To characterize fine-scale variations in vegetation structure, quantify heterogeneity, and capture fuel estimation and consumption, destructive 3D clip plots were sampled across...

To characterize fine-scale variations in vegetation structure, quantify heterogeneity, and capture fuel estimation and consumption, Leica BLK360 G1 terrestrial LiDAR scans were...

Pyrolytic and flaming combustion gases were sampled in a series of experimental fires in a small wind tunnel at the U.S. Forest Service laboratory in Riverside, CA and in 30 m x...

The dataset presents parameters of the Offset Elliptical Normal model for wind climate analysis. Parameters have been obtained for sites across the USA where...

Atmospheric particulate matter less than or equal to 2.5 micrometers (PM2.5, units of micrograms/m3) was measured at three prescribed (Rx) burns at Eglin Air Force Base in March...

Atmospheric particulate matter less than or equal to 2.5 micrometers (PM2.5, units of micrograms/m3) was measured at two prescribed (Rx) burns at Fort Stewart Georgia in...

Field measurements collected before and after 2023 study fires at Eglin Air Force Base (AFB) to document fuel loads (large diameter fuels, litter depth, duff...

Trees and saplings were measured within 61 fixed-radius plots to characterize overstory vegetation across the E, F-6.3, and F-6.4 burn units. This dataset is part of the...

This data product contains 1) weights of destructively sampled biomass, 2) terrestrial laser scanning (TLS) point cloud data, and 3) maps of predicted biomass and consumption...

The data is collected at one Georgia Tech instrumented trailer located at two different locations (shown in the locations information) from March 2 till 6, 2022. Trailer was set...

Sample data and Fire Dynamic Vision (FDV) code for experiments in the paper: Sagel, D., & Quaife, B. (2025). Fire dynamic vision: Image segmentation and tracking for...

This dataset contains fire spread simulations generated with a physics-driven and data-driven model. The data-driven model is trained with a TensorFlow applied to data generated...

Fuel moisture content (FMC) is a critical parameter in fire and plume behaviors, showing diurnal and spatial variations influenced by local meteorological conditions, soil...

This dataset provides the macroplot geographical location data where Leica BLK360 G1 terrestrial LiDAR scans, destructive clip plots, photographs, transects, radiometers, and...

This dataset provides the macroplot geographical location data where Leica BLK360 G1 terrestrial LiDAR scans, destructive clip plots, photographs, transects, radiometers, and...

To measure fuel moisture content, vegetation was collected at adjacent burn units with similar land cover, species composition, and time since the last prescribed burn. This...

Destructive clip plots were sampled in nine burn units to characterize fine-scale variations in vegetation structure, quantify heterogeneity, and capture fuel estimation and...

This dataset contains contextual information for the Wildland Fire Science Initiative (WFSI) research burn campaign: Fort Stewart 2025, conducted April 14, 2025 to April 18,...

Ignition tracking data collected with Garmin GPS and Go Pro recorders for prescribed fire research. Ignitions for the Eglin research prescribed burns were...

A network of a dozen sonic anemometers measured the near-surface winds and temperatures surrounding the burn zone. Three SODARs (Sonic Detection and Ranging) profiled the plume...