Vegetation Biomass and Voxel Data from the 2022 Department of Defense Wildland Fire Science Initiative Fort Stewart Campaign

To characterize fine-scale variations in vegetation structure, quantify heterogeneity, and capture fuel estimation and consumption, destructive 3D clip plots were sampled across the F units. This dataset provides vegetation biomass, occupied volume, and fuel type data collected before (February 2022) and after (March 2022) the prescribed burns.

Data and Resources

Additional Info

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Last Updated July 4, 2025, 09:33 (UTC)
Created July 4, 2025, 09:33 (UTC)
Source https://wfsi-data.org/view/doi%3A10.60594/W4SG60
associated_parties Gregg Chapman, gregg.chapman@usda.gov, USDA Forest Service, Southern Research Station, Clemson, SC, contributor | Irenee Payne, irenee.payne@usda.gov, USDA Forest Service, Southern Research Station, Athens GA, contributor | Derek Wallace, derek.wallace@usda.gov, Tall Timbers Research Station, Tallahassee, FL, contributor | Wade Ross, wross@talltimbers.org, Tall Timbers Research Station, Tallahassee, FL, contributor | Jacob Ney, Tall Timbers Research Station, Tallahassee, FL, contributor | Vanessa Niemczyk, Tall Timbers Research Station, Tallahassee, FL, contributor | Nuria Sanchez-Lopez, University of Idaho, Department of Forest, Rangeland and Fire Sciences, contributor
award Object-based aggregation of fuel structures, physics-based fire behavior and self-organizing smoke plumes for improved fuel, fire, and smoke management on military lands.
creators Eva Louise Loudermilk, eva.l.loudermilk@usda.gov, USDA Forest Service, Southern Research Station, https://orcid.org/0000-0001-8191-8670 | Chad Hoffman, c.hoffman@colostate.edu, Colorado State University, Department of Forest and Rangeland Stewardship , https://orcid.org/0000-0001-8715-937X | Andrew Hudak, andrew.hudak@usda.gov, USDA Forest Service, Rocky Mountain Research Station, https://orcid.org/0000-0001-7480-1458 | Christie Hawley, christie.m.hawley@usda.gov, USDA Forest Service, Southern Research Station, https://orcid.org/0000-0001-9105-2065 | Scott Pokswinski, spokswinski@newmexicoconsortium.org, New Mexico Consortium, Center for Applied Fire and Ecosystems Science, https://orcid.org/0000-0001-5753-4132
doi doi:10.60594/W4SG60
encoding utf8
funder U. S. Department of Defense (DoD), Strategic Environmental Research and Development Program (SERDP) , http://dx.doi.org/10.13039/100013316
harvest_object_id 87f5e7a5-c085-4463-82ab-c6e4a34c053f
harvest_source_id a2637971-af12-457f-ae4a-831d2202a539
harvest_source_title WIFIRE Commons
maintainor Christie Hawley, christie.m.hawley@usda.gov
method Fort Stewart-Hunter Army Airfield is in Hinesville, Georgia, approximately 30 miles west of Savannah. Of the 273,000 acres, 228,511 were prescribed burned across Fiscal Years 2019-2021. In 2022, E16.2 (254 hectares), E16.3 (257 hectares), F6.3 (260 hectares), F6.4 (397 hectares) were available for prescribed burning. Located in the western half of Fort Stewart, F6.3 and F6.4 (F units) are located just below Salem Cemetery and E16.2 and E16.3 are bisected by Taylors Creek. While E16.2 and E16.3 are two management units, they were sampled and burned as one unit, E units. The E units were last burned as one unit on February 28, 2019. F6.3 was last burned on April 13, 2019. F6.4 was last burned on April 14, 2019. In 2022, the research burns occurred on March 2nd (F6.4), 3rd (F6.3), and 5th (E units). In February 2022, 40 macroplots were randomly established in each burn unit for a total of 120 macroplots. In each burn unit, the macroplots were distributed across the dominant forest types—wetland edge (10 plots), burn unit edge (10 plots), and upland pine which includes flatwoods and remnant plantation (20 plots). The interior wetlands were not sampled as they are often inundated with water and typically do not ignite or contribute to fire spread. In the F units, 41 macroplots were randomly selected for pre- and post-burn 3D clip plot sampling, where 21 were in F6.3 and 20 in F6.4. In the F units, pre- and post-burn clip plots were sampled at total of 41 randomly selected macroplots. NOTE: Clip plots were not established or collected in the E units. A pre-burn clip plot was established approximately two to three meters from the plot center. A post-burn clip plot was also established within two to three meters of the plot center. The post-burn plot was visually identified as having a fuel composition and structure similar to the pre-burn clip plot. From the macroplot center, distance and azimuth to the northwest corner of each clip plot were measured. The compass declination was set to zero (magnetic north). The sampling area was 0.5 m in width by 0.5 m in length by 1 m in height. The frame was subdivided into two vertical sampling layers or strata: ground to 30 cm and 30 to 100 cm. Vegetation and fuel categories were recorded in both the pre- and post-burn clip plots. Vegetation, fuel category, and biomass data were collected using a simplified approach from Hawley et al. 2018. The vegetation and fuel categories for this site were defined as woody live vegetation, now dead woody vegetation, woody litter, woody dead and downed 1-hour fuels, 10-hour fuels, 100-hour fuels, 1000-hour fuels, pinecones, conifer litter, conifer needles, and herbaceous vegetation, which includes graminoids, forbs, and vines. The ‘now dead woody vegetation’ category was used only in post-burn sampling to classify pre-burn woody live stems partially consumed by the prescribed fire and when the aboveground plant was dead or top-killed. Before the burn, within both the pre- and post-burn plots, the presence and absence of each vegetation and fuel category were recorded within each stratum. At the pre-burn plot, the biomass was destructively harvested from each stratum. After the burn, within each post-burn clip plot, the presence and absence of each vegetation and the fuel category were again recorded, and the biomass was destructively harvested within each stratum. In the Athens Prescribed Fire Science Laboratory, Athens, GA, USA, the clip plot biomass was sorted, dried, and weighed to determine each vegetation and fuel category's dry weight (grams). The sorted biomass was dried at 70 ◦C until the sample's weight no longer changed, typically within 48–72 hours. Hawley, C.M.; Loudermilk, E.L.; Rowell, E.M.; Pokswinski, S. A novel approach to fuel biomass sampling for 3D fuel characterization. MethodsX 2018, 5, 1597–1604. https://doi.org/10.1016/j.mex.2018.11.006
project Funding Awards RC20-1346 and RC19-1119 for DoD Wildland Fire Science Initiative (WFSI)
spatial {"type": "Polygon", "coordinates": [[[-81.717107, 32.043835], [-81.746122, 32.043835], [-81.746122, 32.078577], [-81.717107, 32.078577], [-81.717107, 32.043835]]]}
temporal {"endTime": "2022-03-06", "startTime": "2022-02-15"}