Modeling Containment of Large Wildfires Using Generalized Linear Mixed-Model Analysis
Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and individual fires were random effects. Changes in daily fire size from 306 fires occurring in years 2001‐2005 were processed to identify intervals of high spread from those of low spread. The model was tested against independent data from 140 fires in 2006. The analysis suggested that containment was positively related to the number of consecutive days during which the fire grew little and the number of previous intervals. Containment probability was negatively related to the length of intervals during which the fire exhibited high spread and the presence of timber fuel types, but fire size was not a significant predictor. Characterization of containment probability may be a useful component of cost-benefit analysis of large fire management and planning systems.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Publication date: 2009-06-01
More about this publication?
- Important Notice: SAF's journals are now published through partnership with the Oxford University Press. Access to archived material will be available here on the Ingenta website until March 31, 2018. For new material, please access the journals via OUP's website. Note that access via Ingenta will be permanently discontinued after March 31, 2018. Members requiring support to access SAF's journals via OUP's site should contact SAF's membership department for assistance.
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
Other SAF Publications
- Submit a Paper
- Membership Information
- Author Guidelines
- Ingenta Connect is not responsible for the content or availability of external websites