Precision and cost considerations for two-stage sampling in a panelized forest inventory design

Abstract

Due to the relatively high cost of measuring sample plots in forest inventories, considerable attention is given to sampling and plot designs during the forest inventory planning phase. A two-stage design can be efficient from a field work perspective as spatially proximate plots are grouped into work zones. A comparison between subsampling with units of unequal size (SUUS) and a simple random sample (SRS) design in a panelized framework assessed the statistical and economic implications of using the SUUS design for a case study in the Northeastern USA. The sampling errors for estimates of forest land area and biomass were approximately 1.5-2.2 times larger with SUUS prior to completion of the inventory cycle. Considerable sampling error reductions were realized by using the zones within a post-stratified sampling paradigm; however, post-stratification of plots in the SRS design always provided smaller sampling errors in comparison. Cost differences between the two designs indicated the SUUS design could reduce the field work expense by 2-7 %. The results also suggest the SUUS design may provide substantial economic advantage for tropical forest inventories, where remote areas, poor access, and lower wages are typically encountered.