Skip to main content

Corrections for Cluster-Plot Slop

Buy Article:

$29.50 plus tax (Refund Policy)

Cluster-plot designs, including the design used by the Forest Inventory and Analysis program of the USDA Forest Service (FIA), are attended by a complicated boundary slopover problem. Slopover occurs where inclusion zones of objects of interest cross the boundary of the area of interest. The dispersed nature of inclusion zones that arise from the use of cluster plots precludes the use of most of the slopover-correction methods that apply to solitary plots. One exception is the walkthrough method, which corrects for slopover bias in radially symmetric cluster-plot designs. In this article, we provide a modification of the walkthrough method, the “walkabout method,” which is applicable to some asymmetric cluster-plot designs, such as the one used by FIA. We also present two general correction methods, the “vectorwalk method” and the “reflection method,” both of which are applicable to cluster-plot designs with satellite subplots arranged in a regular or irregular pattern. The reflection method has two sets of protocols, one that applies to radially symmetric designs and to asymmetric designs with random orientation; the other set applies to asymmetric designs with fixed orientation. Both the vectorwalk and reflection methods incorporate the walkthrough method on a subplot-by-subplot basis. All four methods correct for slopover bias for straight or curved boundaries, and where work outside the tract is impossible.
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: Boundary overlap; Monte Carlo integration; edge effect; reflection method; slopover; vectorwalk method; walkabout method; walkthrough method

Document Type: Research Article

Affiliations: 1: Harry T. Valentine, USDA Forest Service, Northeastern Research Station, PO Box 640, Durham, NH 03824—, Fax: (603)-868-7604, Email: hvalentine@fs.fed.us. 2: Mark J. Ducey, Department of Natural Resources, University of New Hampshire, Durham, NH 03824—, Email: mjducey@cisunix.unh.edu. 3: Jeffrey H. Gove, USDA Forest Service, Northeastern Research Station, PO Box 640, Durham, NH 03824—, Email: jgove@fs.fed.us. 4: Adrian Lanz, Swiss Federal Institute for Forest, Snow and Landscape Research, Zurcherstrasse 111, CH-8903 Birmensdorf, Switzerland—, Email: adrian.lanz@wsl.ch. 5: David L. R. Affleck, Yale University, School of Forestry and Environmental Studies, 210 Prospect Street, New Haven, CT 06511—, Email: david.affleck@yale.edu.

Publication date: 2006-01-01

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
X
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