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FlamMap

FlamMap is a fire analysis desktop application that runs in a 64-bit Windows Operating System environment. It can simulate potential fire behavior characteristics (spread rate, flame length, fireline intensity, etc.), fire growth and spread and conditional burn probabilities under constant environmental conditions (weather and fuel moisture). With the inclusion of FARSITE it can now compute wildfire growth and behavior for longer time periods under heterogeneous conditions of terrain, fuels, fuel moistures and weather.)

Image: Flammap logo

The FlamMap fire mapping and analysis system (Finney 2006) describes potential fire behavior for constant environmental conditions (weather and fuel moisture). Fire behavior is calculated for each pixel within the landscape file independently. Potential fire behavior calculations include surface fire spread, flame length, crown fire activity type, crown fire initiation, and crown fire spread. Dead fuel moisture and conditioning of dead fuels in each pixel based on slope, shading, elevation, aspect, and weather. With the inclusion of FARSITE, FlamMap can now compute wildfire growth and behavior with detailed sequences of weather conditions.

The FlamMap fire mapping and analysis system includes FARSITE (Finney 1998, 2004) and FlamMap BASIC (Finney 2006), Minimum Travel Time (MTT, Finney 2002, 2006), Treatment Optimization Model (Finney 2001, 2006, 2007), and Conditional Burn Probability (Finney 2005, 2006). It incorporates the following fire behavior models:

  • Rothermel's (1972) surface fire spread model,
  • Van Wagner's (1977) crown fire initiation model,
  • Rothermel's (1991) crown fire spread model,
  • Albini's (1979) spotting model,
  • Finney’s (1998) or Scott and Reinhardt’s (2001) crown fire calculation method, and
  • Nelson's (2000) dead fuel moisture model. This allows conditioning of dead fuels in each pixel based on slope, shading, elevation, aspect, and weather.

Because environmental conditions remain constant when using FlamMap, MTT, Burn Probability, and TOM it will not simulate temporal variations in fire behavior caused by weather and diurnal fluctuations as FARSITE does. Nor will it display spatial variations caused by backing or flanking fire behavior. These limitations need to be considered when viewing FlamMap output using these models in an absolute rather than relative sense. However, these outputs are well-suited for landscape level comparisons of fuel treatment effectiveness because fuel is the only variable that changes. Outputs and comparisons can be used to identify combinations of hazardous fuel and topography, aiding in prioritizing fuel treatments.

The FlamMap software creates a variety of vector and raster maps of potential fire behavior characteristics (for example, spread rate, flame length, crown fire activity) and environmental conditions (dead fuel moistures, mid-flame wind speeds, and solar irradiance) over an entire landscape or for specific modeling applications these same outputs are limited to the simulation footprint (MTT and FARSITE). These raster maps can be viewed in FlamMap or exported for use in a GIS, or image format.

The FlamMap software also creates a variety of vector outputs specific to each modeling system within the application. Gridded wind vectors are produced whenever WindNinja is used within the application and information on spotting (tabular and shapefile format) are also created. MTT creates MTT flow paths and MTT Arrival Contours. Within FARSITE, Wind and Spread Vectors, and FARSITE Perimeters are also produced.

Required geospatial Landscape Data

The FlamMap program requires eight geospatial data layers to create a valid landscape file (.LCP)

  • Topographic (Elevation, Slope, Aspect)
  • Fire Behavior Fuel Models
  • Forest Canopy Cover
  • Forest Canopy Height
  • Forest Canopy Base Height
  • Forest Canopy Bulk Density

Required geospatial data for use in FlamMap for the Continental United States, Alaska, and Hawaii can be accessed from the LANDFIRE Program: https://www.landfire.gov/index.php.

FlamMap also requires information on dead and live fuel moistures, weather information, and wind speed and direction. WindNinja has been incorporated into FlamMap allowing for the use gridded wind information generated within the program for any simulation. Gridded winds using WindNinja’s full mass and momentum solver can also be used in any simulation as well. Please see the WindNinja page for more information.

Training

An online tutorial is included in the online Help and example data sets are provided with the installation download. Currently, no formal training course exists for FlamMap.

Technical Support

The first level of technical support is provided through your local support channels. Second level technical support is provided by the USDA Forest Service Fire and Aviation Interagency Incident Applications (IIA) HelpDesk.

HelpDesk Contact Information:

The IIA HelpDesk is available for help with software issues only and cannot answer fire behavior modeling questions.

Image 1: Using FlamMap is different from most Windows® applications. In addition to utilizing menus, commands, and toolbar buttons, FlamMap uses an expanding tree structure and context menus in the left hand pane of the project window to guide you through your work. The right hand pane of the Project window displays the active theme selected in the left hand pane. This display can be zoomed, colors changed, legends displayed, etc.

Image: FlamMap Project window

Image 2: A variety of options are available to display and export Farsite Visible Perimeters

  • All Perimeters: Will display and export every perimeter based on the Farsite Timestep value in the Farsite Model settings tab.
  • (A) By Farsite Timestep Multiple: Allows for displaying perimeters based on some multiple of the total available Farsite timesteps. The default value is 1 which is the equivalent of All Perimeters. The user can define this on multiples of the available timesteps, such as 6, 12, 24. Exceeding the total number of available timesteps will show only the last and final perimeter for the simulation is set at multiples of 6.
  • (B) By Burn Period: Will display the perimeters at the end of each specified Burn Period as set in the Burn Periods in the Model Settings tab shows two Burn Periods.
  • (C) Final Perimeter Only: Will display only the last perimeter from the last specified Burn Period shows only the last and final perimeter.

Farsite image perimeter

Image 3: Burn Probabilities and Minimum Travel Time (MTT) Perimeters FlamMap can use either random ignitions or a user supplied ignition file to determine burn probabilities across a given landscape under a constant set of fuels, wind and weather conditions. The following example displays the simulation results for 100 random ignitions across a landscape along with their respective burn probabilities.

Image 2: simulation results for 100 random ignitions

Image 4: Barrier Files- FlamMap can incorporate barriers into MTT analyses. Barriers can either be filled or unfilled. The following two examples display the effects of using these two barrier types. Notice the effect of spotting in both of these examples. In both examples the MTT Arrival Time (red to yellow shading) and MTT Flow paths (black lines) are displayed. Filled Barrier - Notice how the fire burns up to the edge of the filled barrier (red polygon) and then spots across it. The fire also flanks around the filled barrier to the west and then continues spreading to the northwest.

Image 3: Filled Barrier

Image 5: Unfilled Barrier - Notice how the fire burns up to the edge of the unfilled barrier (red polygon). When a barrier is unfilled the interior can burn yet the perimeter of the unfilled barrier is still resistant to surface fire spread. In this example the fire spreads up to the edge of the barrier and then spots into it in two locations and then spots outside of the unfilled barrier file. The fire also flanks around the filled barrier to the west and then continues spreading to the northwest.

Image 4: Unfilled Barrier

Modified: Sep 25, 2019

Select Publications & Products

Guides for Spatial Fire Behavior Analysis

Stratton, R. D. 2009. Guidebook on LANDFIRE fuels data acquisition, critique, modification, maintenance, and model calibration. General Technical Report RMRS-GTR-220. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. (7,715 KB; 54 pages)

Stratton, R. D. 2006. Guidance on spatial wildland fire analysis: models, tools, and techniques. General Technical Report RMRS-GTR-183. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. (1,558 KB; 15 pages)

Keane, R. E.; Mincemoyer, S. A.; Schmidt, K. M.; Long, D. G.; Garner, J. L. 2000. Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico, [CD-ROM]. General Technical Report RMRS-GTR-46-CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. (490 KB; 131 pages)

Keane, R. E.; Garner, J. L.; Schmidt, K. M.; Long, D. G.; Menakis, J. P., Finney, M. A. 1998. Development of input data layers for the FARSITE fire growth model for the Selway-Bitterroot Wilderness Complex, USA. General Technical Report RMRS-GTR-3. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. (5,873 KB; 66 pages)

Green, K.; Finney, M. A.; Campbell, J.; Weinstein, D.; Landrum, V. 1995. Fire! Using GIS to predict fire behavior. Journal of Forestry 93(5): 21-25. (271 KB; 5 pages)

FlamMap Background Material

Finney, M. A. 1995. FARSITE: A fire area simulator for fire managers. In: Weise, D. R.; Martin, R. E. (tech. coords.). The Biswell Symposium: Fire issues and solutions in urban interface and wildland ecosystems. 1994 February 15-17; Walnut Creek, California. General Technical Report PSW-GTR-158. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station: 55-56. (647 KB; 13 pages)

Finney, M. A. 1998. FARSITE: Fire Area Simulator–model development and evaluation. Research Paper RMRS-RP-4 Revised. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. (1,667 KB; 47 pages)

Finney, M. A. 1999. Mechanistic modeling of landscape fire patterns. In: Mladenoff, D. J. and Baker, W. L. eds. Spatial modeling of forest landscape change: approaches and applications. Cambridge University Press: 186-209.

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. FARSITE: Fire Area Simulator–model development and evaluation. Research Paper RMRS-RP-4 Revised. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. (1,667 KB; 47 pages)

Finney, M. A. 2005. The challenge of quantitative risk analysis for wildland fire. Forest Ecology & Management 211: 97-108.

Finney, M. A. 2006. An overview of FlamMap fire modeling capabilities. In: Fuels management—how to measure success: conference proceedings. 2006 March 28-30; Portland, Oregon. Proceedings RMRS-P-41. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station: 213-220. (647 KB; 13 pages)

Fuel Treatment Location Simulations using FlamMap

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.

Ager, A. A.; Finney, M. A.; Kems, B. K.; Maffei, H. 2007. Modeling wildfire risk to northern spotted owl (Strix occidentalis caurina) habitat in Central Oregon, USA. Forest Ecology and Management 246: 45-56. (2,040 KB; 12 pages)

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

Finney, M. A. 2004. Landscape fire simulation and fuel treatment optimization. In: Hayes, J. L.; Ager, A. A.; Barbour, J. R., tech. ed. Methods for integrating modeling of landscape change: Interior Northwest Landscape Analysis System. General Technical Report PNW-GTR-610. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Station: 117-131. (647 KB; 15 pages)

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

Fire Growth Simulations using FARSITE

Finney, M. A. 2000. Efforts at comparing simulated and observed fire growth patterns. Missoula, MT: Systems for Environmental Management; Final Report INT-95066-RJVA. (71 KB; 20 pages)

Finney, M. A.; Andrews, P. L. 1999. FARSITE: Fire Area Simulator—a program for fire growth simulation. Fire Management Notes 59(2): 13-15. (71 KB; 3 pages)

Finney, M. A.; Andrews, P. L.. 1998. Application and status of the FARSITE fire area simulator. In: Proceedings of the III International Conference on Fire and Forest Meteorology; 1998 November 16-20; Luso, Coimbra-Portugal: 755-760. (4,154 KB; 6 pages)

Finney, M. A.; Andrews, P. L. 1998. The FARSITE Fire Area Simulator: fire management applications and lessons of Summer 1994. In: Close K. and Bartlette R. A.,eds. Fire management under fire (Adapting to Change), Proceedings of the Interior West Fire Council Meeting and Program, International Association of Wildland Fire: 209-215. (9,705 KB; 7 pages)

Finney, M. A. 1995. Fire growth modeling in the Sierra Nevada of California. In: Brown, J. K.; Mutch, R. W.; Spoon, C. W.; and Wakimoto, R. H., eds. Proceedings of a Symposium on Fire in Wilderness and Park Management; 1995 March 30 - April 1; Missoula, MT. (4,424 KB; 3 pages)

Finney, M. A.; Ryan, K. C. 1995. Use of the FARSITE fire growth model for fire prediction in U.S. National Parks. In: Proceedings of the International Emergency Management and Engineering Conference; 1995 May; Sofia Antipolis, France: 183-189. (11,469 KB; 7 pages)

Finney, M. A. 1994. Modeling the spread and behavior of prescribed natural fires. In: Proceedings of the 12th International Conference on Fire and Forest Meteorology. 1993 October 26-28; Jekyll Island, GA. (589 KB; 6 pages)

Fuel Treatment Evaluation using FARSITE

Stratton, R. D. 2004. Assessing the effectiveness of landscape fuel treatments on fire growth and behavior. Journal of Forestry. 102(7): 32-40. (550 KB; 9 pages)

Van Wagtendonk, J. W. 1996. Use of a deterministic fire growth model to test fuel treatments. In: Sierra Nevada Ecosystem Project: Final Report to Congress. Davis, CA: University of California, Centers for Water and Wildland Resources: volume II, chapter 43. (783 KB; 12 pages)

Finney, M. A.; Sapsis, D. B.; Bahro, B. 2002. Use of FARSITE for simulating fire suppression and analyzing fuel treatment economics. In: Symposium on fire and California ecosystems: integrating ecology, prevention and management; 1997 November 17-20, San Diego, CA. (1,132 KB; 16 pages)

Cochrane, M. A.; Moran, C. J.; Wimberly, M. C.; Baer, A. D.; Finney, M. A.; Beckendorf, K. L.; Eidenshink, J.; Zhu, Z. 2012. Estimation of wildfire size and risk changes due to fuels treatments. International Journal of Wildland Fire. 21: 357-367.