Soil moisture is an important variable in the hydrological and meteorological cycle of the earth. It can have profound impacts on the planet-s climate system and also influences processes such as flooding and runoff generation or drought developments. Hence, the knowledge of the distri- bution and amount of water in the soil is of great interest for many applications. The Remote Sensing Research Group at TU Wien developed a method to retrieve soil moisture from backscatter measurements obtained from active microwave sensors. This method was ini- tially developed for scatterometer data, but was then also adapted for the Advanced Synthetic Aperture Radar (ASAR) on board of the Envisat satellite. In 2014, the first of two Sentinel-1 satellites was launched into its orbit, carrying a synthetic aperture radar (SAR) that is similar to the ASAR instrument. Consequently, a transfer of the ASAR soil moisture algorithm to Sentinel-1 was expected to be straight forward. The aim of this thesis is to investigate if the ASAR soil moisture algorithm can be transferred to Sentinel-1 using retrieval parameters calculated from ASAR Wide Swath (WS) data. Due to the lack of historical data, it is not yet feasible to derive the model parameters that are needed in the retrieval from Sentinel-1 data itself. Therefore the Sentinel-1 surface soil moisture (SSM) was calculated with ASAR WS parameters and compared to the ASAR SSM products using coarse spatial resolution soil moisture acquisitions from the Advanced Scatterometer (ASCAT) and from the Global Land and Data Assimilation System (GLDAS). The evaluation of the different products was performed over central Europe by calculation standard performance metrics, i.e. the temporal correlation and the root mean square difference (RMSD) of the SSM time series. Furthermore, the correlation and the RMSD were determined for different land cover types. The results show a better correlation and RMSD performance for ASAR WS than for Sentinel- 1, which can be explained with the smaller sample size and shorter period of Sentinel-1 data- set. Furthermore, if one wants to realise the full potential of Sentinel-1 for soil moisture re- trieval, then (i) an adaptation of the model and (ii) the calibration of the model parameters with Sentinel-1 data should be considered.