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 (352 KB bytes)

Title: A hierarchical linear model for tree height prediction.

Author: Monleon, Vicente J.;

Date: 2003

Source: In: 2003 Joint Statistical Meetings - Section on Statistics & the Environment: 2865-2869

Publication Series: Scientific Journal (JRNL)

Description: Measuring tree height is a time-consuming process. Often, tree diameter is measured and height is estimated from a published regression model. Trees used to develop these models are clustered into stands, but this structure is ignored and independence is assumed. In this study, hierarchical linear models that account explicitly for the clustered structure of the data are compared with model forms currently used in forestry. The data consist of 1433 Douglas firs from 99 Oregon stands measured in 2000, and an independent evaluation dataset of similar size measured in 2001. Overall model performance improved substantially if the stand random effect could be predicted: root mean squared error (RMSE) decreased from 4.91 m (current models) to less than 3.73 m (hierarchical model, 1 tree sampled). However, if the random effect could not be estimated, the improvement was small (RMSE 4.45 m). The within-stand relationship between height and diameter was different from that between stands. As a result, the random and fixed components of the model are confounded. A mixed model that did not account for this problem performed worse than the model that assumed an independent data structure.

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.



Monleon, Vicente J. 2003. A hierarchical linear model for tree height prediction. In: 2003 Joint Statistical Meetings - Section on Statistics & the Environment: 2865-2869


 [ 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.