Earth Observation data give high potential to assess the biomass of vegetation. Initially, methods of deriving information on vegetation growth conditions and biomass were based on optical data, collected by environmental satellites with sensors of different resolutions (low and high-resolution satellite images). However due to frequent clouds cover, the application of multi-temporal SAR data proved to be very useful for classification of vegetation and application for biomass assessment. The presented paper gives an overview of the state-of-the art in the field of radar applications for vegetation studies with the special emphasis put to evaluation of biomass. Applications of different types of SAR sensors are presented for two types of vegetation relevant for biomass production: agricultural crops and forests. As far as forests are concerned, multiple approaches are presented, which apply various radar wavelengths (C-band, L-band, P-band) and different wave polarizations (VV, HH, HV). Results from regression analyses with forest variables: biomass, height, dbh (diameter-breast-height) and total stem number were demonstrated with conclusions concerning optimal choice of radar band and polarization for assessment of these variables with high accuracy. Usefulness of various radar techniques was tested, like PPD (Polarization Phased Difference), or semi-empirical algorithms based on a two layer radar backscatter model. Also applicability of special indices, useful for better assessment of forest biomass, like BCI (Biomass Consolidation Index), which is the combination of biomass density (t/ha) and stand consolidation (amount of trees per ha), was presented. Analogous analysis of recent achievements was done for SAR applications related to agricultural crops. Conclusions concerning optimal SAR wavelengths and polarizations for crop type mapping were presented, including own Author's experience in crop classification based on various SAR sensors (X and L bands). Results concerning interactions of a backscatter signal with soil and vegetation were demonstrated, with their implications on accuracy of biomass assessment. Methods incorporating multi-frequency polarimetric SAR into the crop canopy models aimed at obtaining physical parameters related to biomass, as Leaf Area Index and crop height, were discussed. Finally, the summary table, presenting possibilities of applications and ordering data from different sensors (past and present), wavelengths, polarizations, spatial resolutions for assessment of various vegetation parameters, with the special emphasis put to biomass, was created as a result of the study.