The goal of the current study was to develop methods of estimating the height of vertical components within plantation coniferous forest using airborne discrete multiple return lidar. In the summer of 2008, airborne lidar and field data were acquired for Loblolly pine forest locations in North Carolina and Virginia, USA, which comprised a variety of stand conditions (e.g. stand age, nutrient regime, and stem density). The methods here implement both field plot-scale analysis and an automated approach for the delineation of individual tree crown (ITC) locations and horizontal extents through a marker-based region growing process applied to a lidar derived canopy height model. The estimation of vertical features was accomplished through aggregating lidar return height measurements into vertical height bins, of a given horizontal extent (plot or ITC), creating a vertical 'stack' of bins describing the frequency of returns by height. Once height bins were created the resulting vertical distributions were smoothed with a regression curve-line function and canopy layers were identified through the detection of local maxima and minima. Estimates from Lorey's mean canopy height was estimated from plot-level curve-fitting with an overall accuracy of 5.9% coefficient of variation (CV) and the coefficient of determination (R-2) value of 0.93. Estimates of height to the living canopy produced an overall R-2 value of 0.91 (11.0% CV). The presence of vertical features within the sub-canopy component of the fitted vertical function also corresponded to areas of known understory presence and absence. Estimates from ITC data were averaged to the plot level. Estimates of field Lorey's mean canopy top height from average ITC data produced an R-2 value of 0.96 (7.9% CV). Average ITC estimates of height to the living canopy produced the closest correspondence to the field data, producing an R-2 value of 0.97 (6.2% CV). These results were similar to estimates produced by a statistical regression method, where R-2 values were 0.99 (2.4% CV) and 0.98 (4.9% CV) for plot average top canopy height and height to the living canopy, respectively. These results indicate that the characteristics of the dominant canopy can be estimated accurately using airborne lidar without the development of regression models, in a variety of intensively managed coniferous stand conditions.