Forest structural-complexity metrics derived from aerial lidar across four experimental forests in the southeastern United States

Forest management often aims to enhance wildlife habitat and mitigate wildfire risks, yet spatially-resolved data on structural complexity are often lacking. To address this gap, we utilized 2021 aerial laser scanning (ALS) to generate raster and vector geospatial data characterizing forest structure across four USDA Forest Service Experimental Forests (EFs) in southeastern United States: Bent Creek Experimental Forest, Coweeta Hydrologic Laboratory, Escambia Experimental Forest, and Hitchiti Experimental Forest. This data publication contains raster gridded datasets for each EF, mapped at 1 x 1 meter resolution, providing wall-to-wall coverage. Data include, but are not limited to: aspect, canopy cover, canopy height, terrain surface model, irregularity and variation in elevation, steepness, structural diversity and arrangement of vegetation. Vector-based data include crown delineation and individual tree detection data obtained using multiple methods.
These data were developed to support on-going research focal areas of fire, hydrology, soil science, meteorology, cultural resources, and timber management.
For more information about these data, see Ross et al. (in review).