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Saving the forest by reducing fire severity: Selective fuels treatment and scheduling

Church, R.L. and Niblett, M.R. and O'Hanley, J.R. and Middleton, R. and Barber, K. (2015) Saving the forest by reducing fire severity: Selective fuels treatment and scheduling. In: Eiselt, H.A. and Marianov, V., eds. Applications of location analysis. Springer, pp. 173-190. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:48601)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.

Abstract

Wildfire is a natural process which can lead to a variety of conditions in a forested landscape, some quite destructive. Whatever the cause of a fire, no one questions that destructive fires often occur during certain weather events where litter (woody debris from trees) and ladder fuels are abundant. The US Forest Service has implemented a program to reduce litter and ladder fuels along with thinning of stands in order to mitigate the extent and severity of fires, especially in areas surrounding critical habitat. Fuels reduction/treatment plans are expensive and therefore must be planned over a period of years, often two decades or more. This chapter presents an application of a location-scheduling model which has been developed for the US Forest Service to determine when and where fuels treatments are to be implemented. The model itself is an integer linear programming problem, which has been embed-ded in a decision support system called iFASST. This modeling system is quite flexible, and because of its flexibility has now been used in many of the National Forests in California.

Item Type: Book section
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
S Agriculture > SD Forestry
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Jesse O'Hanley
Date Deposited: 21 May 2015 14:57 UTC
Last Modified: 05 Nov 2024 10:32 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/48601 (The current URI for this page, for reference purposes)

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