Abstract
Advancements in airborne LiDAR analysis technology have made it possible to quantify forest resource volumes based on individual trees, and such technology may soon replace field surveys. Unlike individual tree detection or tree height measurements, diameter at breast height (DBH) is difficult to determine directly from measured data and is instead estimated indirectly using the correlation between crown size and DBH. Indicators that represent crown size include crown area, surface area, length, and length ratio, and were utilized with tree height as explanatory variables in ten combinations to determine a regression formula. DBH and tree height calculated from the regression formula were applied to an equation to calculate stem volumes of individual trees. Airborne LiDAR measurements were taken using ALS50-II and ALS60 (Leica) at a density of 4 points/m2. An evaluation of the relationship between the regression formulae and DBH estimates indicated that a combination of crown area, tree height, and crown ratio for Japanese cedar, and a combination of crown area and tree height for Japanese cypress, yielded the highest coefficients of determination. The average error and RMSE were 6.9% and 2.38 cm respectively for Japanese cedar, while the corresponding values for Japanese cypress were 8.35% and 2.51 cm. Once the relationship was extended to the stem volumes of individual trees, the average error was 14.4% and RMSE was 0.10 m3 for Japanese cedar. The corresponding values for Japanese cypress were 18.9% and 0.10 m3. These results demonstrate the potential use of airborne LiDAR as a substitute for field surveys.
Highlights
Remote sensing can be employed to efficiently survey forest resources
In regression formulae 9 and 10, where crown length and crown length ratio were added to crown area and tree height, respectively, the coefficient of determination improved compared to regression formula 4 for both Japanese cedar and Japanese cypress; the p-value of the power of crown length or crown length ratio, β3, exceeded 0.05
Regression formulae to estimate diameter at breast height (DBH) were tried with ten patterns of equations, using combinations of one to three explanatory variables
Summary
Remote sensing can be employed to efficiently survey forest resources. Research using airborne LiDAR has made significant progress recently. To estimate DBH using airborne LiDAR, subsequent studies have estimated DBH by combining characteristics such as crown area and length to determine the relationship between tree crown size and tree height (Verma, Lamb, Reid, & Wilson, 2014; Yao, Krzystek, & Heurich, 2012) While these studies have shown that several explanatory variables can be used to estimate DBH, explanatory variables appropriate for Japanese cedar and Japanese cypress from airborne LiDAR are unknown. The other method uses individual-tree-based approaches, in which stem volume is computed by applying tree heights obtained from individual tree detection and DBH estimates obtained from LiDAR analysis to an existing stem volume equation (Heurich, et al, 2004; Hyyppä et al, 2005; Persson, Holmgrem, & Söderman, 2002). The study considered the impact of multiple DBH estimates obtained from DBH regression analyses for stem volume estimates, and aimed to identify explanatory variables for DBH estimation appropriate for the estimation of stem volume
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
