Continuous data on vegetation cover, height, and relative density are increasingly sought as useful metrics for determining animal habitat conditions across large areas. Airborne light detection and ranging (lidar) multi-return information provides a ready source of remotely sensed data that can directly estimate vegetation height and cover at appropriate spatial scales. The U.S. Geological Survey (USGS) Three-dimensional (3D) Elevation Program (3DEP) plans to collect lidar across the entire United States by 2023, creating an unprecedented opportunity for mapping habitat metrics at a fine resolution across entire regions. For this study, the 3DEP lidar point cloud data, which contains lidar returns from both bare earth and vegetation, were processed to create 2-dimensional canopy height maps.
The 3DEP lidar data are being used to model habitat characteristics for the endangered golden-cheeked warbler (Setophaga chrysoparia) across its breeding range in the juniper-oak woodlands of central Texas. Researchers obtained 33,897 lidar tiles and their associated digital elevation model (DEM) from 23 separate lidar collections between 2014 and 2018. The lidar data covered 94% of the 67,246 square-kilometer warbler breeding range. Canopy height layers were developed at a 1-meter grid cell size using freely available FUSION software. Because most lidar collections did not have classified vegetation returns, the team isolated vegetation canopy for processing by: (1) extracting only canopy heights less than 40 meters above ground level (AGL); and (2) extracting points using a mask of classified vegetation cover previously developed at the same resolution from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) color infrared (CIR) digital aerial photography. The resulting canopy height maps better distinguish tree versus shrub or low canopy cover measured at specific heights above ground.
Adjusted juniper and broadleaf tree canopy cover classified from NAIP CIR and attributed with lidar canopy height data are being used to determine the tree height threshold that is most favorable for golden-cheeked warbler habitat. Lidar height data are particularly important across the western range of this woodland-dwelling species, where woody species transition from tree to shrub in response to decreasing precipitation. These habitat metrics will be coupled with more than 1,800-point count surveys of the golden-cheeked warbler conducted in 2018 to determine the distribution of the breeding population and identify desired future conditions conducive to recovery of this species. A spatially explicit map of golden-cheeked warbler densities across its breeding range will provide land managers an improved understanding of where high-quality habitat currently exists and locations where active management could be used to improve habitat conditions.
Maps showing (a) original and (b) light detection and ranging (lidar)-corrected tree cover classification at a 1-meter grid cell size across the breeding range of the endangered golden-cheeked warbler.