Josh Enterkine1*, Ahmad
Hojatimalekshah2, Monica
Vermillion3, Thomas Van Der Weide1,
Sergio A. Arispe4, William J.
Price5, April Hulet6, Nancy F.
Glenn1.
1 Boise State University Department of Geosciences,
Boise ID
2 Boise State University Department of Computer
Sciences, Boise ID
3 USDA US Forest Service, Forest Health Protection
Region 4, Boise ID
4 Oregon State University Extension Service-Malheur
County, Oregon State University, Ontario, OR
5 Oregon State University Extension Service-Baker &
Union Counties, Oregon State University, Baker City, OR
6 Brigham Young University, Plant & Wildlife
Sciences, Provo, UT
*joshenterkine@boisestate.edu, 1910 W. University Dr., Boise, ID,
83725-1535
Abstract
Rangelands and semi-arid ecosystems are subject to increasing changes in
ecologic makeup from a collection of factors. In much of the northern
Great Basin of the western United States, rangelands invaded by exotic
annual grasses such as cheatgrass (Bromus tectorum ) and
medusahead (Taeniatherum caput-medusae ) are experiencing an
increasingly short fire cycle, which is compounding and persistent.
Improving and expanding ground-based field methods for measuring
above-ground biomass (AGB) may enable more sample collections across a
landscape and over succession regimes, and better harmonize with other
remote sensing techniques. Developments and increased adoption of
uncrewed aerial vehicles and instrumentation for vegetation monitoring
are enabling greater understanding of vegetation in many ecosystems.
Research towards understanding the relationship of traditional field
measurements with newer aerial platforms in rangeland environments is
growing rapidly, and there is increasing interest in exploring the
potential use both to quantify AGB and fine fuel load at pasture and
landscape scales. Our study here uses relatively inexpensive handheld
photography with custom sampling frames to collect and automatically
reconstruct 3D-models of the vegetation within 0.2 m2quadrats (n = 288). Next, we examine the relationship between volumetric
estimates of vegetation to compare with biomass. We found that volumes
calculated with 0.5 cm voxel sizes (0.125 cm3) most
closely represented the range of biomass weights. We further develop
methods to classify ground points, finding a 2% reduction in predictive
ability compared to using the true ground surface. Overall, our
reconstruction workflow had an R2 of 0.42, further
emphasizing the importance of high-resolution imagery and reconstruction
techniques. Ultimately, we conclude that more work is needed of
increasing extents (such as from UAS) to better understand and constrain
uncertainties in volumetric estimations of biomass in ecosystems with
high amounts of invasive annual grasses and fine fuel litter.