Improved Visibility Calculations with Tree Trunk Obstruction Modeling from Aerial LiDAR

Viewshed and line-of-sight are spatial analysis functions used in applications ranging from urban design to archaeology to hydrology. Vegetation data, a difficult variable to effectively emulate in computer models, is typically omitted from visibility calculations or unrealistically simulated. In visibility analyzes performed on a small scale, where calculation distances are a few hundred meters or less, ineffective incorporation of vegetation can lead to significant modeling error. Using an aerial LiDAR (light detection and ranging) data set of a lodgepole pine (Pinus contorta) dominant ecosystem in Idaho, USA, tree obstruction metrics were derived and integrated into a short-range visibility model. A total of 15 visibility plots were set at a micro-scale level, with visibility modeled to a maximum of 50 m from an observation point. Digital photographs of a 1 m2 target set at 5 m increments along three sightline paths for each visibility plot were used to establish control visibility values. Trunk obstructions, derived from mean vegetation height LiDAR data and processed through a series of tree structure algorithms, were factored into visibility calculations and compared to reference data. Results indicate the model calculated using trunk obstructions with LiDAR demonstrated a mean error of 8.8% underestimation of target visibility, while alternative methods using mean vegetation height and bare-earth models have an underestimation of 65.7% and overestimation of 31.1%, respectively.