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Bivariate Extreme Value Modeling of Wildland Fire Area and Duration

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Area burned and fire duration as two aspects of large wildland fires were assessed by extreme value statistics in this study. A data set of 64,474 fire records from Mississippi between January 1991 and December 2007 was used in the assessment. Large fires occurred mainly between February and May, in the Southeastern Region, and started as debris and incendiary fires. Area burned showed more extremal properties than fire duration. A positive and moderate association existed between area and duration of wildland fires. In the univariate analyses, the generalized Pareto distribution with a heavy tail characterized both the area burned and fire duration well. The bivariate extreme value analyses found that the asymmetric negative logistic distribution provided the best fit to the data. Incorporating the dependence between area and duration into the bivariate extreme value models and forecast of return levels generated more conservative estimates than those from the univariate analyses. The techniques adopted in this study can be applied to analogous data sets for other regions. The information on fire patterns and extremal behavior could be beneficial to forest planning and management.

Keywords: Pareto distribution; Pickands dependence; extreme value statistics; return level; spatial density

Document Type: Research Article


Publication date: 2013-12-06

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
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