1. Factsheet # 27 Canopy Structure From Aerial and Terrestrial LiDAR
Understanding multiscale dynamics of landscape change through the application of remote sensing & GIS
Canopy Structure From Aerial and Terrestrial LiDAR
This research was funded by the Bureau of Land Management
Introduction: Measuring crown parameters in the field can be a challenging and time consuming task, often prone to high measurement error. Technological advancements in the field of remote sensing including the development and implementation of hyperspatial Light Detection and Ranging (LiDAR) and hyperspectral remote sensing are driving the discipline to new frontiers of forestry applications. LiDAR is one of the active optical remote sensing technologies and is a great tool for extracting information about vertical and horizontal canopy structure. The three dimensional nature of LiDAR data makes it possible to detect and isolate individual and clusters of trees (Hyyppa et al., 2001; Persson et al., 2002)
Figure 3. NMDS ordination of plot canopy structure metrics by canopy slice, where slice 2, 3, and 4 represent height gradients from low, medium and high, respectively.
Calibrating Aerial LiDAR with canopy metrics derived from Terrestrial LIDAR
Due to the scanning time and the bulkiness of the equipment the TLS is great at quantifying the canopy structure at the plot level. However the big question of accurately quantifying canopy structure on a landscape level still needs to be answered. We took the calibration approach to investigate the relationship between TLS derived canopy structure and metrics derived from aerial lidar (ALS). 2m
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Figure 1. Left: Graphic respresenting the point cloud slicing technique. Right: Image of a terrestrial lidar scanner while collecting scans of canopy.
Methods: We used a terrestrial lidar scanner (TLS)(Fig1.) to obtain three dimensional point cloud representations of forest plots for further analysis and extraction of canopy metrics. Please note the methods for scanner field set up, point cloud processing and canopy slicing techniques are described in Factsheet #21. We proceeded to extract canopy metrics from the point clouds by applying the patch metrics to quantify the canopy of each plot (Fig.2). The patch metrics in this case were used to characterize the configuration of individual canopy patches and the distribution and density of those patches on the landscape, which in the case of this study is study plot. In use of patch metrics in describing the forest canopy structure three major components were focused on: metrics describe size and shape, patch composition and the spatial configuration of the canopy patches.
Figure 4. The stark differences in point cloud density between ALS and TLS
Can simple ALS metrics describe canopy structure in a similar way? After extracting ALS point cloud metrics for the same set of plots we were able to model the canopy structure metrics derived from TLS. The two lidar datasets connect between slices 3 and 4 (middle of the canopy height gradient). The best model that described canopy shape, size and structure utilized the percentage of ALS 3rd and 4th returns.
Results: Canopy structure metrics that represent canopy shape, size and distribution varied significantly along the height gradient (Fig. 3). The canopy metrics were significantly correlated with stand parameters such as trees per hectare (TPH), above-ground biomass, stand density index (SDI), basal area, volume and quadratic mean diameter (QMD).
Figure 2. Canopy distribution maps for one of the study plots
Figure 5. Average point distribution along the height gradient.
THE ISSUE: Remote sensing techniques can be used to quantify forest stand level structure. We developed a method that uses terrestrial laser scanning (TLS) to accurately quantify canopy structure. To get at canopy structure at landscape level we investigate the possibility of modeling TLS canopy structure with metrics derived from aerial LiDAR.
THE KEY QUESTIONS:
Can we calibrate ALS with canopy structure metrics derived from TLS?
ⓒ RSGAL 2013
Citation: Kazakova A.N., L.M. Moskal, Canopy structure from aerial and terrestrial LiDAR. Factsheet # 27. Remote Sensing and Geospatial Application Laboratory, University of Washington, Seattle, WA. Digital version of the fact sheet can be downloaded at: