| Summary: | Quantifying above-ground biomass changes, Δ<i>AGB</i>, is key for understanding carbon dynamics. National Forest Inventories, NFIs, aims at providing precise estimates of Δ<i>AGB</i> relying on model-assisted estimators that incorporate auxiliary information to reduce uncertainty. Poststratification estimators, PS, are commonly used for this task. Recently proposed endogenous poststratification, EPS, methods have the potential to improve the precision of PS estimates of Δ<i>AGB</i>. Using the state of Oregon, USA, as a testing area, we developed a formal comparison between three EPS methods, traditional PS estimators used in the region, and the Horvitz-Thompson, HT, estimator. Results showed that gains in performance with respect to the HT estimator were 9.71% to 19.22% larger for EPS than for PS. Furthermore, EPS methods easily accommodated a large number of auxiliary variables, and the inclusion of independent predictions of Δ<i>AGB</i> as an additional auxiliary variable resulted in further gains in performance.
|
|---|