Inversion methods for physically‐based models

References

• Abuelgasim , A.A. , Gopal , S. and Strahler , A.H. 1998 . Forward and inverse modeling of canopy directional reflectance using a neural network . Int. J. Remote Sens. , 19 : 453 – 471 .
   Web of Science ®Google Scholar
• Abuelgasim , A.A. , Gopal , S. , Irons , J.R. and Strahler , A.H. 1996 . Classification of ASAS multiangle and multispectral measurements using artificial neural networks . Remote Sens. Environ. , 57 : 79 – 87 .
   Web of Science ®Google Scholar
• Abuelgasim , A.A. , Irons , J.R. , Privette , J.L. , Kovalick , W. , Dabney , P. and Russel , C.A. 2000 . Inversion of a Physically‐based BRDF model using neural networks and ASAS directional data . Int. J. Remote Sens. , (submitted)
   Google Scholar
• Asner , G.P. , Wessman , C.A. , Schimel , D.S. and Archer , S. 1998 . Variability in leaf and litter optical properties: implications for BRDF model inversions using AVHRR, MODIS and MISR . Remote Sens. Environ. , 63 : 243 – 257 .
   Web of Science ®Google Scholar
• Asner , G.P. , Wessman , C.A. and Privette , J.L. 1997 . Unmixing the directional reflectances of AVHRR sub‐pixel landcovers . IEEE Trans. Geosci. Remote Sens. , 35 : 868 – 878 .
   Web of Science ®Google Scholar
• Asrar , G. and Dozier , J. 1994 . EOS ‐ Science Strategy for the Earth Observing System , Woodbury, New York : AIP Press .
   Google Scholar
• Baret , F. , Clevers , J.G.P.W. and Steven , M.D. 1995 . The robustness of canopy gap fraction estimates from red and near‐infrared reflectances: a comparison of approaches . Remote Sens. Environ. , 54 : 141 – 151 .
   Web of Science ®Google Scholar
• Bass , L.P. , Volocsvhenko , A.M. and Germogenova , T.A. 1986 . Methods of discrete ordinates in radiation transport problems. Moscow: Inst. Appl. Math. . Russ. Acad. Sci. , : 231 (in Russian, with English abstract)
   Google Scholar
• Bell , G.I. and Glasstone , S. 1970 . Nuclear Reactor Theory , 619 New York : Van Nostrand Reinholt .
   Google Scholar
• Borel‐Donohue , C.C. 1988 . “ Models for back scattering of millimeter waves from vegetative canopies ” . Mass 01003 : Dept. Electrical and Computer Eng., Univ. of Massachusetts at Amherst . Ph. D. Thesis
   Google Scholar
• Braswell , B.H. , Schimel , D.S. , Privette , J.L. , Moore , B. III , Emery , W.J. , Sulzman , E. and Hudak , A.T. 1996 . Extracting ecological and biophysical information from AVHRR optical measurements: an integrated algorithm based on inverse modeling . J. Geophys. Res. , 101 (D18) : 23335 – 23348 .
   Web of Science ®Google Scholar
• Camillo , P. 1987 . A canopy reflectance model based on an analytical solution to the multiple scattering equation . Remote Sens. Environ. , 23 : 453 – 477 .
   Web of Science ®Google Scholar
• Chen , M.S. and Manry , M.T. Back‐propagation representation theorem using power series . Proceedings of International Joint Conference on Neural Networks (IJCNN) 90 . San Diego, California. I‐643‐I‐648
   Google Scholar
• Chen , S.G. , Shao , B.Y. , Impens , I. and Ceulemans , R. 1994 . Effect of plant canopy structure on light interception and photosynthesis . J. Quant. Spectrosc. Radiat. Transfer , 52 : 115 – 123 .
   Web of Science ®Google Scholar
• Choulli , M. and Stefanov , P. 1996 . Reconstruction of the coefficient of the stationary transport equation from boundary measurements . Inverse Problems , 12 : L19 – L23 .
   Web of Science ®Google Scholar
• Congalton , R. 1991 . A review of assessing the accuracy of classifications of remotely sensed data . Remote Sens. Environ. , 37 : 35 – 46 .
   Web of Science ®Google Scholar
• Cybenko , G. 1989 . Approximations by superpositions of a sigmoidal function. . Mathematical Control, Signals, and Systems , 2 : 303 – 314 .
   Google Scholar
• Diner , D.J. , Martonchik , J.V. , Borel , C. , Gerstl , S.A.W. , Gordon , H.R. , Knyazikhin , Y. , Myneni , R. , Pinty , B. and Verstraete , M.M. 1998 . “ MISR: Level 2 surface retrieval algorithm theoretical basis ” . JPL Internal Doc. D‐11401 96 Pasadena : Rev. C., Calif. Inst. of Technol., Jet Propul. Lab. .
   Google Scholar
• Diner , D.J. , Asner , G.P. , Davies , R. , Knyazikhin , Y. , Muller , J.P. , Nolin , A.W. , Pinty , B. , Schaaf , C.B. and Stroeve , J. 1999 . New directions in Earth observing: Scientific application of multi‐angle remote sensing . Bulletin of the American Meteorological Society , 80 : 2209 – 2228 .
   Web of Science ®Google Scholar
• Dennis , J.E. and Schnabel , R.B. 1983 . Numerical Methods for Unconstrained Optimization and Non‐Linear Equations , 378 Englewood Cliffs, New Jersey : Prentice‐Hall .
   Google Scholar
• Fahlmann , S. and Lebiere , C. 1988 . “ The cascade‐correlation learning architecture ” . In Advances in Neural Information Processing Systems 2 , Edited by: Touretzky , D. 524 – 532 . Aan Mateo, California : Morgan Kaufmann . (Chapt. 19)
   Google Scholar
• Fischer , M.M. and Gopal , S. 1994 . Comparative performance comparisons between multilayer feedforward networks and the conventional spatial interaction model . J. Reg. Sc , 34 (4) : 503 – 527 .
   Web of Science ®Google Scholar
• Fletcher , R. 1987 . Practical Methods of Optimization , 436 New York : John Wiley & Sons .
   Google Scholar
• Fourty , T. and Baret , F. 1997 . Vegetation water and dry matter contents estimated from top‐of‐the‐atmosphere reflectance data: a simulation study. . Remote Sens. Environ. , 61 : 34 – 45 .
   Web of Science ®Google Scholar
• Fu , L. 1994 . Neural Networks in Computer Intelligence , 460 New York : McGraw‐Hill .
   Google Scholar
• Gao , F. and Zhu , Q. 1997 . Process System of Measured Bidirectional Reflectance in Changchun Laboratory . Journal of Remote Sensing China , 1 (Suppl.) : 123 – 130 .
   Google Scholar
• Gao , F. , Li , X. , Xia , Z. , Zhu , Q. and Strahler , A.H. 1998 . Knowledge‐based multi‐staged uncertainty inversion for multiangular remotely sensed data . Science in China , 28 : 346 – 350 . (in Chinese)
   Google Scholar
• Gastellu‐Etchegorry , J.P. , Demarez , V. , Pinel , V. and Zagolski , F. 1996 . Modeling radiative transfer in heterogeneous 3D vegetation canopies . Remote Sens. Environ. , 58 : 131 – 156 .
   Web of Science ®Google Scholar
• Gemmell , F. 1998 . An investigation of terrain effects on the inversion of a forest reflectance model . Remote Sens. Environ. , 65 : 155 – 169 .
   Web of Science ®Google Scholar
• Girosi , F. and Poggio , T. 1989 . Representation properties of networks: Kolmogorov's theorem is irrelevant . Neural Computation , 1 : 465 – 469 .
   Web of Science ®Google Scholar
• Gobron , N. , Pinty , B. and Verstraete , M.M. 1997a . “ Presentation and application of an advanced model for the scattering of light by vegetation in the solar domain ” . In Physical Measurements and Signatures in Remote Sensing , Edited by: Guyot , G. and Phulpin , T. 267 – 273 . Rotterdam : Balkema .
   Google Scholar
• Gobron , N. , Pinty , B. and Verstraete , M.M. 1997b . Theoretical limits to the estimation of the leaf area index on the basis of optical remote sensing data . IEEE Trans. Geosci. Remote Sens. , 35 : 1438 – 1445 .
   Web of Science ®Google Scholar
• Goel , N.S. 1988 . Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data . Remote Sens. Rev. , 4 : 1 – 213 .
   Google Scholar
• Goel , N.S. and Strebel , D.E. 1983 . Inversion of vegetation canopy reflectance models for estimating agronomic variables. I. Problem definition and initial results using the Suits’ model . Remote Sens. Environ. , 13 : 487 – 507 .
   Web of Science ®Google Scholar
• Goel , N.S. and Thompson , R.L. 1985 . Optimal solar/viewing geometry for an accurate estimation of leaf area index and leaf angle distribution from bidirectional canopy reflectance data . Int. J. Remote Sens. , 6 : 1493 – 1520 .
   Web of Science ®Google Scholar
• Goel , N.S. and Thompson , R.L. 2000 . A snapshot of canopy reflectance and their use in estimation of biophysical parameters from reflectance data . Remote Sens. Rev. , 18 : 197 – 225 .
   Google Scholar
• Hadamard , J. 1902 . Sur les problems aux derivees partielles et leur significations physiques . Bui. Univ. Princeton , 13 (in France)
   Google Scholar
• Hall , G.G. , Townshend , J.R. and Engman , E.T. 1995 . Status of remote sensing algorthims for estimation of land surface state parameters . Remote Sens. Environ. , 51 : 138 – 156 .
   Web of Science ®Google Scholar
• Hartman , E.J. , Keeler , J.D. and Kowalski , J.M. 1990 . Layered neural networks with Gaussian hidden units as universal approximations . Neural Computation , 2 : 210 – 215 .
   Web of Science ®Google Scholar
• Haykin , S. 1994 . Neural Networks, A Comprehensive Foundation , 696 New York : Macmillan .
   Google Scholar
• Hecht‐Nielsen , R. Theory of backpropagation neural network . Proceedings of International Joint Conference on Neural Networks (IJCNN) ‘89 . Vol. 1 , June . pp. 18 – 22 . Washington D.C. I‐593‐I‐605
   Google Scholar
• Hornik , K. , Stinchcombe , M. and White , H. 1989 . Multi‐layer feed‐forward networks are universal approximators . Neur. Nets. , 2 : 359 – 366 .
   Web of Science ®Google Scholar
• Hornik , K. , Stinchcombe , M. and White , H. 1990 . Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks . Neur. Nets. , 3 : 551 – 560 .
   Web of Science ®Google Scholar
• Irons , J.R. , Ranson , K.J. , Williams , D.L. , Irish , R.R. and Huegel , F.G. 1991 . An off‐nadir pointing imaging spectrometer for terestrial ecosystem studies . IEEE Trans. Geosci. Remote Sens. , 29 : 66 – 74 .
   Web of Science ®Google Scholar
• Jacobs , R.A. 1988 . Increased rates of convergence through learning rate adaptations . Neur. Nets. , 1 : 295 – 307 .
   Web of Science ®Google Scholar
• Jacquemoud , S. and Baret , F. 1990 . PROSPECT: a model of leaf optical properties spectra . Remote Sens. Environ. , 34 : 75 – 91 .
   Web of Science ®Google Scholar
• Kimes , D.S. , Holben , B.N. , Nickeson , J.E. and McKee , A. 1996 . Extracting forest age in a Pacific Northwest Forest from thematic mapper and topographic data . Remote Sens. Environ , 56 : 133 – 140 .
   Web of Science ®Google Scholar
• Kimes , D.S. , Gastellu‐Etchegorry , J. and Esteve , P. 2000 . Recovery of forest canopy characteristics through inversion of a complex 3D model . Remote Sens. Environ , (submitted)
   Web of Science ®Google Scholar
• Kimes , D.S. , Nelson , R.F. , Manry , M.T. and Fung , A.K. 1998 . Atributes of neural networks for extracting continuous vegetation variables from optical and radar measurements . Int. J. Rem. Sens. , 19 : 2639 – 2663 .
   Web of Science ®Google Scholar
• Kimes , D.S. , Ranson , K.J. and Sun , G. 1997 . Inversion of a forest backscatter model using neural networks . Int. J. Rem. Sens. , 18 : 2181 – 2199 .
   Web of Science ®Google Scholar
• Kimes , D.S. , Sellers , P.J. and Diner , D.J. 1987 . Extraction of spectral hemispherical reflectance (albedo) of surfaces from nadir and directional reflectance data . Int. J. Rem. Sens. , 8 : 1727
   Web of Science ®Google Scholar
• Knyazikhin , Y. , Martonchik , J.V. , Myneni , R.B. , Diner , D.J. and Running , S.W. 1998a . Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data. . J. Geophys. Res. , 103 : 32 257 – 32275 .
   Web of Science ®Google Scholar
• Knyazikhin , Y. , Martonchik , J.V. , Diner , D.J. , Myneni , R.B. , Verstraete , M.M. , Pinty , B. and Gobron , N. 1998b . Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere‐corrected MISR data . J. Geophys. Res. , 103 : 32239 – 32256 .
   Web of Science ®Google Scholar
• Knyazikhin , Yu. , Kranigk , J. , Miessen , G. , Panfyorov , O. , Vygodskaya , N. and Gravenhorst , G. 1996 . Modelling three‐dimensional distribution of photosynthetically active radiation in sloping coniferous stands . Biomass and Bioenergy , 2/3 : 189 – 200 .
   Web of Science ®Google Scholar
• Kranigk , J. and Gravenhorst , G. 1993 . Ein dreidimensionales Modell fur Fichtenkronen . Allg. Forst Jagdztg. , 164 (8) : 146 – 149 .
   Google Scholar
• Kranigk , J. , Gruber , F. , Heimann , J. and Thorwest , A. 1994 . Ein Model fur die Kronenraumstruktur und die raumliche Verteilung der Nadeloberflache in einem Fichtenbestand . Allg. Forst Jagdztg. , 165 (10–11) : 193 – 197 .
   Google Scholar
• Kurth , W. 1994 . Morphological models of plant growth: possibilities and ecological relevance . Ecol. Modell. , 75/76 : 299 – 308 .
   Web of Science ®Google Scholar
• Kuusk , A. 1985 . The hot spot effect of a uniform vegetative cover . Sov. J. Remote. Sens. , 3 : 645 – 658 .
   Google Scholar
• Kuusk , A. 1991a . The angular distribution of reflectance and vegetation indices in barley and clover canopies . Remote Sens. Environ. , 37 : 143 – 151 .
   Web of Science ®Google Scholar
• Kuusk , A. 1991b . “ The hot spot effect in plant canopy reflectance ” . In Photo‐Vegetation Interaction, Applications in Optical Remote Sensing and Plant Ecology , Edited by: Myneni , R.B. and Ross , J. 139 – 159 . Berlin : Springer Verlag .
   Google Scholar
• Kuusk , A. 1994 . Multispectral canopy reflectance model . Remote Sens. Environ. , 50 : 75 – 82 .
   Web of Science ®Google Scholar
• Levin , E. , Tishby , N. and Solla , S.A. 1990 . A statistical approach to learning and generalization in layered neural networks . Proc. IEEE , 78 (10) : 1568 – 1574 .
   Web of Science ®Google Scholar
• Li , X. and Strahler , A.H. 1992 . Geometric optical bidirectional reflectance modeling of the discrete crown vegetation canopy: effects of crown shape and mutual shadowing . IEEE Trans. Geosci. Remote Sens. , 30 : 276 – 292 .
   Web of Science ®Google Scholar
• Lippman , R.P. 1987 . An introduction to computing with neural nets . IEEE ASSP Magazine , April : 4 – 22 .
   Google Scholar
• Marshak , A. 1989 . Effect of the hot spot on the transport equation in plant canopies . J. Quant. Agric. For. Meteorol. , 55 : 323 – 344 .
   Google Scholar
• Martonchik , J.V. , Diner , D.J. , Pinty , B. , Verstraete , M.M. , Myneni , R.B. , Knyazikhin , Y. and Gordon , H.R. 1998 . Determination of land and ocean reflective, radiative and biophysical properties using multi‐angle imaging. . IEEE Trans. Geosci. Remote Sens. , 36 : 1266 – 1281 .
   Web of Science ®Google Scholar
• Myneni , R.B. and Ross , J. , eds. 1991 . Photon‐Vegetation Interactions , 565 New York : Springer‐Verlag .
   Google Scholar
• Myneni , R.B. , Ross , J. and Asrar , G. 1989 . A review on the theory of photon transport in leaf canopies . Agricultural Forest Meteorology , 45 : 1 – 53 .
   Web of Science ®Google Scholar
• Myneni , R.B. , Nemani , R.R. and Running , S.W. 1997 . Estimation of global leaf area index and absorbed PAR using radiative transfer model . IEEE Trans. Geosci. Remote Sens. , 35 : 1380 – 1393 .
   Web of Science ®Google Scholar
• Nelder , J.A. and Mead , R. 1965 . A simplex method for function minimization . Computer J. , 7 : 308 – 313 .
   Web of Science ®Google Scholar
• Ni , W. , Li , X. , Woodcock , C.E. , Caetano , M.R. and Strahler , A.H. 1998 . An analytical hybrid GORT model for bidirectional reflectance over discontinuous plant canopies . IEEE Trans. Geosci. Remote Sens. , 37 : 987 – 999 .
   Web of Science ®Google Scholar
• Nilson , T. and Kuusk , A. 1989 . A reflectance model for homogeneous plant canopies and its inversion . Remote Sens. Environ. , 27 : 157 – 167 .
   Web of Science ®Google Scholar
• Numerical Algorithms Group . 1990 . “ The NAG Fortran Library, Mark 14 ” . Vol. 3 , Downers Grove, IL. : NAG Inc. .
   Google Scholar
• Panferov , O. , Knyazikhin , Y. , Myneni , R.B. , Szarzynski , J. , Engwald , S. , Schnitzler , K.G. and Gravenhorst , G. 2000 . The role of canopy structure in the spectral variation of transmission and absorption of solar radiation in vegetation canopies . IEEE Trans. Geosci. Remote Sens , (submitted)
   Web of Science ®Google Scholar
• Pinty , B. , Verstraete , M.M. and Dickinson , R.E. 1989a . A physical model for predicting bidirectional reflectance over bare soils . Remote Sens. Environ. , 27 : 273 – 288 .
   Web of Science ®Google Scholar
• Pinty , B. , Verstraete , M.M. and Dickinson , R.E. 1989b . A physical model of the bidirectional reflectance of vegetation canopies, Part 2: Inversion and validation . J. Geophys. Res. , 95 : 11767 – 11775 .
   Web of Science ®Google Scholar
• Pinty , B. and Verstraete , M.M. 1991 . Extracting information on surface properties from bidirectional reflectance measurements . J. Geophys. Res. , 96 : 2865 – 2874 .
   Web of Science ®Google Scholar
• Press , W.H. , Flannery , B.P. , Teukolsky , S.A. and Vetterling , W.T. 1986 . Numerical Recipes , 274 – 312 . New York : Cambridge University Press .
   Google Scholar
• Privette , J.L. , Deering , D.W. and Wickland , D.E. Report on the workshop on multi‐angular remote sensing for environmental applications . pp. 113202 Washington, DC : NASA Tech. Memo. .
   Google Scholar
• Privette , J.L. , Eck , T.F. and Deering , D.W. 1997b . Estimating spectral albedo and nadir reflectance through inversion of simple BRDF models with AVHRR/MODIS‐like data . J. Geophys. Res. , 102 (D24) : 29529 – 29542 .
   Web of Science ®Google Scholar
• Privette , J.L. , Emery , W.J. and Schimel , D.S. 1996a . Inversion of a vegetation reflectance model with NOAA AVHRR data . Remote Sens. Environ. , 58 (2) : 187 – 200 .
   Web of Science ®Google Scholar
• Privette , J.L. , Myneni , R.B. , Emery , W.J. and Hall , F.G. 1996b . Optimal sampling conditions for estimating grassland parameters via reflectance model inversions . IEEE Trans. Geosci. Remote Sens. , 34 (1) : 272 – 284 .
   Web of Science ®Google Scholar
• Privette , J.L. , Myneni , R.B. , Emery , W.J. and Pinty , B. 1995 . Inversion of a soil bidirectional reflectance model for use with vegetation BRDF models . J. Geophys. Res. , 100 (D12) : 25497 – 25 508 .
   Web of Science ®Google Scholar
• Privette , J.L. , Myneni , R.B. , Tucker , C.J. and Emery , W.J. 1994 . Invertibility of a 1‐D discrete ordinates canopy reflectance model . Remote Sens. Environ. , 48 : 89 – 105 .
   Web of Science ®Google Scholar
• Qin , W. and Liang , S. 2000 . Plane‐parallel canopy radiative transfer modeling: recent advances and future directions . Remote Sens. Rev. , 18 : 281 – 305 .
   Google Scholar
• Reffye , P. , Dinouard , P. and Barthelemy , D. 1991 . “ Modelisation et simulation de l'architecture de l'orme du japon Zelkova Serrata (Thunb.) Makino (Ulmaceae): La notion d'axe de reference ” . In Naturalia Monspeliensia 251 – 266 . Montpellier, , France
   Google Scholar
• Renders , J‐M. , Flasse , S.P. , Verstraete , M.M. and Nordvik , J‐P. 1992 . “ A comparative study of optimization methods for the retrieval of quantitative information from satellite data ” . In Joint Research Center Report EUR 14851 Brussels
   Google Scholar
• Rumelhart , D.E. , Hinton , G.E. and Williams , R.J. 1986a . Learning representations by back‐propagating errors . Nature , 323 : 533 – 536 .
   Web of Science ®Google Scholar
• Rumelhart , D.E. , Hinton , G.E. and Williams , R.J. 1986b . “ Learning internal representations by error propagation ” . In Parallel Distributed Processing. Exploration in the Microstructure of Cognition , Foundations, 1 Edited by: Rumelhart , D.E. and McClelland , J.L. Vol. 1 , 318 – 362 . Cambridge (Mass) and London, , England : The MIT Press . and the PDP research Group
   Google Scholar
• Running , S.W. , Myneni , R.B. , Nemani , R. and Glassy , J. 1996 . “ MOD15 LAI/FPAR algorithm theoretical basis document, MODIS LAI (leaf area index) and MODIS FPAR (fraction of absorbed photosynthetically active radiation) ” . Tech. Rep., Sch. of For. Missoula : Univ. of Mont. .
   Google Scholar
• Sellers , P.J. 1985 . Canopy reflectance, photosynthesis and transpiration . Int. J. Rem. Sens. , 8 : 1335
   Web of Science ®Google Scholar
• Shah , S. , Palmieri , F. and Datum , M. 1992 . Optimal algorithms for fast learning in feedforward neural networks . Neural Nets. , 5 : 779 – 787 .
   Web of Science ®Google Scholar
• Smith , J.A. 1993 . LAI inversion using a back‐propagation neural network trained with a multiple scattering model . IEEE Trans. Geosci. Remote Sens. , 31 : 1102 – 1106 .
   Web of Science ®Google Scholar
• Stamnes , K. 1982 . Reflection and transmission by a vertically inhomogeneous planetary atmosphere . Planet. Space Sci. , 30 : 727 – 732 .
   Web of Science ®Google Scholar
• Tarantola , A. 1987 . Inverse Problem Theory: Methods for Data Fitting and Model Parameter Estimation , New York : Elsevier Science Publishing Company inc. .
   Google Scholar
• Tikhonov , A.N. and Arsenin , V.Y. 1986 . Methods for Solving Ill‐Posed Problems , 288 Moscow : Nauka . (in Russian)
   Google Scholar
• Twomey , S. 1977 . Introduction to the Mathematics of Inversion in Remote Sensing and Indirect Measurements , 243 Amsterdam : Elsevier Sci. Publish. Co. . Reprinted by Dover Publish., Inc.
   Google Scholar
• Verhoef , W. 1984 . Light scattering by leaf layers with application to canopy reflectance modeling: the sail model. . Remote Sens. Environ. , 16 : 125 – 141 .
   Web of Science ®Google Scholar
• Verstraete , M.M. , Pinty , B. and Myneni , R.B. 1996 . Potential and limitations of information extraction on the terrestrial biosphere from satellite remote sensing . Remote Sens. Environ. , 58 : 201 – 214 .
   Web of Science ®Google Scholar
• Wanner , W. , Li , X. and Strahler , A.H. 1995 . On the derivation of kernels for kernel‐driven models of bidirectional reflectance . J. Geophys. Res. , 100 : 21077 – 21090 .
   Web of Science ®Google Scholar
• Weigend , A.S. , Rumelhart , D.E. and Huberman , B.A. Backpropagation, weight elimination and time series prediction . Connectionist Models. Proceedings of the 1990 Summer School . Edited by: Touretzky , D.S. , Elman , J.L. , Sejnowski , T.J. and Hinton , G.E. pp. 105 – 116 . San Mateo, (CA) : Morgan Kaufmann Publishers .
   Google Scholar
• Zhang , Z. , Kalluri , S.N.V. , Jaja , J. , Liang , S. and Townshend , J.R.G. 1998 . Models and high performance algorithms for global BRDF retrieval . IEEE Computational Sci. Engin. , 5 : 16 – 29 .
   Web of Science ®Google Scholar
• Corresponding author.
   Google Scholar