Estimating Urban Tree Metrics Using Terrestrial LiDAR Scanning

Abstract

Trees grown in an urban environment are typically from a selected list of suitable species due to their appearance and other factors. A popular oak species in recent decades has been the Nuttall oak (Quercus texana). A total of seven Nuttall oaks were scanned using a terrestrial LiDAR scanner and modeled for comparison to manual measurements. These trees were then destructively sampled in place to measure their above-ground biomass. The biomass data were compiled and statistically compared against digital models of each tree that were created from the LiDAR scans. This resulted in a Pearson coefficient of .977 and linear regression R2 value of .99 for the LiDAR derived measurements predictive ability in comparison to the manually derived measurements. This indicates an ability of this ground based LiDAR model to predict both the linear dimensions and volumetrics of the standing specimens without the need for such labor intensive and expensive sampling given the sensitivity and value of urban forests.