Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – infrared data

The United States Department of Defense (DoD) Strategic Environmental Research and Development Program (SERDP) funded project: "Multi-scale Analyses of Wildland Fire Combustion Processes in Open-canopied Forests using Coupled and Iteratively Informed Laboratory-, Field-, and Model-based Approaches (RC-2641)" small-scale field experiments were designed to investigate how contrasting fuel conditions (e.g., fuel load, particle type, bulk density), fire spread type (e.g., heading vs. backing), and ambient conditions (e.g., seasonality, moisture, flow, temperature) influenced physical processes associated with combustion (e.g., heat transfer, flame propagation, flow) and the scale-dependent coupling of these processes. Additionally, these experiments provide 1) a linkage between small-scale laboratory combustion experiments and large-scale operational prescribed fires, and 2) archived datasets for further model development and evaluation. Our experimental design incorporates complementary approaches, methods, and instrumentation employed at these other scales, to quantify critical properties of the experimental fires’ physics domains (e.g., fuels and ambient conditions) and processes associated with combustion (e.g., heat transfer, flame propagation, flow). The small-scale field experiments include a series of highly instrumented, intermediate-scale experiments conducted on 100 square meter plots at the Silas Little Experimental Forest, New Lisbon, New Jersey. This dataset contains data collected in the spring of 2018 and 2019 from a FLIR infrared video camera. Infrared (IR) data were collected using a FLIR infrared video camera (A655SC, FOL6 100.0-650.0 C lens; FLIR Systems Inc., Wilsonville, OR). The camera was mounted on the plot center tower 7.5 meters (m) and 9 m above the ground, depending on experiment, to provide a nadir view of the plot. Data were collected at 20 hertz using FLIR ResearchIR Max (Version 4.40.1.6) software. The raw data includes a sequence (SEQ) IR video file for each burn. The processed data includes a series of tables per burn in approximately 1 second (s) increments identifying pixels burning (temperatures above 300 degrees Celsius (°C)), and plot burn summaries for each burn identifying the count and percent of pixels burning per frame, count and percent of pixel ignitions per frame and pixel residence time (time (s) each pixel burned).
Many DoD facilities utilize low intensity prescribed fire to manage hazardous fuels, restore ecological function and historic fire regimes, and encourage the recovery of threatened and endangered species in the forests they manage. Current predictive models used to simulate fire behavior during low-intensity prescribed fires (and wildfires) are empirically based, simplistic, and fail to adequately predict fire outcomes because they do not account for variability in fuel characteristics and interactions with important meteorological variables. This study used a suite of measurements at the fuel particle, fuel bed, field plot, and stand scales to quantify how variability in fuel characteristics and key meteorological factors interact to drive fire behavior during low intensity prescribed burns. These experiments were designed to inform the development and evaluation of physics-based models that explicitly account for combustion, turbulent transfer, and energy exchange by coupling and scaling individual component processes. These datasets provide measurements to improve the understanding of, and ability to accurately predict, fire behavior under a wide range of management scenarios.
A summary of the SERDP Project RC-2641 can be found at the RC-2641 Project Overview (serdp-estcp.org): https://www.serdp-estcp.org/Program-Areas/Resource-Conservation-and-Resiliency/Air-Quality/Fire-Emissions/RC-2641. Please reference the plot layout and documentation data publication (Gallagher et al. 2022) as these data provide the sensor locations of each burn, a detailed description of data collected and a burn summary.