Classifying and communicating landscape vegetation structure with LiDAR

PARTNERS: Oak Ridge National Laboratory, U.S. Fish and Wildlife Service, National Park Service, National Forests in North Carolina, State of North Carolina

SUMMARY: Information about vegetation vertical structure is critically important for characterizing species habitats and biodiversity. It is also useful for monitoring and managing forest resources and conservation planning. Compared to vegetation composition mapping, approaches to map structure have been greatly wanting, usually being inferred from simple assumptions of tree height and forest layer complexity based on time passed since disturbance. However, in landscapes that are topographically and developmentally diverse, such assumptions don’t always hold.

Light Detection and Ranging (LiDAR) captures information on three-dimensional canopy structure, yielding information not available in two-dimensional images of the landscape provided by traditional multi-spectral remote sensing platforms or traditional vegetation maps from polygons, but the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge. Researchers developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and characterized the vegetation canopy structure. This project combines novel methodological approaches to classifying vegetation structure with understanding the genesis of those complex patterns across the landscape. Researchers' primary focus area is the Southern Appalachians that have a complex vegetation including old growth, areas of historical logging and fire, younger managed forests, and non-forest across remarkable elevational and moisture gradients.

EFETAC’s ROLE: Eastern Threat Center scientists have helped develop the methodology used and are conducting landscape analyses of pattern and process.

STATUS: Ongoing

PROGRESS: Clustering-based classifications have been conducted separately for mid-2000s era North Carolina LiDAR at 20m, for the Tennessee side of Great Smoky Mountains National Park, and western North Carolina at 30m. Using this approach to typing and unclassified forest height data from LiDAR, researchers have assessed the relationships of forest structure to vegetation type, topography, and land use history.


Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR (research paper)

LiDAR-derived Vegetation Canopy Structure, Great Smoky Mountains National Park, 2011 (data set)

Mapping Vegetation Canopy Structure and Distribution for Great Smoky Mountains National Park Using LiDAR (poster)

"A New View of the Forest Canopy of the Smokies" (related article from CompassLive)


Steve Norman, Eastern Threat Center Research Ecologist, or (828) 259-0535

Bill Hargrove, Eastern Threat Center Research Ecologist, or (828) 257-4846

Updated June 2017

Document Actions
Personal tools

For the latest up-to-date ag webinars on all things agriculture, visit the Agriculture Webinars Portal