Using Airborne Light Detection and Ranging (LIDAR) to Characterize Forest Stand Condition on the Kenai Peninsula of Alaska.
Authors:
Andersen, Hans-Erik USDA, FS
Source:
Western journal of applied forestry. 2009 Apr., v. 24, no. 2, p. 95-102.
NALT Subjects:
forest stands lidar forest canopy vegetation cover tree crown classification tree and stand measurements forest inventory spatial data forest types forest trees height remote sensing Alaska
Other Subjects:
condition classes
Issue Date:
Apr-2009
Abstract:
Airborne laser scanning (also known as light detection and ranging or LIDAR) data were used to estimate three fundamental forest stand condition classes (forest stand size, land cover type, and canopy closure) at 32 Forest Inventory Analysis (FIA) plots distributed over the Kenai Peninsula of Alaska. Individual tree crown segment attributes (height, area, and species type) were derived from the three-dimensional LIDAR point cloud, LIDAR-based canopy height models, and LIDAR return intensity information. The LIDAR-based crown segment and canopy cover information was then used to estimate condition classes at each 10-m grid cell on a 300 x 300-m area surrounding each FIA plot. A quantitative comparison of the LIDAR- and field-based condition classifications at the subplot centers indicates that LIDAR has potential as a useful sampling tool in an operational forest inventory program.
