An alternative post-stratification scheme to decrease variance of forest attribute estimates in the Interior West

Miranda A. Rintoul; Sarah Maebius; Edwin Alvarado; Alexander Lloyd-Damnjanovic; Mai Toyohara; Kelly S. McConville; Gretchen Moisen; Tracey Frescino

Treesearch

An alternative post-stratification scheme to decrease variance of forest attribute estimates in the Interior West

Informally Refereed

Authors:

Miranda A. Rintoul, Sarah Maebius, Edwin Alvarado, Alexander Lloyd-Damnjanovic, Mai Toyohara, Kelly S. McConville, Gretchen Moisen, Tracey Frescino

Year:

2020

Type:

General Technical Report

Station:

Rocky Mountain Research Station

Source:

In: Brandeis, Thomas J., comp. Celebrating progress, possibilities, and partnerships: Proceedings of the 2019 Forest Inventory and Analysis (FIA) Science Stakeholder Meeting; November 19-21, 2019; Knoxville, TN. e-Gen. Tech. Rep. SRS-256. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. p. 268-276.

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Abstract

The National Forest Inventory and Analysis (FIA) Program of the Forest Service, U.S. Department of Agriculture, estimates many important forest attributes. Post-stratification with auxiliary data is used in the estimation process to improve precision. Current procedures used by the FIA unit in the U.S. Interior West involve stratifying by predicted forest and nonforest areas. This research aims to increase the efficiency of these post-stratified estimates by exploring alternative stratification schemes. We propose five candidate schemes based on auxiliary data from different sources and compare their relative efficiencies to both a simple random sampling estimator and to the current post-stratification. The best candidate, a four-strata scheme based on forest probability, is shown to improve the precision of forest attribute estimates over the current scheme across the Interior West region.

Parent Publication

Celebrating progress, possibilities, and partnerships: Proceedings of the 2019 Forest Inventory and Analysis (FIA) Science Stakeholder Meeting.

Keywords

FIA, post-stratification, forest probability, Interior West

Citation

Rintoul, Miranda A.; Maebius, Sarah; Alvarado, Edwin; Lloyd-Damnjanovic, Alexander; Toyohara, Mai; McConville, Kelly S.; Moisen, Gretchen G.; Frescino, Tracey S. 2020. An alternative post-stratification scheme to decrease variance of forest attribute estimates in the Interior West. In: Brandeis, Thomas J., comp. Celebrating progress, possibilities, and partnerships: Proceedings of the 2019 Forest Inventory and Analysis (FIA) Science Stakeholder Meeting; November 19-21, 2019; Knoxville, TN. e-Gen. Tech. Rep. SRS-256. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. p. 268-276.