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NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2017

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Abstract

Post-stratified model-assisted (MA) and hybrid (HY) estimators are used with repeated airborne laser scanning (ALS) strip sampling and national forest inventory field data for stratum-wise and overall estimation of aboveground biomass (AGB) stock and change. The study area covered the southern portion of the Hedmark County in Norway. Both MA and HY estimation substantially reduced the uncertainty in AGB change when compared with estimation using the field survey only. Relative efficiencies (relative variance) of 4.15 (MA) and 3.36 (HY) for overall estimates were found. The results suggest the MA estimator for single-time estimation and the HY as more appropriate for change estimation by cover class. With the HY estimator, a nested post-stratification scheme is demonstrated, combining cover classes with change classes, which enables detailed reporting for change according to cause within each cover class, and has the potential to improve the estimation precision. Finally, parametric bootstrapping is demonstrated as an empirical alternative to estimate the model-error component in the HY estimator. The model error estimated with parametric bootstrapping converged to the analytically determined value of the HY estimator within 1000 bootstrap samples.