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A mirage boundary correction method for distance sampling

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Several boundary overlap correction procedures have been proposed for forest sampling with fixed-radius circular plots and point sampling but there has been no corresponding method for n-tree distance sampling. n-tree distance sampling samples the n trees closest to a randomly located sample point. Estimators of forest parameters such as density have been proposed based on this sample. However, in forest inventory applications, it is possible that the randomly located sample point may fall close to a tract boundary. In this case, selection of n trees closest to the sample point and within the tract boundary may contribute to biased estimates. It is proposed to correct this using an approach similar to the mirage method that has often been applied to point sampling and fixed-radius plot sampling. This is accomplished by establishing a mirage sample point outside the tract boundary at a distance equal to that between the original interior point and the boundary on a line perpendicular to the boundary. Then the n sample trees closest to either the original sample point or the mirage point are selected for use in one of the n-tree sampling estimation methods.

Document Type: Research Article


Publication date: 2012-02-11

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  • Published since 1971, this monthly journal features articles, reviews, notes and commentaries on all aspects of forest science, including biometrics and mensuration, conservation, disturbance, ecology, economics, entomology, fire, genetics, management, operations, pathology, physiology, policy, remote sensing, social science, soil, silviculture, wildlife and wood science, contributed by internationally respected scientists. It also publishes special issues dedicated to a topic of current interest.
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