Canadian Forest Service Publications

Forecasting Forest Inventory Using Imputed Tree Lists for LiDAR Grid Cells and a Tree-List Growth Model. 2018. Lamb, S.M.; MacLean, D.A.; Hennigar, C.R.; Pitt, D.G. Forests 9(4):167.

Year: 2018

Issued by: Great Lakes Forestry Centre

Catalog ID: 39230

Language: English

Availability: PDF (download)

Available from the Journal's Web site.
DOI: 10.3390/f9040167

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Plain Language Summary

A method to forecast forest inventory variables derived from light detection and ranging (LiDAR) would increase the usefulness of such data in future forest management. We evaluated the accuracy of forecasted inventory from imputed tree lists for LiDAR grid cells (20 × 20 m) in spruce plantations and tree growth predicted using a locally calibrated tree-list growth model. To demonstrate the novel application of this method for operational management decisions, annual commercial thinning was planned at grid-cell resolution from 2018–2020 using forecasted inventory variables and commercial thinning eligibility rules.