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Type: Journal Article
Author(s): Miguel G. Cruz; Martin E. Alexander; Ronald H. Wakimoto
Publication Date: 2004

The unknowns in wildland fire phenomenology lead to a simplified empirical model approach for predicting the onset of crown fires in live coniferous forests on level terrain. Model parameterization is based on a data set (n=71) generated from conducting outdoor experimental fires covering a significant portion of the spectrum of burning conditions associated with the initiation of crown fires. A logistic model is developed to predict the likelihood of crown fire occurrence based on three fire environment variables, namely the 10-m open wind speed, fuel strata gap (equivalent to live crown base height in some stands), estimated moisture content of fine dead fuels, and one fire-behavior descriptor-surface fuel consumption. The model correctly predicts 85% of the cases in the data set used in its development, and the receiver operating characteristic statistic is 0.94. The model is evaluated for its sensitivity to its inputs, and its behavior is compared with other models used in decision support systems to operationally predict crown fire initiation. The results of a limited test of the model against two independent experimental fire data sets for distinctly different fuel complexes is encouraging.

[This publication is referenced in the "Synthesis of knowledge of extreme fire behavior: volume I for fire managers" (Werth et al 2011).]

Online Links
Citation: Cruz, Miguel G.; Alexander, Martin E.; Wakimoto, Ronald H. 2004. Modeling the likelihood of crown fire occurrence in conifer forest stands. Forest Science 50(5):640-658.

Cataloging Information

Fire Behavior    Fuels    Models
Alaska    California    Eastern    Great Basin    Hawaii    Northern Rockies    Northwest    Rocky Mountain    Southern    Southwest    International    National
Partner Sites:
  • CFIS - Crown Fire Initiation and Spread System
  • crown fire
  • crown fire initiation
  • crowning
  • environmental management
  • experimental fire
  • fire behavior prediction
  • forest fires
  • forest management
  • forest resources
  • logistic model
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Record Maintained By: FRAMES Staff (
FRAMES Record Number: 3831