Sustainable forest and soil management requires accurate information about site index (SI, tree height at a base age). The objectives of this study were to compare site indices from field inventory data (2008-2009), Soil Survey Geographic Database (SSURGO), and Light Detection and Ranging (LiDAR, 2008), and to determine the uncertainty in the site indices from the southern part of the Clemson Experimental Forest.  When LiDAR derived analysis was used to compare to SSURGO there were statistical differences for site indices for all of the tree species in this study: loblolly pine (Pinus taeda), scarlet oak (Quercus coccinea), shortleaf pine (Pinus echinata), white oak (Quercus alba), and yellow poplar (Liriodendron tulipifera). LiDAR has the potential to provide reliable and rapid estimates of site index variability within the soil map units.  Loblolly pine and shortleaf pine had the greatest statistical differences with the LiDAR derived site indices being much larger than the SSURGO values. The results of this study indicate that a larger sample size for LiDAR is a better option to decrease variation, and that the map unit level may be the best option.