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From local measurements to high spatial resolution VALERI maps

From local measurements to high spatial resolution VALERI maps. M. Weiss, F. Baret D. Allard, S. Garrigues. SPOT Image. Map LAI, fCover, fAPAR (Medium Resolution). Transfer Function (TF). Level 1 Map LAI, fCover, fAPAR (High Resolution). Block Kriging. Level 2 Map

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From local measurements to high spatial resolution VALERI maps

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  1. From local measurements to high spatial resolution VALERI maps M. Weiss, F. Baret D. Allard, S. Garrigues NOV-3300-SL-2857

  2. SPOT Image Map LAI, fCover, fAPAR (Medium Resolution) Transfer Function (TF) Level 1 Map LAI, fCover, fAPAR (High Resolution) Block Kriging Level 2 Map LAI, fCover, fAPAR + Flag (High Resolution) Co-Kriging HP LAI2000 GPS OVERVIEW OF THE VALERI METHODOLOGY NOV-3300-SL-2858

  3. Spatial sampling of the Measurements • Objectives = • set the minimum number of ESUs at the optimal location to provide robust relationships between LAI and high resolution spatial images • Get a good description of the geostatistics over the site • In practice = • Sample in proportion all cover types & variability inside • Spread spatially equal within 1km² for variogram computation • Not too close to a landscape boundary • Sometimes difficulty to access the fields • Manpower must be reasonable =3 to 5 ESU per 1km²(  0.18% of the site) => Need to evaluate the sampling afterwards NOV-3300-SL-2858

  4. Evaluation of the spatial sampling (1) •  30 to 50 ESUs to compare with 22500 SPOT pixels Comparing directly the two NDVI histograms is not statistically consistent • Monte-Carlo procedure to compare the actual cumulative ESU NDVI frequency with randomly shifted sampling pattern 1 – Computing the NDVI cumulative frequency of the 50 exact ESU location 2 – Applying a unique random translation to the sampling pattern 3 – Computing the NDVI cumulative frequency of the shifted pattern 4 – Repeating steps 2 and 3, 199 times with 199 random translation vectors NOV-3300-SL-2858

  5. Evaluation of the spatial sampling (2) • Statistical test on the population of 199+1 cumulative frequencies For a given NDVI level, if the actual ESU density function is between the 5 highest and 5 lowest frequency value, the hypothesis that ESUs and whole site NDVI distributions are equivalent. NOV-3300-SL-2858

  6. Evaluation of the spatial sampling (3) • SPOT image classification & comparison of SPOT/ESU distributions NOV-3300-SL-2858

  7. Evaluation of the spatial sampling (4) • The convex-hull criterium • Strict convex-hull summits = ESU reflectance values in each band • Large convex-hull summits = ESU reflectance values in each band ± 5%relative • Pixels inside the convex-hull: • transfer function used as an interpolator • Pixels outside the convex-hull • Transfer function used as an extrapolator NOV-3300-SL-2858

  8. Evaluation of the spatial sampling (5) 2 bands 3 bands 4 bands TURCO 2003 Red = interpolation Dark & light blue = strict & large convex-hull NOV-3300-SL-2858

  9. Determination of the transfer function (1) • Preliminary analysis of the data Larose, 2003 Haouz, 2003 Robust regression /LUT Robust Regression /LUT Averaging NOV-3300-SL-2858

  10. Determination of the transfer function • Test of 2 methods • Use of robust regression • iteratively re-weighted least squares algorithm (weights computed at each iteration by applying bisquare function to the residuals). • Results less sensitive to outliers than ordinary least squares regression. • Use of LUT composed of the ESU values • LUT with nbESU elements (3,4 reflectances + measured LAI) • Cost Function: • Estimated LAI = Average value over x data minimizing the cost function • Choice of the best band combination by taking into account 3 errors: • Weighted RMSE • RMSE • Cross-validation RMSE NOV-3300-SL-2858

  11. Determination of the transfer function NOV-3300-SL-2858

  12. Collocated kriging (1) LAIreg = LAI issued from transfer function LAI(xa) = LAI measured at ESU a Minimisation of the estimation variance:(s2=f(gLAI, LAI , gLAI, LAIreg , gLAIreg, LAIreg ) ) Swa + d = 1 NOV-3300-SL-2858

  13. Collocated kriging (2) • Ordinary Kriging • Few measurements • No actual spatialisation • Collocated Kriging • High influence of HR image • Require linear LAI-r • Highly decreases the estimation variance Romilly 2000 NOV-3300-SL-2858

  14. Conclusions: data base status • The spatial sampling & associated methodology are quite well established • Level 0 : averaging the ESU values • Level 1 : provide HR LAI maps from transfer function • Level 2 : provide HR LAI maps from collocated kriging • Level 0.5: LAI maps derived from SPOT image classification • For some very homogeneous sites, only level 0.5 Year 2000 & 2003 completed Years 2001 & 2002 partially completed Year 2004 not investigated Aek Loba 2001 Counami 2001,2002 NOV-3300-SL-2858

  15. Many thanks for all your contributions & May the force be with you NOV-3300-SL-2858

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