A novel application of small area estimation in loblolly pine forest inventory

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dc.contributor.authorGreen, P. Coreyen
dc.contributor.authorBurkhart, Harold E.en
dc.contributor.authorCoulston, John W.en
dc.contributor.authorRadtke, Philip J.en
dc.contributor.departmentForest Resources and Environmental Conservationen
dc.date.accessioned2021-03-18T19:17:45Zen
dc.date.available2021-03-18T19:17:45Zen
dc.date.issued2020-04en
dc.description.abstractLoblolly pine (Pinus taeda L.) is one of the most widely planted tree species globally. As the reliability of estimating forest characteristics such as volume, biomass and carbon becomes more important, the necessary resources available for assessment are often insufficient to meet desired confidence levels. Small area estimation (SAE) methods were investigated for their potential to improve the precision of volume estimates in loblolly pine plantations aged 9-43. Area-level SAE models that included lidar height percentiles and stand thinning status as auxiliary information were developed to test whether precision gains could be achieved. Models that utilized both forms of auxiliary data provided larger gains in precision compared to using lidar alone. Unit-level SAE models were found to offer additional gains compared with area-level models in some cases; however, area-level models that incorporated both lidar and thinning status performed nearly as well or better. Despite their potential gains in precision, unit-level models are more difficult to apply in practice due to the need for highly accurate, spatially defined sample units and the inability to incorporate certain area-level covariates. The results of this study are of interest to those looking to reduce the uncertainty of stand parameter estimates. With improved estimate precision, managers, stakeholders and policy makers can have more confidence in resource assessments for informed decisions.en
dc.description.adminPublic domain – authored by a U.S. government employeeen
dc.description.notesThe Forest Modeling Research Cooperative, the Department of Forest Resources and Environmental Conservation, Virginia Tech and the United States Department of Agriculture McIntire-Stennis program (Project No. VA-136630) are all gratefully acknowledged for supporting this project.en
dc.description.sponsorshipForest Modeling Research Cooperative; Department of Forest Resources and Environmental Conservation, Virginia Tech; United States Department of Agriculture McIntire-Stennis program [VA-136630]en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1093/forestry/cpz073en
dc.identifier.eissn1464-3626en
dc.identifier.issn0015-752Xen
dc.identifier.issue3en
dc.identifier.urihttp://hdl.handle.net/10919/102741en
dc.identifier.volume93en
dc.language.isoenen
dc.rightsPublic Domainen
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/en
dc.subjectSmall area estimationen
dc.subjectForest inventoryen
dc.subjectAuxiliary dataen
dc.subjectLidaren
dc.subjectLoblolly pineen
dc.titleA novel application of small area estimation in loblolly pine forest inventoryen
dc.title.serialForestryen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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