## 1 Introduction  
In agriculture areas, information on soil and vegetation conditions is key for water and crop management. The use of _in situ_ sensors to measure soil and vegetation parameters is not effective, especially over large areas, due to the punctual information provided by these measurements. Space-borne remote sensing is a useful tool for mapping vegetation and soil parameters due to its capacity to provide continuous coverage over large areas at various spatial and temporal resolutions. The information extracted from optical data is sometimes incomplete due to clouds. Sensors with spectral bands in the microwave range allow for the acquisition of images in all types of weather. Thus, SAR (Synthetic Aperture Radar) sensors are useful additional remote sensing data sources for applications such as crop and water management. Over the last decade, SAR sensors have been launched to meet the increasing spatial data needs of the scientific and user communities. These SAR sensors have very high spatial resolution (1 m) and short revisit intervals (daily). Given their high spatial and temporal resolutions, TerraSAR-X (TSX) and COSMO-SkyMed (CSK) provided new opportunities for the operational monitoring of biophysical soil and vegetation parameters. The German radar satellite TerraSAR-X (TSX) was launched in June 2007 for commercial and scientific applications. It carries a high frequency X-band SAR sensor (9.65 GHz) that can be operated in different imaging modes [1]. In Spotlight imaging mode, a spatial resolution of up to 1 m can be achieved. The Stripmap mode (SM) allows for acquisitions with up to 3 m resolution. In the ScanSAR mode, a spatial resolution of up to 18 m is achieved. Imaging is possible in single polarization, dual-polarization (HH, VV, HH/VV, HH/HV, or VV/VH), or quad-polarization (HH, VV, HV, VH), and the nominal revisit period is 11 days. The absolute and relative radiometric accuracies, determined during the commissioning phase of TerraSAR-X and confirmed by the recalibration campaigns, are 0.6 dB and 0.3 dB, respectively [1,2]. The second X-band SAR system is the COSMOSkyMed (CSK) constellation (9.6 GHz), developed in cooperation between the Italian Space Agency (ASI) and the Italian Defense Ministry. It is composed of four radar satellites (CSK1, CSK2, CSK3, CSK4). The first satellite in the constellation was launched in June 2007; the fourth satellite was launched in November 2010. The CSK SAR has the following three imaging modes [3]: Spotlight, Stripmap, and Scansar. Spotlight mode allows for images with spatial resolutions equal to 1 m (HH or VV). The Stripmap Himage (HI) and Pingpong (PP) modes provide spatial resolutions between 3 m (HH, HV, VH or VV) and 15 m (HH/VV, HH/HV, or VV/VH). Finally, the Scansar modes achieve medium (30 m) to coarse (100 m) spatial resolution (one polarization is selectable among HH, HV, VH and VV). The CSK can operate with right- and left-looking imaging capabilities and a revisit time of few hours (less than 12 h). For CSK, a radiometric accuracy better than 1 dB and a radiometric stability better than 0.5 dB are expected [4]. Monitoring the spatio-temporal variations in vegetation biophysical parameters and soil moisture is key information for irrigation and crop management at both the farm level and the irrigation network level. Optical data in the visible and infrared spectral range have shown great potential for the mapping and characterization of vegetation biophysical parameters such as the Leaf Area Index (LAI) [5, 6, 7, 8, 9, 10, 11], biomass, height, and the Vegetation Water Content (VWC) [12]. Several studies used the Normalized Difference Vegetation Index (NDVI) to estimate the LAI of different crop types (such as wheat, grassland, rice, orchard, corn, and maize) or more complex models based on radiative transfer models combined with neural networks [13, 14, 15]. In addition, several studies have used the NDVI to estimate grassland biomass and height [16, 17, 18, 19].