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): Jeffrey T. Walton; David J. NowakEric J. Greenfield
    Date: 2008
    Source: Arboriculture & Urban Forestry. 34(6): 334-340.
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: View PDF  (95.58 KB)

    Description

    With the availability of many sources of imagery and various digital classification techniques, assessing urban forest canopy cover is readily accessible to most urban forest managers. Understanding the capability and limitations of various types of imagery and classification methods is essential to interpreting canopy cover values. An overview of several remote sensing techniques used to assess urban forest canopy cover is presented. A case study comparing canopy cover percentages for Syracuse, New York, U.S. interprets the multiple values developed using different methods. Most methods produce relatively similar results, but the estimate based on the National Land Cover Database is much lower.

    Publication Notes

    • Check the Northern Research Station web site to request a printed copy of this publication.
    • Our on-line publications are scanned and captured using Adobe Acrobat.
    • During the capture process some typographical errors may occur.
    • Please contact Sharon Hobrla, shobrla@fs.fed.us if you notice any errors which make this publication unusable.
    • 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

    Walton, Jeffrey T.; Nowak, David J.; Greenfield, Eric J. 2008. Assessing urban forest canopy cover using airborne or satellite imagery. Arboriculture & Urban Forestry. 34(6): 334-340.

    Keywords

    remote sensing, urban tree canopy

    Related Search


    XML: View XML
Show More
Show Fewer
Jump to Top of Page
https://www.fs.usda.gov/treesearch/pubs/19515