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    Many regional (extensive) forest surveys use clusters of subplots or prism points to reduce survey costs. Two common methods of handling clusters that straddle stand boundaries entail: (1) moving all subplots into a single forest cover type, or (2)"averaging" data across multiple conditions without regard to the boundaries. these methods result in biased estimates of tree attributes (volume/acre, basal area/acre, etc.) and/or misclassification of discrete stand-area attributes (cover type, stand size, etc.). To circumvent the problems encountered with these approaches, a technique is described whereby subplots always are arranged in a fixed pattern, and trees are tallied by the cover type or "condition class" in which they occur. This involves mapping boundaries that bisect a subplot and proportioning subplot area by condition class. field and calculation procedures leading to unbiased estimates are given.

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    Scott, Charles T.; Bechtold, William A. 1995. Techniques and computations for mapping plot clusters that straddle stand boundaries. For. Sci. Monogr., Vol. 31: 46-61


    Forest inventory, cluster sampling

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