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Validation of CYCLOPES, MODIS & MERIS PRODUCTS

Validation of CYCLOPES, MODIS & MERIS PRODUCTS. M. Weiss, F. Baret, K. Pavageau, P. Bicheron, M. Huc, D. Béal, W.Wang. Error quantification (rms). Few points Bad repartition in space Bad repartition in time. Good repartition in space (BELMANIP) Temporal monitoring

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Validation of CYCLOPES, MODIS & MERIS PRODUCTS

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  1. Validation of CYCLOPES, MODIS & MERIS PRODUCTS M. Weiss, F. Baret, K. Pavageau, P. Bicheron, M. Huc, D. Béal, W.Wang NOV-3300-SL-2858

  2. Error quantification (rms) • Few points • Bad repartition in space • Bad repartition in time • Good repartition in space • (BELMANIP) • Temporal monitoring • (Weekly or decadal data) No error quantification Objectives= to validate LAI, fAPAR, fCover • Consistency between products (relative validation) ? • Consistency with ground truth (absolute validation) ? Relative validation Inter-comparison Absolute Validation Use the two ways to get « the best evaluation » NOV-3300-SL-2858

  3. Problems associated with inter-comparison • Product definition (effective LAI or true LAI, instantaneous fAPAR at satellite overpass….) • Temporal composition : CYCLOPES = decade, MODIS= week • The « Footprint » : the size of the two objects must be the same • Geo-location : same geographic position (cartographic projection, sensor geo-location error, GPS measurement error,…) • Sensor PSF : the measured signal for a given pixel correspond to the pixel itself + its environment Attenuating PSF + Geo location effect: Site size = 3kmx3km Footprint: CYCLOPES = UTM, WGS84 MERIS = lat/lon WGS84 NOV-3300-SL-2858

  4. MERIS & CYCLOPES product definition • LAI = effective LAI • fAPAR = instantaneous fAPAR at 10h00 NOV-3300-SL-2858

  5. CYCLOPES PROJECT • Final objectives: provide LAI, fAPAR, fCover products derived from the fusion of AVHRR, VGT, POLDER data from 1997 to 2003 (2 spatial resolution: 1km – 8km) • Up to now: 2 versions available • Version 1 = VGT data derived from already existing processing chains. BRDF normalization using Roujean’s model, use relationships between Roujean’s coefficients and biophysical variables • Version 2 = algorithm based on neural nets calibrated on radiative transfer simulations using normalized TOC nadir reflectances (for LAI: + fAPAR as input) NOV-3300-SL-2858

  6. MERIS PRODUCT DESCRIPTION • Same philosophy (neural nets calibrated on radiative transfer simulations) except that • Inputs are Top of Atmosphere reflectances + pressure + view & satellite angles • No normalization: one LAI, fAPAR, fCover estimated at each date • Up to now, no cloud filtering is applied to the data. Application of a manual filtering + smoothing using gaussian filtering NOV-3300-SL-2858

  7. Relationship used for Intercomparison with MERIS MODIS Product description • LAI (sinusoidal projection) = collection 4 downloaded from EOS data gateway • fAPAR (sinusoidal projection) = The fAPAR MODIS standard product (collection 4) re-processed by BU • Use of the MODIS re-projection tool (nearest neighbor resampling because of flags) to provide the products in : • UTM/WGS84 (comparison with CYCLOPES) • Plate Carrée (Lat/lon WGS84) (comparison with MERIS) NOV-3300-SL-2858

  8. Turco, Bolivia Barrax, Spain Concepcion, Chile Fundulea, Romania Haouz, Morocco Larose, Canada Hirsikangas,Finland The used sites • VALERI sites in 2003: • Additional sites in 2003 AERONET+ VALERI (other years) • AERONET: Banizoumbou, Bordeaux, Jabiru, Ouagadougou, Moldova, Fontainebleau • VALERI : - Grasslands: Laprida, ZhangBei, Larzac • - Shrublands: Gourma • - Croplands :Avignon_Alpilles, Sud-Ouest, Romilly, Gilching • - Forests :Counami, SierraCincua,AekLoba, Puechabon NOV-3300-SL-2858

  9. LAI-fAPAR relationships • - MGVI-LAI bad relationship • Bad results for CYCLOPES V1 for low canopies • Low scattering for CYCLOPES V2 • -LAI higher for MODIS than other products NOV-3300-SL-2858

  10. LAI,fAPAR cumulated distribution • Good consistency for fAPAR • Differences for low LAI & high LAIs NOV-3300-SL-2858

  11. Comparison with CYCLOPES products (interpolation of MODIS data at CYCLOPES dates) – UTM/WGS84 projection. Europe & Africa sites Comparison with MERIS products (interpolation at MERIS dates) – lat/lon on WGS84. All sites Comparison between products fAPAR: Good consistency between CYCLOPES V2/MODIS, MODIS/MERIS LAI : more scattering. Higher LAI for CYC ENF, higher LAI for MOD DBF HIGH values for MOD crops NOV-3300-SL-2858

  12. Comparison with VALERI maps CYC_V1 CYC_V2 fAPAR: Maybe problems with CAN-EYE when understorey LAI : MERIS underestimates ENF although MODIS overestimates NOV-3300-SL-2858

  13. Temporal evolution for some VALERI sites NOV-3300-SL-2858

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  20. Conclusions • Encouraging results, especially for fAPAR (computation of fAPAR in VALERI when understorey?) • More inter-comparison (BELMANIP) & validation (temporal monitoring of validation sites) are required to better understand the weaknesses of the different algorithms NOV-3300-SL-2858

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