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Airborne laser scanning (also known as light detection and ranging or [WAR) 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 [IDAR 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-rn area surrounding each HA plot. A quantitative comparison of the [IDARand field-based condition classifications at the subplot centers indicates that LIDAR has potential as a useful sampling tool in an operational forest inventory program.

Using Airborne Light Detection and Ranging (LIDAR) to Characterize Forest Stand Condition on the Kenai Peninsula of Alaska