Register

Download Presentation Slides

“FuelsCraft: An Innovative Wildland Fuel Mapping Tool for Prescribed Fire Decision Support on Military Installations” by Dr. Susan Prichard (RC23-7779)

In close collaboration with other SERDP and ESTCP projects, the FuelsCraft project team is using innovative methods to measure, model, and map wildland fuels in three dimensions. This presentation will describe the tools that have been developed and are being demonstrated for improved wildland fuels mapping. Scaled point cloud imagery from airborne laser scanning, terrestrial laser scanning, close-range photogrammetry, and field measurements can be translated into 3D inputs to computational fluid dynamics models of fire behavior and smoke. Based on our growing digital twin library, we are also developing ways to represent vegetation as heterogeneous complexes of shrubs, herbs, fine wood, and litter and to create building blocks for prescribed burn units to landscape mapping. FuelsCraft is being co-developed with the FastFuels framework to deliver scaled 3D datasets of understory fuels and realistic tree crowns to improve fire behavior and effects modeling. Within FuelsCraft, tree crowns, shrubs, grasses, downed wood, litter, and mixed complexes of combustible fuels are represented in volumetric pixels (voxels) as inputs to models of fire behavior and smoke. These improved methods to model fire behavior in forest understories, shrublands and grasslands are particularly important for prescribed burn planning and operations on U.S. military installations.

“FastFuels and QUIC-Fire: A Tool Suite Advancing DoW’s Prescribed Fire Planning and Analysis Capabilities” by Dr. Anthony Marcozzi (RC23-7626)

DoW installations conduct over 800,000 acres of prescribed burning annually to maintain training grounds and reduce wildfire risk. However, current fire planning tools rely on coarse two-dimensional fuel data and old empirical models that may not have the detail needed for effective prescribed fire planning. This project develops FastFuels and QUIC-Fire, a web-based tool suite that provides high-resolution, three-dimensional fuel and fire modeling capabilities for DoW fire managers. FastFuels generates detailed 3D fuel representations across the contiguous United States by integrating forest inventory data, remote sensing, and machine learning. It supports data assimilation from LiDAR and other local sources through a flexible "onramps" architecture, enabling site-specific fuel characterization. Paired with the physics-based QUIC-Fire model, the system enables managers to simulate prescribed fire operations, evaluate fuel treatment alternatives, and assess fire behavior under varying conditions. This presentation will describe the tool suite's capabilities, demonstrate applications at DoW-relevant sites, and discuss how these next-generation tools provide critical decision support for prescribed fire planning, wildfire risk reduction, and ecosystem management on military installations.

Speaker Biographies

Dr. Susan Prichard is the lead scientist with the Fire Landscapes Adaptive Management & Ecology (FLAME) laboratory at the University of Washington School of Environmental and Forest Sciences. Her main research interests include the effects of fire and other disturbances on forest dynamics and fuel treatment options to mitigate fire severity and smoke impacts in fire-prone forests. She currently leads research on wildland fire and vegetation dynamics, drivers of wildfire severity, smoke tradeoffs between prescribed and wildland fires, and 3D fuel characterization and modeling. Dr. Prichard received her bachelor’s degree from Evergreen State College, and her master’s and doctoral degrees in ecosystem science from the University of Washington in Seattle. 

Dr. Anthony Marcozzi is a research scientist with the New Mexico Consortium in Missoula, Montana where he conducts research on interactions between fuel and fire behavior, fireline dynamics, 3D fuel structure, and applications of AI and machine learning to large-scale forest mapping. His goal is to bridge the gap between detailed fuel science and operational fire management, and provide tools that enable fire managers to plan and evaluate prescribed fire operations and fuel treatments using advanced simulation capabilities. Dr. Marcozzi earned his bachelor’s degree in mathematics, economics, and statistics from the University of Missouri-Columbia, and his master’s and doctoral degrees in computer science from the University of Montana.