Sampling trees with probability nearly proportional to biomass

Academic Article


  • It is a truism in the sampling literature that sampling is most efficient when it is conducted with probability proportional to the variable of interest. Variable probability sampling methods have long been applied to trees. The most familiar approach is horizontal point sampling (HPS) which samples trees with probability proportional to basal area. Here, I introduce a generalization of horizontal point sampling (GHPS). GHPS is a simple practical technique for sampling trees with probability proportional to an approximate equation for biomass. The technique requires construction of a gauge, but the gauge need not be complicated. In principle, GHPS should be more efficient than ordinary HPS. This hypothesis was tested with a field trial. Somewhat surprisingly, GHPS was only marginally superior to HPS in terms of sampling variance and efficiency. However, GHPS took no longer to perform, and was not associated with detectable non-sampling error. Results suggest that a well-designed subsampling approach, used in conjunction with GHPS, might lead to appreciable improvements.
  • Authors


    Publication Date

  • October 2009
  • Has Subject Area

    Published In


  • Bitterlich sampling
  • Forest inventory
  • Prism sampling
  • Digital Object Identifier (doi)

    Start Page

  • 2110
  • End Page

  • 2116
  • Volume

  • 258
  • Issue

  • 9