An economic assessment of forest inventory parameters from LIDAR

LIDAR and field measurements of trees per acre and stand height in loblolly pine, Pinus taeda L., plantations were compared. This study focuses on the economic implications of simulating various LIDAR posting densities during forest inventory sampling to obtain estimates of stand variables. LIDAR-derived trees per acre were not significantly different from field estimates at alpha = 0.05. Stand height was significantly different due to measurement error and biological influences. Field-sampled distributions of trees per acre were used to truncate LIDAR height distribution of dominant and codominant trees. Confidence interval estimates at the 95 percent level were used to compute upper and lower bounds on per acre estimates of volume and dollar value from trees per acre and stand height. Since the 95 percent confidence interval on LIDAR values did not encompass ground values, LIDAR error was expressed as a percentage of field mean value. The knowledge gained from this study will potentially enhance future economic utility of LIDAR and implementation of the technology into operational settings.