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): Emilie Grossmann; Janet Ohmann; James Kagan; Heather May; Matthew Gregory
    Date: 2010
    Source: Gap Analysis Bulletin. 17: 16-22
    Publication Series: Scientific Journal (JRNL)
    Station: Pacific Northwest Research Station
    PDF: View PDF  (2.53 MB)

    Description

    New methods for predictive vegetation mapping allow improved estimations of plant community composition across large regions. Random Forest (RF) models limit over-fitting problems of other methods, and are known for making accurate classification predictions from noisy, nonnormal data, but can be biased when plot samples are unbalanced. We developed two contrasting maps of forested ecological systems in the western Oregon Cascades ecoregion based on (a) RF and (b) RF with a bias adjustment. The methods had similar overall accuracy but different strengths and weaknesses. Both methods predicted dominant systems well. For systems with small sample sizes, accuracy was lower and differed more between methods. The bias adjustment process improved accuracy for minor systems with only minor impact on overall accuracy. The unadjusted RF model severely overestimated the area of abundant systems and underestimated minor classes. The adjustment process improved the areal estimates but did not completely eliminate the bias problem. Choice of methods and resulting maps should be based on objectives of the particular project.

    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

    Grossmann, E.; Ohmann, J.; Kagan, J.; May, H.; Gregory, M. 2010. Mapping ecological systems with a random foret model: tradeoffs between errors and bias. Gap Analysis Bulletin. 17: 16-22.

    Keywords

    Biogeography, environmental gradients, vegetation types, landscape analysis, vegetation modeling

    Related Search


    XML: View XML
Show More
Show Fewer
Jump to Top of Page