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Design of Successive Forest Inventories: Optimization by Convex Mathematical Programing

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Convex mathematical programing is proposed as a method of optimally allocating forest inventory sampling resources under different sampling plans to meet specified precision requirements on several variables. Results of a sensitivity analysis under sampling with partial replacement shows the response of the solution to changing inputs when each restriction becomes limiting. The solutions illustrate that the optimum replacement fraction can vary from complete remeasurement to large replacement fractions depending upon the specified precision levels, the population parameters, and the relative costs of obtaining information. Forest Sci. 20:117-127.
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Keywords: Forest surveys; forest sampling designs; inventory planning

Document Type: Journal Article

Affiliations: Assistant Professor, Department of Forestry, Iowa State University, Portland, Oregon

Publication date: 1974-06-01

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.

    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
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