Modeling a historic forest fire using GIS and FARSITE

Autori

  • Thomas M Williams Baruch Institute of Coastal Ecology and Forest Science Clemson University
  • Brian J Williams Baruch Institute of Coastal Ecology and Forest Science Clemson University
  • Bo Song Baruch Institute of Coastal Ecology and Forest Science Clemson University

Parole chiave:

19th century forest fire, Fire visualization, mega-fire, Hinckley MN

Abstract

The September 1, 1894 fire near Hinckley, Minnesota has well documented accounts from many survivors that allow position of the flame front to be established for a number of times throughout the fire. FARSITE is a modern fire spread rate simulation model requiring spatial layers of elevation, slope aspect, timber type, and derived layers of fuel type, crown cover, stand height, crown base height, crown bulk density, duff and coarse woody debris. We combined present GIS data, historical map data, and present ecosystem properties to provide data needed for these layers. GIS output of FARSITE spread predictions were used to match flame front position to eyewitness accounts and model parameters were altered to produce a flame front location and time that matched eyewitness location and timing.

Biografie autore

  • Thomas M Williams, Baruch Institute of Coastal Ecology and Forest Science Clemson University

    Professor Emeritus

    Department of Forest and Natural Resources

  • Brian J Williams, Baruch Institute of Coastal Ecology and Forest Science Clemson University
    Baruch Institute of Coastal Ecology and Forest Science
    Reseach Tecnician
  • Bo Song, Baruch Institute of Coastal Ecology and Forest Science Clemson University

    Assocaite Professor

    Department of Forest and Natural Resources

Dowloads

Pubblicato

2014-09-30

Fascicolo

V. 6 N. 2: MCFNS September 30, 2014

Sezione

Special Section on the Southern Forestry GIS Conference

Licenza

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Come citare

Williams, T. M., Williams, B. J., & Song, B. (2014). Modeling a historic forest fire using GIS and FARSITE. Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS), 6(2), 80-88 (9). https://mcfns.com/index.php/Journal/article/view/6.9

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