Potentiel des données SAR TerraSAR-X pour la caractérisation des paramètres de surface du sol

International audienceThis study investigates the sensitivity to soil surface characteristics of the new SAR: TerraSAR-X. Investigations on the relationship between SAR in X-band and surface soil parameters (soil moisture and surface roughness) are rare. The few papers found in the literature were based on scatterometer measurements (Ulaby et al., 1986), airborne SAR observations (Hajnsek et al., 2003; Baghdadi et al., 2007), and on modelled backscattering coefficient (Autret et al., 1989). The objective of this paper: realize a preliminary diagnostic on the potential of spatial SAR in X-band for the characterization of soil surface

Analysis of surface and root-zone soil moisture dynamics with ERS scatterometer and the hydrometeorological model SAFRAN-ISBA-MODCOU at Grand Morin watershed (France)

International audienceSpatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport and vegetation productivity. Its characterization, offers an avenue to improve our understanding of complex land surface-atmosphere interactions. In this paper, soil moisture dynamics at soil surface (first centimeters) and root-zone (up to 1.5 m depth) are investigated at three spatial scales: local scale (field measurements), 8×8 km2 (hydrological model) and 25×25 km2 scale (ERS scatterometer) in a French watershed. This study points out the quality of surface and root-zone soil moisture data for SIM model and ERS scatterometer for a three year period. Surface soil moisture is highly variable because is more influenced by atmospheric conditions (rain, wind and solar radiation), and presents RMSE up to 0.08 m3 m−3. On the other hand, root-zone moisture presents lower variability with small RMSE (between 0.02 and 0.06 m3 m−3). These results will contribute to satellite and model verification of moisture, but also to better application of radar data for data assimilation in future

Relationship between soil moisture and vegetation in the Kairouan plain region of Tunisia using low spatial resolution satellite data

The present paper proposes an empirical approach for the modeling of vegetation development, using moisture measurements only. The study is based simply on the use of two databases: one containing soil moisture products derived from ERS scatterometer data over the period 1991-2006 and the other containing normalized difference vegetation indices (NDVI) derived from advanced very high resolution radiometer over the period 1991-2000. The study is applied over the Kairouan plain, the central semiarid region of Tunisia (North Africa). Soil moisture products were first validated on the basis of comparisons with Global Soil Wetness Project, Phase 2 Data, outputs and rainfall events. The soil moisture distribution during the rainy period between October and May is described and is found to be correlated with the vegetation dynamics estimated using the NDVI products. Finally, a semiempirical model is proposed, based on satellite moisture and NDVI products, which allows the NDVI value to be estimated for a period of 1 month during the rainy season as a function of the moisture profile estimations obtained during the previous months. This approach could prove very useful and provide a simple tool for the modeling of vegetation dynamics during rainy seasons in semiarid regions