Skip to main content

Documentation and Evaluation of Growth and Other Estimators for the Fully Mapped Design Used by FIA: A Simulation Study

Buy Article:

$29.50 plus tax (Refund Policy)


For the proposed mapped design of the USDA Forest Service, Forest Survey and Inventory (FIA) units, in a simulation study for a realistic mapped population, Grosenbaugh's ingrowth estimator Î1 and Van Deusen's survivor growth estimator ΔS2 are best. If additivity of estimates is desired, ΔY1 should be used for total growth estimation. If additivity is not required, a plausible assumption as FIA users become more statistically literate, Roesch's estimator ΔY4, which is 12% more efficient than ΔY1 should be used if survivor ongrowth trees can be cored to determine their first time period diameters. If not, Grosenbaugh's nonadditive estimator ΔY2 should be used which is 8% more efficient than ΔY1. The classical variance estimator yields unbiased estimates of the variance of the parameter estimates as expected. Area estimation, change in area estimation, percentage of plots in more than one condition, means per tree, and changes in means per tree over time can be estimated reliably if sample size is large enough and conditions or changes in conditions are not too infrequent. The length of boundaries between conditions are consistently underestimated. For. Sci. Monogr. 31:26-45.

Keywords: Classical variance estimator; area estimation; length of boundaries

Document Type: Journal Article

Affiliations: USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, 240 West Prospect Street, Fort Collins, CO 80526-2098

Publication date: 1995-08-01

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.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 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