Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data

L'objectif de cette etude etait d'evaluer l'interet des donnees de teledetection pour l'estimation des variables biophysiques des couverts vegetaux. Les donnees considerees etaient acquises au niveau du couvert dans plusieurs directions, pour differentes longueurs d'onde du domaine du visible et du proche infrarouge. Les variables estimees etaient l'indice foliaire, le contenu en chlorophylle des feuilles, la fraction de rayonnement photosynthetiquement actif absorbe par le couvert, et le pourcentage de couverture du sol. Une technique simple d'inversion de donnees basee sur des tables de correspondance a ete utilisee. Dans un premier temps, la taille de la table et le nombre d'elements selectionnes pour obtenir une distribution de la solution ont ete determines. Les performances d'estimation des variables en termes de distributions et de co-distributions des solutions ont ete evaluees dans le cas le plus simple en utilisant les reflectances rouge et proche infrarouge au nadir. L'echantillonnage spectral et directionnel optimal correspondant a la meilleure precision d'estimation de chaque variable consideree a egalement ete determine. Enfin, les effets de l'heterogeneite spatiale, des hypotheses du modele de transfert radiatif utilise pour generer la table de correspondance, ainsi que du bruit radiometrique, sur l'estimation des variables ont ete quantifies. Ces resultats sont discutes en vue de la definition des caracteristiques des capteurs a venir pour obtenir des estimations precises des caracteristiques des couverts vegetaux.

[1]  Richard L. Thompson,et al.  Inversion of vegetation canopy reflectance models for estimating agronomic variables. V. Estimation of leaf area index and average leaf angle using measured canopy reflectances , 1984 .

[2]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model , 1984 .

[3]  W. Verhoef.  Earth observation modelling based on layer scattering matrices , 1984 .

[4]  G. Asrar,et al.  Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .

[5]  Richard L. Thompson,et al.  Inversion of vegetation canopy reflectance models for estimating agronomic variables. II. Use of angle transforms and error analysis as illustrated by suits' model , 1984 .

[6]  N. Goel,et al.  Evaluation of a Canopy Reflectance Model for LAI Estimation through Its Inversion , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[7]  W. Verhoef,et al.  Comparative study of suits and sail canopy reflectance models , 1985 .

[8]  G. Campbell.  Extinction coefficients for radiation in plant canopies calculated using an ellipsoidal inclination angle distribution , 1986 .

[9]  J. C. Price.  On the information content of soil reflectance spectra , 1990 .

[10]  F. Baret,et al.  PROSPECT: A model of leaf optical properties spectra , 1990 .

[11]  J. Lagouarde,et al.  The assessment of regional crop water conditions from meteorological satellite thermal infrared data , 1991 .

[12]  A. Kuusk.  The Hot Spot Effect in Plant Canopy Reflectance , 1991 .

[13]  F. Baret,et al.  Potentials and limits of vegetation indices for LAI and APAR assessment , 1991 .

[14]  A. Kuusk,et al.  The Inversion of the Nilson-Kuusk Canopy Reflectance Model, a Test Case , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.

[15]  F. T. Turner,et al.  Chlorophyll Meter to Predict Nitrogen Topdress Requirement for Semidwarf Rice , 1991 .

[16]  C. L. Wiegand,et al.  Accuracy and sensitivity analyses of SAIL model-predicted reflectance of maize , 1992 .

[17]  G. Guyot,et al.  Estimating surface soil moisture and leaf area index of a wheat canopy using a dual-frequency (C and X bands) scatterometer , 1993 .

[18]  S. Jacquemoud.  Inversion of the PROSPECT + SAIL Canopy Reflectance Model from AVIRIS Equivalent Spectra: Theoretical Study , 1993 .

[19]  Gérard Dedieu,et al.  Methodology for the estimation of terrestrial net primary production from remotely sensed data , 1994 .

[20]  C. Tucker,et al.  Invertibility of a 1-D discrete ordinates canopy reflectance model , 1994 .

[21]  R. Myneni,et al.  On the relationship between FAPAR and NDVI , 1994 .

[22]  N. Bruguier,et al.  A simple algorithm to retrieve soil moisture and vegetation biomass using passive microwave measurements over crop fields , 1995 .

[23]  J. Roujean,et al.  Estimating PAR absorbed by vegetation from bidirectional reflectance measurements , 1995 .

[24]  J. Clevers,et al.  The robustness of canopy gap fraction estimates from red and near-infrared reflectances: A comparison of approaches , 1995 .

[25]  Wenhan Qin,et al.  An evaluation of hotspot models for vegetation canopies , 1995 .

[26]  F. Baret,et al.  Leaf optical properties with explicit description of its biochemical composition: Direct and inverse problems , 1996 .

[27]  Charles L. Walthall,et al.  Evidence of hot spot directional signature from airborne POLDER measurements , 1997, IEEE Trans. Geosci. Remote. Sens..

[28]  Ranga B. Myneni,et al.  Estimation of global leaf area index and absorbed par using radiative transfer models , 1997, IEEE Trans. Geosci. Remote. Sens..

[29]  M. Steven,et al.  Evaluation of an improved version of SAIL model for simulating bidirectional reflectance of sugar beet canopies , 1997 .

[30]  S. Running,et al.  Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active , 1998 .

[31]  Bruno Andrieu,et al.  The nested radiosity model for the distribution of light within plant canopies , 1998 .

[32]  D. Diner,et al.  Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere‐corrected MISR data , 1998 .

[33]  F. Baret,et al.  A dynamic model of maize 3D architecture: application to the parameterisation of the clumpiness of the canopy , 1998 .

[34]  Michael T. Manry,et al.  Attributes of neural networks for extracting continuous vegetation variables from optical and radar , 1998 .

[35]  W. Lucht.  Expected retrieval accuracies of bidirectional reflectance and albedo from EOS-MODIS and MISR angular sampling , 1998 .

[36]  J. C. Price,et al.  An Approach for Analysis of Reflectance Spectra , 1998 .

[37]  G. Asner.  Biophysical and Biochemical Sources of Variability in Canopy Reflectance , 1998 .

[38]  P. Bicheron.  A Method of Biophysical Parameter Retrieval at Global Scale by Inversion of a Vegetation Reflectance Model , 1999 .

[39]  F. Baret,et al.  Comparison of three radiative transfer model inversion techniques to estimate canopy biophysical variables from remote sensing data , 1999, IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293).

[40]  F. Baret,et al.  Evaluation of Canopy Biophysical Variable Retrieval Performances from the Accumulation of Large Swath Satellite Data , 1999 .