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Notes: Estimation of Log Volume by Importance Sampling

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Abstract:

Importance sampling is proposed as a technique for estimating log volume that eliminates the bias of conventional methods arising from irregular log taper. In a trial of the technique, the average relative sampling error for individual logs, based on a measurement of one cross-section per log, was 5.2%. To estimate an aggregate volume, a two-stage sampling procedure is suggested in which importance sampling constitutes the second stage. Optimal sampling strategy is discussed briefly. Forest Sci. 32:1073-1078.

Keywords: Monte Carlo integration; proxy function

Document Type: Miscellaneous

Affiliations: Assistant Professor of Forest Biometrics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061

Publication date: 1986-12-01

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.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 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
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