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It is important to monitor vegetation such as forests in order to understand the impacts of global climate change on terrestrial ecosystems and agriculture crops to ensure food security to the people and livestock. Remote sensing data such as polarimetric SAR data plays a useful role in estimating total vegetation cover and biomass. In this study, a radar vegetation index (RVI) were used to separate vegetation from non-vegetated area and the same were used along with SAR backscatter values at different polarizations in C - and L-band to estimate above-ground biomass of a tropical forest. Models based on multi-frequency SAR data including X -, C - and L-band were developed to improve the estimation of forest biomass. Also, the study of agricultural crops using C - and L-band SAR data at different polarization modes revealed that C-band produced better classification results than L-band. However, L-band showed better correlation with crop growth variables. Further, full polarimetric data was found to be better than various modes of hybrid polarimetric data for crop studies.