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Correction of bidirectionnal effects and impact on land cover classifications. J-L. CHAMPEAUX METEO-FRANCE S. GARRIGUES METEO-FRANCE C. GOUVEIA ICAT, Universidade de Lisboa, Lisbon, Portugal EST, Instituto Politécnico de Setubal, Portugal P. BICHERON SCOT, Toulouse, France.
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Correction of bidirectionnal effects and impact on land cover classifications J-L. CHAMPEAUX METEO-FRANCE S. GARRIGUES METEO-FRANCE C. GOUVEIA ICAT, Universidade de Lisboa, Lisbon, Portugal EST, Instituto Politécnico de Setubal, Portugal P. BICHERON SCOT, Toulouse, France GLC 2000 – “FIRST RESULTS” WORKSHOP JRC – Ispra, 18-22 March 2002
The usual strategy for directional correction: A 3 STEPS APPROACH NORMALISE the DATA qso; qvo=NADIR COLLECT RELIABLE CLOUD-FREE DATA FIT THE BRDF MODEL Roujean et al. (1992): MOD(s, v, ) =k0 +k1 f1 (s, v, ) + k2 f2 (s, v, ) Cloud mask For S Products?
COLLECT THE N LAST CLOUD-FREE DATA FIT THE BRDF MODEL USE THE ADJUSTED BRDF TO NORMALISE THE CLEAR REFLECTANCES OF THE LAST 10 DAYS THE BIDIRECTIONAL COMPOSITING (BDC)P. MAISONGRANDE, B. DUCHEMIN, CESBIO MAIN IDEA : COLLECT A CONSTANT NUMBER OF DATA TO FIT THE BRDF, REGARDLESS TO THE DATE OF ACQUISITION AVERAGE OF THESE REFLECTANCES
The BDC approach was applied here but S1 products are not optimal : - reduced data number and angular sampling - no possibility to track aerosol loading - cloud mask is not satisfactory SCOT CLOUD MASK: A pixel is cloudy if: B0(j) > 0.2 and B0(j) > 6* B0 Clim (month) And B0(j) > B2(j) METEO-France CLOUD MASK: A pixel is cloudy if: B0(j) > 0.11 And SWIR(j) > 0.09
I IMPORTANCE OF CLOUD DETECTION BDC NDVI (SCOT mask) BDC NDVI (Meteo-France mask)
Plot of 10-days NDVI profiles: MVC (red) , BDC (green)
10-days NDVI profiles for several methods MVC, BDC, Roujean model, daily data Blue: Roujean model Green:Roujean model Red: MVC Black: BDC
CONCLUSION • The cloud mask is crucial • for use in kernel-driven BRDF models • (corrupted data distort the adjustment of • the regression) • After bidirectional corrections, • NDVI profiles are noisy mainly in cloudy regions • (due to the too small number of points used for the regression) • At this stage of the study, the landcover classifications made with data corrected from the bidirectionnal effects • do not improve the final results