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

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

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

Banizoumbou, Niger (13,54°N ; 2,66°E) Djougou, Benin (9,7°N ; 1,68°E) TB H TB V AMSR-E raw measurements

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

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

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

Soil moisture products

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

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

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

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 CS

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

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

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

Local scale measurement vs. AMSR-E product

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

Active sensor at 6 GHz (C-band) 55 km resolution 2 polarizations n incidence angles (18 to 59°) Sun-synchroneous orbit (10.30 am 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

Site

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

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

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

Datesample spacing size PolarisationsAngleOrbital path m X 12.5 mHH/VVIS1descending m X 12.5 mHH/VVIS1ascending m X 12.5 mHH/VVIS1descending m X 12.5 mHH/VVIS1ascending m X 12.5 mHH/VVIS1descending m X 12.5 mHH/VVIS1descending m X 12.5 mHH/VVIS2ascending m X 12.5 mHH/VVIS1ascending m X 12.5 mHH/VVIS2descending m X 12.5 mHH/VVIS1ascending m X 12.5 mHH/VVIS1descending m X 12.5 mHH/VVIS2ascending m X 12.5 mHH/VVIS2descending m X 12.5 mHH/VVIS1descending m X 12.5 mHH/VVIS2descending Radar images details

Land surface

Vegetation cover dynamic

pool and relief identification

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

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

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

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 a b c d

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

Surface soil moisture AMSR-E product,