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Effects of uncertainty in upper-stem diameter information on tree volume estimatesAuthor(s): James A. Westfall; Ronald E. McRoberts; Philip J. Radtke; Aaron R. Weiskittel
Source: European Journal of Forest Research
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionAlmost all relevant data in forestry databases arise from either field measurement or model prediction. In either case, these values have some amount of uncertainty that is often overlooked when doing analyses. In this study, the uncertainty associated with both measured and predicted data was quantified for upper-stem diameter at 5.27 m. This uncertainty was propagated through a tree taper model into predictions of individual-tree volume. The effects of uncertainty on individual-tree volume predictions and population estimates of total volume were assessed. Generally, when little or no systematic measurement deviation was present, less uncertainty was associated with field-measured diameters compared to model predictions. However, diameters predicted from a model were preferred when systematic deviations in field measurement exceeded approximately 0.2 cm. Comparisons of results obtained from an alternative taper model showed that more precise estimates of population totals might be obtained without upper-stem diameter information. Upper-stem diameter information increases the prediction accuracy of individual- tree volume, and thus, models using this information may be preferable in applications such as timber sales containing high-value trees. Due to the various factors that influence measurement and modeling uncertainty, foresters are encouraged to make similar evaluations in the context of their specific activities.
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CitationWestfall, James A.; McRoberts, Ronald E.; Radtke, Philip J.; Weiskittel, Aaron R. 2016. Effects of uncertainty in upper-stem diameter information on tree volume estimates. European Journal of Forest Research. 135(5): 937-947. https://doi.org/10.1007/s10342-016-0985-4.
KeywordsError propagation, Measurement variability, Taper model, Quality assurance, Forest inventory
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