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FlamMap | Print |

Image: FlamMap logoFlamMap is capable of calculating surface and crown fire behaviors, moisture of fine dead fuels over an entire landscape, simulating fire growth for constant conditions under a minimum travel time (MTT) algorithm, conduct fuel treatment optimization modeling (TOM) for delaying the growth of large fires, and calculate the burn probability for a landscape.

 flammap_smallAll FlamMap calculations are assumed to be under constant weather and fuel moisture conditions. All outputs generated by FlamMap are in either a vector or raster output and can be viewed in FlamMap or exported for use in a GIS, image, or word processor. While FlamMap uses the same spatial and tabular data as FARSITE, it is not a replacement for FARSITE or a complete fire growth simulation model as there is no temporal or contagion component in FlamMap.


Mark Finney, Research Forester


Rob Seli; Rocky Mountain Research Station (RMRS); Wildland Fire Management RD&A; Boise, Idaho
Stu Brittain; Systems for Environmental Management; Missoula, Montana
Chuck McHugh; RMRS; Missoula Fire Sciences Laboratory


The FlamMap project was begun in 2000 with the objective of extending the utility of current operational wildland fire behavior systems to the landscape-level where the necessary inputs have been mapped using geographic information systems (GIS). FlamMap is designed to examine the spatial variability in fire behavior assuming that fuel moisture, wind speed and wind direction are held constant in time thereby allowing for more direct comparison of fuel treatment effects. FlamMap’s features allow the user to easily characterize fuel hazard and potential fire behavior, as well as investigate fire movement and fuel treatment interactions.


With the release of FlamMap5 (July 2012) previous versions of the program will no longer be supported. This new release will improve upon some of the existing features and address bugs discovered within past versions. With this new release the program is now available in both 32-bit and 64-bit Operating System versions. The program and user documentation is distributed free over the internet (firemodels.org). The program is officially a national system and is supported by the Fire Applications Support Desk in Boise.


Landscape level simulations using FlamMap have shown to be very practical and are widely used in support of wildland fire operations and fuel treatment planning. FlamMap is parallelized to operate efficiently on multiple processors which work well on modern multi-core CPUs. To date, FlamMap has been taught in regional workshop settings and in training sessions associated with national conferences. FlamMap will be incorporated into a new more comprehensive training course (to be offered in spring 2009) referred to as S-495. FlamMap is used internationally because of the general input requirements.


Image: Joint Fire Sciences Program logoOriginal funding for developing FlamMap was obtained from the Forest Service, Bureau of Land Management, and through the Joint Fire Science Program.

User support and bug fixes are supported by the U.S. Forest Service.


The technical documentation of the simulation structure has been published, and an electronic help system and tutorial are provided with the software. The program and user documentation is distributed free over the internet (firemodels.org).

Finney, M.A. 1998. FARSITE: Fire Area Simulator – model development and evaluation. USDA For. Serv. Res. Pap. RMRS-RP-4. 47p.

Finney, M.A. 2001. Design of regular landscape level fuel treatment patterns for modifying fire growth and behavior. For. Sci. 47(2):219-228.

Finney, M.A. 2002. Fire growth using minimum travel time methods. Can. J. For. Res. 32(8):1420-1424.

Finney, M.A. 2004. Chapter 9, Landscape fire simulation and fuel treatment optimization. IN: J.L. Hayes, A.A. Ager, J.R. Barbour (tech. eds). Methods for integrated modeling of landscape change: Interior Northwest Landscape Analysis System. PNW-GTR-610. p 117-131.

Finney, M.A. 2006. An overview of FlamMap modeling capabilities. In: P.L. Andrews, B.W. Butler (comps.). Fuels Management – How to measure success: Conference Proceedings. RMRS-P-41. p 213-219.

Finney, M.A. 2007. A computational method for optimizing fuel treatment locations. Intl. J. Wildl. Fire. 16:702-711.

Finney, M.A., R.C. Seli, C.W. McHugh, A.A. Ager, B.Bahro, and J.K. Agee. 2007. Simulation of long-term landscape-level fuel treatment effects on large wildfires. Intl. J. Wildl. Fire. 16:712-727.

Stratton, Rick D. Assessing the Effectiveness of Landscape Fuel Treatments on Fire Growth and Behavior pdf_iconJournal of Forestry. Pp 32-40 October/November 2004

Stratton, Rick D. Guidance on Spatial Wildland Fire Analysis: Models, Tools, and Techniques. USDA Forest Service Gen.Tech.Rep RMRS-GTR-183. 2006