Richter, DanielHarrington, Mary2015-12-072015-12-072015-12-07https://hdl.handle.net/10161/11110Airborne scanning LiDAR (Light Detection and Ranging) is a promising technique for efficient and accurate forest volume and biomass mapping due to its capacity for direct measurement of the three-dimensional vegetation structure. In this study, small-footprint, multiple return LiDAR data was collected over our 58 mi2 study site in western South Carolina. The area was heavily farmed for about 150 years until farmers abandoned the fields in the early 1900s. Today, mature old-field pine forests grow on the abandoned agricultural land. This study used LiDAR data to compare aboveground biomass (ABG) of old-field forests and neighboring reference hardwood stands. Metrics were derived from the LiDAR data and a step-wise multiple linear regression was calibrated with field measurements (R2 =0.722, F2,32 =45.23, p < 0.001). The resulting model was used to predict the distribution of AGB across the site. A paired t-test indicated that mean AGB was significantly higher in reference hardwood sites than in old-field forests (t=5.22, df= 21, p < 0.001).en-USaboveground biomassLiDARClimate changePiedmontOld-field forestcalhoun experimental forestMaster's project