In the context of sustainable development, soil and water resources management is a key issue from not only the environmental point of view, but also from a socioeconomic perspective. Soil moisture, roughness, composition, and slaking crusts are some key variables used to understand and model natural hazards, such as erosion, drought and floods. For agricultural bare soils (most subject to runoff), numerous studies have already shown the potential of C-band RADAR data for the mapping of soil moisture and roughness. However, the application of these methods in operational settings remained limited. In this context, , the first objective of this thesis was to analyse the sensitivity of X-band TerraSAR-X sensors to soil surface characteristics (SSC) at high spatial and temporal resolutions. Different TerraSAR-X configurations were evaluated and results were used to define the optimal instrumental configuration for the characterization of each SSC parameter. The comparison of TerraSAR-X sensor sensitivity with equivalent levels recorded with the C-band sensor showed that the TerraSAR-X sensor is undoubtedly the most suitable of the two when estimating and mapping soil moisture at a fine scale (50 m²). The second objective of this work was to develop a method to estimate and map soil moisture levels of agricultural bare soil. To achieve this goal, methods that are commonly used to retrieve soil moisture from C-band, have been tested on X-band data. The accuracy of soil moisture estimations using an empirical algorithm was determined, and validated successfully over numerous study sites. A mapping process based uniquely on TerraSAR-X data, both for bare soil detection and for the estimation of soil moisture content, was developed. This innovative chain of " automatic and autonomous" mapping processing steps should enable the utilization of TerraSAR-X data for the mapping of soil moisture levels in operational conditions.
