1. Soil moisture estimates over Niger from satellite sensors (T. Pellarin, M. Zribi)

2. Passive sensor at 6, 10, 18, 36, 85 GHz 55 km (regridded to 25 km) 2 polarizations 1 incidence angle 55° Sun-synchroneous orbit (1.30 am 1.30 pm) Measurements since june 2002 AMSR-E onboard the AQUA platform Passive satellite sensors

3. Banizoumbou, Niger (13,54°N ; 2,66°E) Djougou, Benin (9,7°N ; 1,68°E) 2002 2003 2004 2005 2006 TB H TB V AMSR-E raw measurements

4. TB V - TB H TB V + TB H PR = Positive variation of PR during 15 consecutive days 1 july to 15 july 2004 16 july to 31 july 2004 AMSR-E raw measurements Vegetation attenuation

5. Positive variation of PR during 4 consecutive days AMSR-E raw measurements 9 august to 13 august 2004

6. Rain does not reach the soil AMSR-E raw measurements Meteosat MCS Tracking Positive variation of PR during 4 consecutive days Rain seems to stop

7. Soil moisture products

8. ISBA outputs* (1km²) TB (1km²) TB (25x25km²) C-MEB agreggation In-situ soil moisture measurements TB AMSR-E (25x25km²) Modification of the ISBA code Modification of the C-MEB code Measurements Simulations Atmosph. Forcing Land Cover ISBA ISBA outputs* : surface soil moisture, soil temperature, vegetation water content, water interception by the vegetation Objective and methodology Validate high resolution soil moisture maps uing low resolution AMSR TB measurement Look at the within pixel soil moisture variability

9. Surface soil moisture measurements Campbell CS616 Tondikiboro  AMSR-E 25x25 km² reggrided

10. ISBA standard Evaporation Runoff Drainage Surface soil moisture simulations SVAT vs. Campbell CS616 84% 12% 4% 2004

11. ISBA standard + Ksat(crust) = 1E-7 m/s + Ksat(sub-soil) = 5E-5 m/s (Vandervaere et al. 1997, Esteves and Lapetite, 2003) ISBA standard 84% 12% 4% Evaporation Runoff Drainage 71% 29% 0% Surface soil moisture simulations SVAT vs. Campbell CS616 2004

12. Rainrate from raingauges (5x5 km², 5 min.) LAI from Cyclopes (1km², 10 days) Studied area (140x120 km²) Meso scale simulations ISBA (1km²)

13. Simulated TB 1km 55km footprint 55km Meso scale TB simulations ISBA + C-MEB (1km²) C-band Microwave Emission of the Biosphere (Pellarin et al., 2006) Simulated TB 25km-reggrided AMSR-E TB Level 3 25km product

14. Within pixel variability Soil moisture comparison (1km² vs. 25x25 km²)

15. Local scale measurement vs. AMSR-E product

16. Monitoring of surface soil moisture based on ASAR/ENVISAT radar data over Kori Diantandou site (Niger)

17. Active sensor at 6 GHz (C-band) 55 km resolution 2 polarizations n incidence angles (18 to 59°) Sun-synchroneous orbit (10.30 am 11.00 pm) Measurements since 1991 ASAR onboard the ENVISAT platform Scatterometer and SAR onboard the ERS platform Active satellite sensors Active sensor at 6 GHz (C-band) 30m resolution 2 polarizations n incidence angles (18 to 59°) Sun-synchroneous orbit Measurements since 2002

18. Site

19. Soil moisture estimation in Western Africa (A new approach based on ERS/WSC)

20. dry season radar imageRadar images SPOT/HRVDTM * Registration * incidence angle correction of images NDVI and NDWI mapping Mask of high NDVI (NDVI>0.25) Mask of high slopes (m>3%) global mask A mean radar signal estimation on 100 X 100 pixels (out of the mask) More than 20% of pixels must be out of the mask  =  1 *Mv 1 +c 1  VV=  2 *Mv 2 +c 2 Mask of pools Mv=(Mv 1 +Mv 2 )/2 Elimination of roughness effect using dry season image

21. Satellite measurements ASAR-ENVISAT, SPOT Ground truth measurements Soil moisture (IRD, L. Descroix) Dantiandou site

22. Datesample spacing size PolarisationsAngleOrbital path 17-02-200412.5m X 12.5 mHH/VVIS1descending 05-08-200412.5m X 12.5 mHH/VVIS1ascending 30-08-200412.5m X 12.5 mHH/VVIS1descending 09-09-200412.5m X 12.5 mHH/VVIS1ascending 14-09-200412.5m X 12.5 mHH/VVIS1descending 01-02-200512.5m X 12.5 mHH/VVIS1descending 15-02-200512.5m X 12.5 mHH/VVIS2ascending 05-07-200512.5m X 12.5 mHH/VVIS1ascending 07-07-200512.5m X 12.5 mHH/VVIS2descending 21-07-200512.5m X 12.5 mHH/VVIS1ascending 26-07-200512.5m X 12.5 mHH/VVIS1descending 09-08-200512.5m X 12.5 mHH/VVIS2ascending 11-08-200512.5m X 12.5 mHH/VVIS2descending 30-08-200512.5m X 12.5 mHH/VVIS1descending 15-09-200512.5m X 12.5 mHH/VVIS2descending Radar images details

23. Land surface

24. Vegetation cover dynamic

25. pool and relief identification

26. Incidence angle correction, IS1, IS2 data Is1: incidence angle ranged between 15 and 22° Is2: incidence angle ranged between 19 and 26°

27. Results, application of the algorithm, HH, VV data High correlation between radar data and soil moisture High coherence between IS1 and IS2 normalised data

28. Validation of inversion approach Application of inversion empirical approach over different test sites

29. Mapping of soil moisture Figure 9. Estimated soil maps of the Kori Dantiandou region, generated from ASAR data and our soil moisture algorithm on four different dates: (a) 6 July 2004; (b) 14 September 2004; (c) 11 August 2005; (d) 30 August 2005. a b c d

30. Conclusions Considered data: IS1, IS2 Normalisation of radar data to one incidence angle Estimation of radar signal over bare soil and low vegetation cover An empirical linear relationship is established between moisture and processed radar signal A mapping of soil moisture is proposed in 15 dates in 2004 and 2005

31. Surface soil moisture AMSR-E product, 20060802