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Evaluating the Adequacy of a Fire-Danger Rating Network

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Historically fire-danger rating stations have been located by convenience rather than design. The resulting collection of stations may or may not sample the data the fire manager needs to get a useful picture of the variability of fire danger in his area. The objectives of this analysis were to determine how well an existing network sampled the fire danger and to determine the station spacing for an optimum network. The method of optimum interpolation was used to analyze the burning index and ignition component computed from the National Fire-Danger Rating System, assuming fuel model G and using weather data from 28 Federal and State fire-danger stations and 9 NOAA/NWS stations in Minnesota, Wisconsin, and upper Michigan. Two indicators of performance were studied: the coefficient of variation of interpolation estimated from distance-correlation relationships, and the station spacing necessary to limit interpolation errors of the burning index to less than ±5. In the spring, minimum interpolation errors ranged from 15 to 20 percent of the station mean, increasing to 20 to 30 percent in the summer and decreasing only slightly again in the fall. The station spacing required to limit the interpolation error to a range of ±5 burning index units was closest in the spring and farthest in the summer. Strategies for refining fire-danger network design are discussed. Forest Sci. 30:1045-1058.
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Keywords: Fire danger; correlation; network design; optimal interpolation; structure function

Document Type: Journal Article

Affiliations: Principal Meteorologist, USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 240 W. Prospect, Fort Collins, CO 80526

Publication date: 1984-12-01

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    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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