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Ground-based light distance and ranging (LiDAR) laser scanning provides a way of generating dense point cloud models that reflects the nature and structure of three-dimensional objects. Scanning hardware and its interpretive software relies upon the measurement of the speed of light, a known constant, which these sensors emit. Each laser pulse is emitted from a known point of origin and measures the time elapsed between the transmission of a pulse and reception of the reflected pulse (Bachman, 1979). This means that laser scanners can be manufactured to perform quickly in the field. Select laser scanning platforms, of varying price and applicability, can capture and record laser pulses at speeds of up to 100,000 individual points per second (Jones et al., 2016).
Efforts have been made to reconstruct the stem and branch structures from ground scans (Pfeifer et al., 2004; Cheng et al., 2007). Still others have developed an approach for producing polygon models of trees reconstructed from ground scans (Xu et al, 2007). These efforts are nonetheless highly dependent of the type of equipment, distance from target, and other varying factors of the scans. In Hopkinson, a natural stand of Sugar maple (Acer saccharum) in southern Ontario were scanned and later sampled. This traditionally pioneer species possess a relatively simple architecture within a natural stand that does not greatly impede the use of scanning systems. However, as a short-lived species that is susceptible to water stress, they are not traditionally present in an urban forest landscape (Close, Nguyen, and Kielbaso, 1996). Scans made in natural forest environments usually require dealing with different levels of obstruction between the various vegetation components (Hopkinson et al., 2004). In addition, the presence of varying wind conditions will result in a scattering of data points due to the motion of the canopy and foliage. The registration of multiple scans of a given tree acquired from different observation angles will lead to extremely dense point clouds that do not necessarily contribute to any further modeling ability (Huang et al., 2011).
Methods for estimating diameter at breast height (DBH), stem mapping, and tree height determination are representative and accurate when appropriately paired with ground-based LiDAR. (Tansey et al., 2009, Lovell et al., 2011, Huang et al., 2011, Jones et al., 2016). A recent study using phase-based LiDAR scanning technology to measure inventory parameters showed that this new technology has potential to mitigate the distorting effect that tree leaves exhibit in the point cloud data which suggest this area requires further investigation (Yao et al., 2011). Other studies have shown that beyond interpolation of linear metrics these dense point clouds can be used to estimate aboveground biomass, product quality, tree species identification, crown canopy extent and volume (Lin and Herold, 2016; Hackenberg et. al., 2015; Blanchette et. al., 2015; Newnham et. al., 2015; Hopkinson et. al., 2004; Lefsky, 2002). In Lin and Herold, a four part theoretical and field based comparison study involved Boreal forest tree species that achieve up to 90% volumetric accuracy results. These results are based upon field estimates that themselves rely upon the use of a correlation equation, not direct physical measurement of the specimen. Others such as Newnham and Hackenberg evaluate existing allometrics that show a strong predictive ability of terrestrial LiDAR with regard to biomass, but in the case of Newnham these results are not field validated and though Hackenberg validates with destructive sampling the results are narrowly applied (Newnham et al., 2015; Hackenberg et al., 2015). In general, validation restrictions hamper most studies through either cost and time constraints or the specimen in question being protected or high value in nature. This study uses a routine of data collection, model construction, and field verification that, within its scope, could be applied to all similar oak species using any vendor’s scanning/registration products.