Measurements of the three-dimensional (3-D) structure of forest canopies are important because they can convey information about how the canopy intercepts material (e.g., precipitation or light) and how habitat is structured within it. The most common methods are based on plant area index (the total plant area per unit ground area), a quasi-3-D metric that is further hampered by the manner in which it is measured, either directly or indirectly. Direct methods are laborious and require destructive sampling, while indirect methods have resolution limitations and accuracy issues. However, airborne laser scanners (lidar) have the ability to make direct non-destructive measurements of the heights of plant elements over large areas that are very accurate, which should be able to convey more detailed information about 3-D canopy structure than current field-based techniques. The goal of this research is to test the hypotheses that coarsely collected discrete airborne lidar can be used to estimate the height of intra-canopy elements, and that it can be used to describe the 3-D structure of a large heterogeneous forest. Results/Conclusions
Tree heights and canopy structure were measured in 67 plots across nine forest types (3 deciduous and 6 coniferous) on the Bayfield Peninsula in northern Wisconsin. These data were used to analyze discrete lidar data collected across the approximately 200 km2 of forest on the peninsula. We found strong correlations between heights of a number of canopy elements (top of tree r2 = 0.88, height of the widest point of crown r2 = 0.75, height of the lowest living branch of the crown r2 = 0.70) for plots as small as 300 m2. Estimates of canopy closure (CC) and plant area index (PAI) were comparable. Because PAI and CC do not capture the true 3-D nature of a canopy, we developed a novel approach that quantifies the 3-D clumping of canopy elements using lidar data. We then applied these relationships to the full set of lidar data and created maps of canopy structure for the 200 km2 region of the peninsula. Though there are numerous applications for these maps, we will initially use them to analyze patterns of snow interception by different forest types across a large spatial extent.
