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Spatial optimization of operationally relevant large fire confine and point protection strategies: Model development and test cases

Author(s): Yu Wei, Matthew P. Thompson, Jessica R. Haas, Gregory K. Dillon, Christopher D. O'Connor
Year Published: 2018
Description:

This study introduces a large fire containment strategy that builds upon recent advances in spatial fire planning, notably the concept of potential wildland fire operation delineations (PODs). Multiple PODs can be clustered together to form a “box” that is referred as the “response POD” (or rPOD). Fire lines would be built along the boundary of an rPOD to contain a large fire. Assets such as communities and infrastructure within an rPOD could be protected through “point zone protection.” We develop a mixed integer program model to optimally aggregate PODs into an rPOD with an objective of coordinating containment and point protection to maximize net value change under different fire weather scenarios and resource availability constraints. This optimization framework leverages emerging fire risk assessment and response planning methods by considering factors that drive selection of the optimal rPOD including fire-related benefits and losses, the fire line construction effort required to contain fire, and the point protection requirement within the rPOD to reduce asset losses. The model could be used to support prefire assessment and planning, training, and incident response decisions. We use a portion of the Lolo National Forest in western Montana, U.S.A., as a study site for demonstration.

Citation: Wei, Yu; Thompson, Matthew P.; Haas, Jessica R.; Dillon, Gregory K.; O’Connor, Christopher D. 2018. Spatial optimization of operationally relevant large fire confine and point protection strategies: Model development and test cases. Canadian Journal of Forest Research. 48: 1-14. dx.doi.org/10.1139/cjfr-2017-0271
Topic(s): Human Dimensions of Fire Management, Organizational Effectiveness, Risk
Ecosystem(s): None
Document Type: Book or Chapter or Journal Article
NRFSN number: 17539
Record updated: Apr 25, 2018