Skip to page content
USDA Forest Service

Research & Development Treesearch

Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help - We Participate  Government Made Easy

Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

View PDF (2.5 MB)

Title: Mapping ecological systems with a random foret model: tradeoffs between errors and bias

Author: Grossmann, Emilie; Ohmann, Janet; Kagan, James; May, Heather; Gregory, Matthew;

Date: 2010

Source: Gap Analysis Bulletin. 17: 16-22

Publication Series: Scientific Journal (JRNL)

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.

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

Publication Notes:

  • 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.



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.


 [ Get Acrobat ]  Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.