Title:

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

Author(s):

Ross, C. Wade; Loudermilk, E. Louise; O’Brien, Joseph J.; Snitker, Grant

Publication Year:

2024

How to Cite:

These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Ross, C. Wade; Loudermilk, E. Louise; O’Brien, Joseph J.; Snitker, Grant. 2024. Forest structural-complexity metrics derived from aerial lidar across four experimental forests in the southeastern United States. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2024-0019

Abstract:

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.

Keywords:

biota; elevation; environment; Ecology, Ecosystems, & Environment; Inventory, Monitoring, & Analysis; Assessments; Natural Resource Management & Use; Forest management; Timber; forest structure; structural complexity; lidar; ALS; Joint Fire Science Program; JFSP; Bent Creek Experimental Forest; Coweeta Hydrologic Laboratory; Escambia Experimental Forest; Hitchiti Experimental Forest; southeastern United States; Alabama; Georgia; North Carolina; Tennessee

Related publications:

• Ross, C. Wade; Loudermilk, E. Louise; O’Brien, Joseph J.; Snitker, Grant. Unknown. Lidar-derived structural-complexity data across four experimental forests. Data in Brief. [In review].

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  • RDS-2024-0019_Metadata_Fileindex.zip (32.1 KB; Checksum)
  • RDS-2024-0019_Supplements.zip (122.67 KB; Checksum)
  • RDS-2024-0019_Data_BentCreek.zip (2.36 GB; Checksum)
  • RDS-2024-0019_Data_Coweeta.zip (2.05 GB; Checksum)
  • RDS-2024-0019_Data_Escambia.zip (1.96 GB; Checksum)
  • RDS-2024-0019_Data_Hitchiti.zip (1.31 GB; Checksum)

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