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Design-unbiased point-to-object sampling on lines, with applications to areal sampling

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Abstract

Sampling methods that depend on the distance between a sample point and a fixed number of objects, such as trees or downed logs, have often been proposed in the forestry and ecology literature. However, such methods have been biased when objects are not distributed with complete spatial randomness, have required difficult field procedures (such as measuring the position of out-of-sample objects), or both. Here a new approach based on measurement of the distance to objects along sample lines is proposed. The approach does not require measuring the position of out-of-sample objects, and its design-unbiased estimators require only simple arithmetic. Furthermore, because many useful sampling procedures can be related back to sampling on a line, the new method leads quickly to sampling procedures applicable when objects are distributed in a two-dimensional region. These include, among others, fixed-count approaches to line intersect sampling, a new approach to variable-area transect sampling, and a density-adapted variable sector sampling method.

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Acknowledgements

Thomas B. Lynch and Timothy G. Gregoire provided valuable comments on an earlier version of the manuscript. The Associate Editor and two anonymous reviewers gave helpful suggestions. Partial funding for this work was provided by the New Hampshire Agricultural Experiment Station. This is Scientific Contribution Number 2773. This work was supported by the USDA National Institute of Food and Agriculture McIntire–Stennis Project 1007007.

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  1. Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, 03824, USA

    Mark J. Ducey

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Correspondence to Mark J. Ducey.

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Communicated by Arne Nothdurft.

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Ducey, M.J. Design-unbiased point-to-object sampling on lines, with applications to areal sampling. Eur J Forest Res 137, 367–383 (2018). https://doi.org/10.1007/s10342-018-1109-0

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