Skip to Main Content
U.S. Forest Service
Caring for the land and serving people

United States Department of Agriculture

Home > Search > Publication Information

  1. Share via EmailShare on FacebookShare on LinkedInShare on Twitter
    Dislike this pubLike this pub
    Author(s): Jacob Strunk; Hailemariam Temesgen; Hans-Erik Andersen; James P. Flewelling; Lisa Madsen
    Date: 2012
    Source: Canadian Journal of Remote Sensing. 38(5): 644-654
    Publication Series: Scientific Journal (JRNL)
    Station: Pacific Northwest Research Station
    PDF: View PDF  (743.0 KB)

    Description

    Using lidar in an area-based model-assisted approach to forest inventory has the potential to increase estimation precision for some forest inventory variables. This study documents the bias and precision of a model-assisted (regression estimation) approach to forest inventory with lidar-derived auxiliary variables relative to lidar pulse density and the number of sample plots. For managed forests on the Lewis portion of the Lewis-McChord Joint Base (35 025 ha, 23 290 forested) in western Washington state, we evaluated a regression estimator for combinations of pulse density (.05–3 pulses/m2) and sample size (15–105 plots) to estimate five forest yield variables: basal area, volume, biomass, number of stems, and Lorey’s height. The results indicate that there is almost no loss in precision in using as few as .05 pulses/m2 relative to 3 pulses/m2. We demonstrate that estimation precision declined quickly for reduced sample sizes (as expected from sampling theory); but of more importance we demonstrate that sample size has a dramatic effect on the validity of inferences. Our investigations indicate that for our test dataset that central limit theorem based confidence intervals were too small on average for sample sizes smaller than 55. The results from this study can aid in identifying design components for forest inventory with lidar which satisfy users’ objectives.

    Publication Notes

    • You may send email to pnw_pnwpubs@fs.fed.us to request a hard copy of this publication.
    • (Please specify exactly which publication you are requesting and your mailing address.)
    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

    Citation

    Strunk, Jacob; Temesgen, Hailemariam; Andersen, Hans-Erik; Flewelling, James P.; Madsen, Lisa. 2012. Effects of lidar pulse density and sample size on a model-assisted approach to estimate forest inventory variables. Canadian Journal of Remote Sensing. 38(5): 644-654. https://doi.org/10.5589/m12-052.

    Cited

    Google Scholar

    Keywords

    inventory, lidar, model-assisted

    Related Search


    XML: View XML
Show More
Show Fewer
Jump to Top of Page
https://www.fs.usda.gov/treesearch/pubs/54332