Skip to main content

Predicting Scenic Quality for Urban Forests Using Vegetation Measurements

Buy Article:

$21.50 plus tax (Refund Policy)

Scenic quality models were formulated for urban residential areas. The focus of the study was on determining the predictive ability of measurable parameters of tree and other vegetation. Two types of data bases were used: (1) site inventory measurements and (2) photo measurements of urban forest related variables. Regression results indicate that visual preference for urban forest scenes increases with increasing average dbh, basal area per stem, and crown enclosure. There are tentative indications that the relationship between preference and amount of vegetation may be nonmonotonic and also that people prefer scenes with fewer, larger stems to those with many smaller stems. It is hypothesized that these scenic quality models have potential for integration with urban tree inventory data bases for determining planting prioritization. Forest Sci. 30:71-82.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

Keywords: Landscape preference; urban forestry; visual quality prediction

Document Type: Journal Article

Affiliations: Associate Professor of Forestry, Virginia Polytechnic Institute and State University

Publication date: 1984-03-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Podcasts
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more