FastFuels: 3D Fuels for Next Generation Fire Models

Advanced 3D fire models offer new possibilities for detailed analysis of fuel treatments and prescribed fires. However, the spatially explicit, detailed 3D fuels data they require is difficult to get, particularly for large areas. FastFuels opens the door to this kind of modeling by combining existing fuels and spatial data with cutting edge modeling to generate the fuels data the 3D fire models need.

Managers are familiar with fire models used in incident support for wildfires. But they often find that when they use those models to analyze fuel treatments or to plan prescribed burns, they lack critical detail and can be difficult to relate to real world fuels. Newer 3D fire models offer remarkable capabilities to help managers understand their options at project level detail but so far have generally not been accessible to managers due to lack of 3D fuels data. FastFuels is intended to accelerate the use of advanced fire models, expanding the solution space for contemporary fire and fuels management problems from project level to landscape scales.

FastFuels is envisioned as a 3D fuels “superhighway”, accelerating the use of 3D fire models by leveraging FIA databases and other available spatial data, and then combining that data with cutting edge modeling to enable use of 3D fire models at landscape scales. Much of the logic in FastFuels derives from STANDFIRE, a prototype system for 3D fuel and fire modeling focused on fuel treatment analysis (Parsons et al 2018). FastFuels generates wall to wall fuels data for large areas and can be represented in tiles several kilometers on a side. A critical aspect of FastFuels is that, in addition to providing voxelized (3D raster) data for 3D fire models, it also retains individual tree attribute data, facilitating in-depth fuel treatment analysis and paving the way for stronger fire behavior – fire effects interactions. Similarly, FastFuels also seeks to facilitate use of data from new sources (e.g. LiDAR, UAS) and new techniques emerging in the remote sensing and wildland fuels science fields. Along these lines, a series of specialized “onramps” are envisioned to enable rapid incorporation of detailed data for specific areas. FastFuels is a work in progress – we will update this website frequently to provide the wildland fire community with updates on our progress.

FastFuels is still in development so findings at this point are preliminary. However, here are a few milestones so far:

  • FastFuels 3D fuels data generation has been carried out for several large areas, collectively comprising more than tens of millions of acres of land.
  • FastFuels currently produces input data suitable for use with QUIC-Fire (Linn et al 2020). Export processes are in progress for HIGRAD/FIRETEC (Linn et al 2002) and the Fire Dynamics Simulator (FDS, Mell et al 2009).
  • QUIC-Fire simulations usings FastFuels data have been successfully carried out for selected test landscapes.
  • FastFuels provides unique capabilities for visualization of wildland fuels. In conjunction with 3D fire modeling, these tools offer new possibilities for firefighter training, incident reviews etc.
  • Fall 2021 -- Working with our partners, our FastFuels team is part of a larger recently funded NSF project linking fuel mapping, fire modeling, big data and Artificial Intelligence to open new possibilities in fuel and fire management. This project, called the WiFIRE commons, is using supercomputing facilities at the San Diego Supercomputing Center to produce FastFuels data as seamless 3D voxels over large areas. You can view this data here: -- to check out FastFuels data, navigate in the map area to a forested area of interest. Then, using the themes icon in the upper right corner, turn on the “USFS FastFuels 3D” data layer. Click on the map to see an interactive 3D display of FastFuels data.
  • November 2021 – Holtz Forestry, led by Dr. Lucas Wells, is one of our most critical partners in the FastFuels development. Check out their FastFuels webpage here:
  • We will keep you posted with new developments!

Related Projects:

Audio and Video

Video file
FastFuels Example Data

This animation illustrates a FastFuels data tile, containing terrain and forest fuels data, for an area of several square kilometers. Different colors represent different species.

Video file
FastFuels-QuicFire demo.mp4

This animation shows a 3D fire simulated with QUIC-Fire using FastFuels data.

Select Publications & Products

This paper provides a good overview of 3D fire models and their potential applications.

Hoffman, Chad M.; Sieg, Carolyn H.; Linn, Rodman R.; Mell, William; Parsons, Russell A.; Ziegler, Justin P.; Hiers, J. Kevin. 2018. Advancing the science of wildland fire dynamics using process-based models. Fire. 1(2): 32.

These two papers provide some background for the underlying logic used in FastFuels. FastFuels streamlines elements of both FuelManager and STANDFIRE, a prototype 3D fuel modeling platform

Pimont, Francois; Parsons, Russell; Rigolot, Eric; Coligny, Francois de; Dupuy, Jean-Luc; Dreyfus, Philippe; Linn, Rodman R. 2016. Modeling fuels and fire effects in 3D: Model description and applications. Environmental Modelling and Software. 80: 225-244.

Parsons, Russell A.; Pimont, Francois; Wells, Lucas; Cohn, Greg; Jolly, W. Matt; de Coligny, Francois; Rigolot, Eric; Dupuy, Jean-Luc; Mell, William; Linn, Rodman R. 2018. Modeling thinning effects on fire behavior with STANDFIRE. Annals of Forest Science. 75(1):1-10

This paper describes the QUIC-Fire model.

Linn, R.R.; Goodrick, S.L.; Brambilla, S.; Brown, M.J.; Middleton, R.S.; O'Brien, J.J.; Hiers, J.K. 2020. QUIC-fire: A fast-running simulation tool for prescribed fire planning. Environmental Modelling & Software. 125: 104616-.