We validated a canopy backscatter model for loblolly pine forest stands at the Duke Forest, North Carolina, by comparing the observed and modelled SAR backscatter from the stands. Given the SAR backscatter data calibration uncertainty, the model made good predictions of C-HH, C-HV, L-HH, L-HV, L-VV, P-HH, and P-HV backscatter for most of 25 stands studied. The model overestimated C-VV backscatter for several stands, and largely overestimated P-VV backscatter for most of the stands. Using the collected SAR backscatter and ground data, and the backscatter model, we studied the influences of changes in biomass on SAR backscatter as a function of radar frequency and polarization, and evaluated the feasibility of deriving the biomass from the backscatter. This study showed that C-HH, C-HV, C-VV, L-VV, and P-VV SAR backscatter may be insensitive to the biomass change. L-HH, L-HV, P-HH, and P-HV SAR backscatter changed more than 5dB as the biomass varied. This study also showed that the L-HH and P-HH backscatter or L-HV and P-H V backscatter may be used to develop algorithms to retrieve trunk biomass or canopy biomass of the loblolly pine forests.