Skip to Main Content
Interpretation of forest characteristics from computer-generated images.Author(s): T.M. Barrett; H.R. Zuuring; T. Christopher
Source: Landscape and Urban Planning. 80(4): 396-403
Publication Series: Scientific Journal (JRNL)
PDF: Download Publication (2.0 MB)
DescriptionThe need for effective communication in the management and planning of forested landscapes has led to a substantial increase in the use of visual information. Using forest plots from California, Oregon, and Washington, and a survey of 183 natural resource professionals in these states, we examined the use of computer-generated images to convey information about forest characteristics. Age and density (basal area (BA)) were underestimated for large, old, dense forest and overestimated for small, young, open forest. Although accuracy of responses for density, tree size, and age of forest plot images was low, the ordering of such images by these attributes did correspond to the actual forest plot characteristics. Alterations to the standard image were made for three of the forest plots, including alterations for the area depicted, the incorporation of understory vegetation and fallen trees, the addition of a truck, and regular and clumpy individual tree spacing. Image alterations did affect some mean responses for tree size, density, fire hazard, vertical stratification, and forest age. Results show managers and planners may need to exercise caution and supplement images with additional information to avoid miscommunication about the nature of current and projected forest landscapes.
- Visit PNW's Publication Request Page to request a hard copy of this publication.
- 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.
CitationBarrett, T.M.; Zuuring, H.R.; Christopher, T. 2006. Interpretation of forest characteristics from computer-generated images. Landscape and Urban Planning. 80(4): 396-403
KeywordsComputer visualization, decision-support systems, vegetation modeling, public communication
- Estimating forest characteristics for longleaf pine restoration using normalized remotely sensed imagery in Florida USA
- Simulated effects of forest management alternatives on landscape structure and habitat suitability in the Midwestern United States
- Neighboring group density is more important than forest stand age to a threatened social woodpecker population
XML: View XML