Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation

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dc.contributor.authorCao, Qianqianen
dc.contributor.authorDettman, Garret, T.en
dc.contributor.authorRadtke, Philip J.en
dc.contributor.authorCoulston, John W.en
dc.contributor.authorDerwin, Jillen
dc.contributor.authorThomas, Valerie A.en
dc.contributor.authorBurkhart, Harold E.en
dc.contributor.authorWynne, Randolph H.en
dc.date.accessioned2023-04-18T17:54:51Zen
dc.date.available2023-04-18T17:54:51Zen
dc.date.issued2022-04-26en
dc.description.abstractMany National Forest Inventory (NFI) stakeholders would benefit from accurate estimates at finer geographic scales than most currently implemented in operational estimates using NFI sample data. In the past decade small area estimation techniques have been shown to increase precision in forest inventory estimates by combining field observations and remote-sensing.We sought to demonstrate the potential for improving the precision of forest inventory growing stock volume estimates for counties in United States of North Carolina, Tennessee, and Virginia, by pairing canopy height models from digital aerial photogrammetry (DAP) and field plot data from the United States NFI. Area-level Fay-Herriot estimators were used to avoid the need for precise (GPS) coordinates of field plots. Reductions in standard errors averaging 30% for North Carolina county estimates were observed, with 19% average reductions in standard errors in both Tennessee and Virginia. Accounting for spatial autocorrelation among adjacent counties provided further gains in precision when the three states were treated as a single forest land population; however, analyses conducted one state at a time showed that good results could be achieved without accounting for spatial autocorrelation. Apparent gains in sample sizes ranged from about 65% in Virginia to 128% in North Carolina, compared to the current number of inventory plots. Results should allow for determining whether acquisition of statewide DAP would be costeffective as a means for increasing the accuracy of county-level forest volume estimates in the United States NFI.en
dc.description.sponsorshipThis work was supported by USDA, Forest Service Southern Research Station, 20-JV-11330145-074.en
dc.description.versionPublished versionen
dc.format.extent13 pgen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationCao Q, Dettmann GT, Radtke PJ, Coulston JW, Derwin J, Thomas VA, Burkhart HE and Wynne RH (2022) Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation. Front. For. Glob. Change 5:769917. doi: 10.3389/ffgc.2022.769917en
dc.identifier.doihttps://doi.org/10.3389/ffgc.2022.769917en
dc.identifier.urihttp://hdl.handle.net/10919/114546en
dc.identifier.volume5en
dc.language.isoenen
dc.publisherFrontiers Mediaen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectspatial Fay-Herriot modelsen
dc.subjectmodel-assisted analysisen
dc.subjectmodel-based estimationen
dc.subjectcomposite estimatorsen
dc.subjectforest inventoryen
dc.titleIncreased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimationen
dc.title.serialFrontiers in Forests and Global Changeen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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