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    Author(s): J.H. Gove
    Date: 2018
    Source: tps://r-forge.r-project.org/scm/viewvc.php/*checkout*/extra/vignettes/sampSurfIntro.pdf?root=sampsurf. 61 p.
    Publication Series: Miscellaneous
    Station: Northern Research Station
    PDF: View PDF  (677.0 KB)

    Description

    Sampling methods in natural resources are largely based on probability proportional to size or frequency concepts and are often referred to as areal sampling methods, because they induce an enlarged area about the object within which a random point may fall and select the object. The ability to compare di erent sampling methods is key to designing inventories and assessing the eciency of newly developed methods when compared against existing methods. Simulation methods are often used on synthetic populations of individuals with the desired characteristics of some target population in order to assess the adequacy of di ering methods. The R (R Core Team, 2017) sampSurf package (Gove, 2017c) was developed to facilitate the comparison of sampling methods for forested or previously forested target populations of standing trees and downed coarse woody debris. Simulation is accomplished by constructing one or more \sampling surfaces" from which the eciency (in terms of variance) of a method can be deduced relative to other methods. The theory behind sampling surface estimation and development is reviewed along with the package design and examples showing its use and extension.

    Publication Notes

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    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

    Citation

    Gove, J.H. 2018. SampSurf: sampling surface simulation for areal sampling designs in R. https://r-forge.r-project.org/scm/viewvc.php/*checkout*/extra/vignettes/sampSurfIntro.pdf?root=sampsurf. 61 p.

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https://www.fs.usda.gov/treesearch/pubs/57055