Skip to Main Content
A form of two-phase sampling utilizing regression analysisAuthor(s): Michael A. Fiery; John R. Brooks
Source: e-Gen. Tech. Rep. SRS–101. U.S. Department of Agriculture, Forest Service, Southern Research Station: 60-68 [CD-ROM].
Publication Series: Miscellaneous Publication
PDF: View PDF (596 KB)
DescriptionA two-phase sampling technique was introduced and tested on several horizontal point sampling inventories of hardwood tracts located in northern West Virginia and western Maryland. In this sampling procedure species and dbh are recorded for all “in-trees” on all sample points. Sawlog merchantable height was recorded on a subsample of intensively measured (second phase) sample points and these heights were predicted on the non-intensive (first phase) sample points. Regression analysis was used to predict heights on first phase points in order to achieve an estimate of board foot volume per acre for every point. Results indicate an improved estimate of the mean volume per acre when compared to traditional double sampling using basal area as the auxiliary variable. An unbiased sampling error was also achieved in this process.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- 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.
CitationFiery, Michael A.; Brooks, John R. 2007. A form of two-phase sampling utilizing regression analysis. e-Gen. Tech. Rep. SRS–101. U.S. Department of Agriculture, Forest Service, Southern Research Station: 60-68 [CD-ROM].
- More practical critical height sampling.
- Preliminary Results of Double-Sample Forest Inventory of Pine and Mixed Stands with High- and Low-Density LiDAR
- Increased uniformity by planting clones will likely have a minimal effect on inventory costs
XML: View XML