and A. Strahler, Geometrical-optical bidirectional reectance modeling of conifer forest canopy, IEEE Transactions on Geoscience and Remote Sensing GE, issue.24, pp.906-919, 1986.

X. Li and A. Strahler, Modeling the gap probability of a discontinuous vegetation canopy, IEEE Transactions on Geoscience and Remote Sensing, vol.26, issue.2, pp.161-170, 1988.
DOI : 10.1109/36.3017

S. Los, C. Justice, and T. C. , A global 1?? by 1?? NDVI data set for climate studies derived from the GIMMS continental NDVI data, International Journal of Remote Sensing, vol.25, issue.17, pp.153493-3518, 1994.
DOI : 10.1080/01431169408954342

D. Major, G. Schaalje, C. Wiegand, and B. , Accuracy and sensitivity analysis of SAIL model-predicted reeectance of maize. Remote sensing of environment, pp.61-70, 1992.

T. Malthus, Anglo-french collaborative reeectance experiment. report and data, p.38, 1990.

C. Mejia, S. Thiria, N. Tran, and M. Cr-epon, Determination of the geophysical model function of the ERS-1 scatterometer by the use of neural networks, Journal of Geophysical Research: Oceans, vol.99, issue.C6, pp.12853-12868, 1998.
DOI : 10.1029/97JC02178

M. Minnaert, The reciprocity principle in lunar photometry, The Astrophysical Journal, vol.93, pp.403-410, 1941.
DOI : 10.1086/144279

J. Monteith, Solar Radiation and Productivity in Tropical Ecosystems, The Journal of Applied Ecology, vol.9, issue.3, pp.747-766, 1972.
DOI : 10.2307/2401901

R. Myneni, G. Asrar, and H. F. , A three-dimensional radiative transfer method for optical remote sensing and plant ecology, pp.105-121, 1992.

R. Myneni, F. Hall, P. Sellers, and A. Marshak, The interpretation of spectral vegetation indexes, IEEE Transactions on Geoscience and Remote Sensing, vol.33, issue.2, pp.481-486, 1995.
DOI : 10.1109/36.377948

R. Myneni, S. Maggion, J. Iaquinta, J. Privette, N. Gobron et al., Optical remote sensing of vegetation: Modeling, caveats, and algorithms, Remote Sensing of Environment, vol.51, issue.1, pp.169-188, 1995.
DOI : 10.1016/0034-4257(94)00073-V

R. Myneni and D. Williams, On the relationship between FA- PAR and NDVI. Remote Sensing of the Environment, pp.200-211, 1994.

I. Nabney and C. Bishop, Modelling wind direction from satellite scatterometer data, Neural Computing Research Group, 1995.

J. Nelder and R. Mead, A Simplex Method for Function Minimization, The Computer Journal, vol.7, issue.4, pp.308-313, 1987.
DOI : 10.1093/comjnl/7.4.308

T. Nilson, A theoretical analysis of the frequency of gaps in plant stands, Agricultural Meteorology, vol.8, pp.25-38, 1971.
DOI : 10.1016/0002-1571(71)90092-6

A. Olioso, D. Courault, H. Chauki, J. P. Wigneron, C. Ottl-e et al., Estimation de l' e]vapotranspiration et de la photosynth ese al'aidedemod eles de TSVAetdelatemp erature de surface, Physical Measurements and Signatures in Remote Sensing, pp.841-851, 1997.

C. Ottl-e and D. Vidal-madjar, Estimation of land surface temperature with NOAA9 data, Remote Sensing of Environment, vol.40, issue.1, pp.27-41, 1992.
DOI : 10.1016/0034-4257(92)90124-3

R. Pearson and L. Miller, Remote mapping of standing crop biomass for estimation of the productivity of the short-grass Prairie, Pawnee National Grasslands, Colorado, 8th International Symposium on Remote Sensing of Environment. ERIM, Ann Arbor MI, pp.1357-1381, 1972.

B. Pinty and M. Verstraete, Extracting information on surface properties from bidirectional reflectance measurements, Journal of Geophysical Research, vol.21, issue.D2, pp.2865-2874, 1991.
DOI : 10.1029/90JD02239

B. Pinty and M. Verstraete, GEMI: a non-linear index to monitor global vegetation from satellites, Vegetatio, vol.91, issue.1, pp.15-20, 1992.
DOI : 10.1007/BF00031911

B. Pinty and M. Verstraete, On the design and validation of surface bidirectional reflectance and albedo models, Remote Sensing of Environment, vol.41, issue.2-3, pp.155-167, 1992.
DOI : 10.1016/0034-4257(92)90075-U

L. Pr, F. Baret, A. Chanzy, and A. Olioso, Assimilation of multi-sensor and multi-temporal remote sensing data to monitor vegetation and soil : the Alpilles-ReSeDA project, IGARSS'98, International GeoscienceandRemote Sensing Symposium, 1998.

J. Price, On the information content of soil reflectance spectra, Remote Sensing of Environment, vol.33, issue.2, pp.113-119, 1990.
DOI : 10.1016/0034-4257(90)90037-M

J. Privette, R. Myneni, C. Tucker, and E. W. , Invertibility of a 1-D discrete ordinates canopy reeectance model, pp.89-105, 1994.

J. Qi, A. Chehbouni, A. Huete, Y. Kerr, and S. Sorooshian, A modiied soil adjusted vegetation index, pp.119-126, 1994.

W. Qin and N. Goel, An evaluation of hotspot models for vegetation canopies, Remote Sensing Reviews, vol.3, issue.1-2, pp.121-159, 1995.
DOI : 10.1029/JD095iD08p11755

H. Rahman, Inferring spectral surface albedo from bidirectional reflectance measurements, Geocarto International, vol.98, issue.1, pp.41-46, 1998.
DOI : 10.1080/01431168508948283

H. Rahman and G. Dedieu, SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum, International Journal of Remote Sensing, vol.928, issue.1, pp.123-143, 1994.
DOI : 10.1364/AO.29.001897

H. Rahman, B. Pinty, and M. , Coupled Surface- Atmosphere Reeectance (CSAR) model. 2. Semiempirical surface model usable with NOAA Advanced Very High Resolution Radiometer Data, Journal of Geophysical Research, issue.D11, pp.9820791-20801, 1993.

A. Richardson and C. Wiegand, Distinguishing vegetation from soil background information, Photogrammetry Engeneering on Remote Sensing, vol.43, pp.1541-1552, 1977.

R. Rojas, Neural Networks. A systematic introduction, p.502, 1996.

J. Ross and A. Marshak, Photon-Vegetation interactions, pp.441-464, 1991.

W. Rossow, L. Gardner, P. Lu, and W. A. , International Satellite Cloud Climatology Project (ISCCP), documentation on cloud data, World Meteorological Organisation, 1988.

J. Roujean and F. Br-eon, Estimating PAR absorbed by vegetation from bidirectional reflectance measurements, Remote Sensing of Environment, vol.51, issue.3, pp.375-384, 1995.
DOI : 10.1016/0034-4257(94)00114-3

J. Roujean, M. Leroy, and P. Deschamps, A bidirectional reeectance model of the Earth's surface for the correction of remote sensing data, Journal of Geophysical Research, issue.D18, pp.9720455-20468, 1992.

J. Roujean, . Leroym, A. Podaire, and P. , Evidence of surface reflectance bidirectional effects from a NOAA/ AVHRR multi-temporal data set, International Journal of Remote Sensing, vol.319, issue.4, pp.685-698, 1992.
DOI : 10.1080/01431169208904146

J. Rouse, R. Haas, J. Schell, D. Deering, and H. J. , Monitoring the vernal advancement of retrogradation of natural vegetation . Type III 371pp, 1974.

J. Royer, A. Olioso, and C. D. , Les mod eles de circulation g en erale de l'atmosph ere, Actes de l' ecole chercheurs INRA en bioclimatologie, pp.193-226, 1995.

W. Sarle, Stopped training and other remedies for overtting, of the 27th Symposium on the Interface of computing science and statistics. pp. 352{360. Disponible sur le web, 1995.

P. Sellers, Canopy reeectance, photosynthesis and transpiration, International Journal of Remote Sensing, issue.6 8, pp.1335-1372, 1985.

P. Sellers, Canopy reflectance, photosynthesis, and transpiration, II. The role of biophysics in the linearity of their interdependence, Remote Sensing of Environment, vol.21, issue.2, pp.143-183, 1987.
DOI : 10.1016/0034-4257(87)90051-4

P. Sellers, S. Los, C. Tucker, C. Justice, D. Dazlich et al., A global 1 by 1 degree NDVI data set for climate studies. Part 2 : the generation of global elds of terrestrial biophysical parameters from the NDVI, International Journal of Remote Sensing, issue.17, pp.153519-3545, 1994.

P. Sellers, S. Los, C. Tucker, C. Justice, D. Dazlich et al., A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part II: The Generation of Global Fields of Terrestrial Biophysical Parameters from Satellite Data, Journal of Climate, vol.9, issue.4, pp.706-737, 1996.
DOI : 10.1175/1520-0442(1996)009<0706:ARLSPF>2.0.CO;2

P. Sellers, Y. Mintz, Y. Sud, and A. Dalcher, A Simple Biosphere Model (SIB) for Use within General Circulation Models, Journal of the Atmospheric Sciences, vol.43, issue.6, pp.43505-531, 1986.
DOI : 10.1175/1520-0469(1986)043<0505:ASBMFU>2.0.CO;2

M. Shibayama and C. Wiegand, View azimuth and zenith, and solar angle effects on wheat canopy reflectance, Remote Sensing of Environment, vol.18, issue.1, pp.91-103, 1985.
DOI : 10.1016/0034-4257(85)90040-9

M. Shibayama, C. Wiegand, and A. Richardson, Diurnal patterns of bidirectional vegetation indices for wheat canopies, International Journal of Remote Sensing, vol.71, issue.2, pp.233-246, 1986.
DOI : 10.1080/01431168608954678

J. Smith, LAI inversion using a backpropagation neural network trained with multiple scattering model, IEEE Transactions on GeoscienceandRemote Sensing, issue.5, pp.311102-1106, 1993.

V. Steinmetz, B. Cauquil, and F. Bocquet, Des neurones dans le champagne, Ingenieries -EAT, vol.3, pp.23-28, 1995.
URL : https://hal.archives-ouvertes.fr/hal-00467457

A. Strahler, M. Barnsley, R. D-'entremont, B. Hu, P. Lewis et al., MODIS BRDF/Albedo product : algorithm theoritical basis document, 1995.

G. Suits, The calculation of the directional reflectance of a vegetative canopy, Remote Sensing of Environment, vol.2, pp.117-125, 1972.
DOI : 10.1016/0034-4257(71)90085-X

D. Tanr-e, C. Deroo, P. Duhaut, M. Herman, J. Morcrette et al., Technical note Description of a computer code to simulate the satellite signal in the solar spectrum: the 5S code, International Journal of Remote Sensing, vol.53, issue.4, pp.659-668, 1990.
DOI : 10.1364/AO.20.003676

J. Tarpley, R. Schneider, and R. Money, Global Vegetation Indices from the NOAA-7 Meteorological Satellite, Journal of Climate and Applied Meteorology, vol.23, issue.3, pp.491-494, 1984.
DOI : 10.1175/1520-0450(1984)023<0491:GVIFTN>2.0.CO;2

S. Thiria, C. Mejia, and F. Badran, A neural network approach for modeling nonlinear transfer functions: Application for wind retrieval from spaceborne scatterometer data, Journal of Geophysical Research, vol.1, issue.C12, pp.9822827-22841, 1993.
DOI : 10.1029/93JC01815

C. Touzet, Les r eseaux de neurones artiiciels. Introduction au connexionisme, 1992.

V. Tresp, R. Neumeier, and A. S. , Advances in neural information processing systems 7, 1995.

C. Tucker, Red and photographic infrared linear combinations for monitoring vegetation, Remote Sensing of Environment, vol.8, issue.2, pp.127-150, 1979.
DOI : 10.1016/0034-4257(79)90013-0

W. Verhoef, Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model, Remote Sensing of Environment, vol.16, issue.2, pp.125-141, 1984.
DOI : 10.1016/0034-4257(84)90057-9

W. Verhoef, Earth observation modeling based on layer scattering matrices, Remote Sensing of Environment, vol.17, issue.2, pp.165-178, 1985.
DOI : 10.1016/0034-4257(85)90072-0

M. Verstraete and B. Pinty, Designing optimal spectral indexes for remote sensing applications, IEEE Transactions on Geoscience and Remote Sensing, vol.34, issue.5, pp.1254-1264, 1991.
DOI : 10.1109/36.536541

M. Verstraete, B. Pinty, and R. Myneni, Potential and limitations of information extraction on the terrestrial biosphere from satellite remote sensing, Remote Sensing of Environment, vol.58, issue.2, pp.201-214, 1996.
DOI : 10.1016/S0034-4257(96)00069-7

E. Walter-shea, J. Privette, D. Cornell, M. Mesarch, and C. Hays, Relations between directional spectral vegetation indices and leaf area and absorbed radiation in Alfalfa, Remote Sensing of Environment, vol.61, issue.1, pp.162-177, 1997.
DOI : 10.1016/S0034-4257(96)00250-7

C. Walthall, A study of reflectance anisotropy and canopy structure using a simple empirical model, Remote Sensing of Environment, vol.61, issue.1, pp.118-128, 1997.
DOI : 10.1016/S0034-4257(96)00245-3

C. Walthall, J. Norman, J. Welles, G. Campbell, and B. , Simple equation to approximate the bidirectional reflectance from vegetative canopies and bare soil surfaces, Applied Optics, vol.24, issue.3, pp.383-387, 1985.
DOI : 10.1364/AO.24.000383

M. Weiss, F. Baret, M. Leroy, A. Hautecoeur, O. Santer et al., Hemispherical reeectance and albedo estimates from the accumulation of across track sun synchroneous datarach, 1999.

L. Wessels and E. Barnard, Avoiding false local minima by proper initialization of connections, IEEE Transactions on Neural Networks, vol.3, issue.6, pp.899-905, 1992.
DOI : 10.1109/72.165592

C. Wiegand, J. Richardson, D. Escobar, and A. Gerbermann, Vegetation indices in crop assessments, Remote Sensing of Environment, vol.35, issue.2-3, pp.105-119, 1991.
DOI : 10.1016/0034-4257(91)90004-P

B. Yoder and R. Pettigrew-crosby, Predicting nitrogen and chlorophyll content and concentration from reeectance spectra (400- 2500nm) at leaf and canopy scales, pp.199-211, 1995.