Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation
Many 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 inven...
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| Format: | Article |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Forests and Global Change |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/ffgc.2022.769917/full |
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| author | Qianqian Cao Garret T. Dettmann Philip J. Radtke John W. Coulston Jill Derwin Valerie A. Thomas Harold E. Burkhart Randolph H. Wynne |
| author_facet | Qianqian Cao Garret T. Dettmann Philip J. Radtke John W. Coulston Jill Derwin Valerie A. Thomas Harold E. Burkhart Randolph H. Wynne |
| author_sort | Qianqian Cao |
| collection | DOAJ |
| description | Many 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 cost-effective as a means for increasing the accuracy of county-level forest volume estimates in the United States NFI. |
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| institution | Directory Open Access Journal |
| issn | 2624-893X |
| language | English |
| last_indexed | 2024-12-12T22:21:32Z |
| publishDate | 2022-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Forests and Global Change |
| spelling | doaj.art-c64c2695a6f447aa9025be47d1b5cbde2022-12-22T00:09:54ZengFrontiers Media S.A.Frontiers in Forests and Global Change2624-893X2022-04-01510.3389/ffgc.2022.769917769917Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area EstimationQianqian Cao0Garret T. Dettmann1Philip J. Radtke2John W. Coulston3Jill Derwin4Valerie A. Thomas5Harold E. Burkhart6Randolph H. Wynne7Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United StatesDepartment of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United StatesDepartment of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United StatesSouthern Research Station, Forest Service, United States Forest Service, Asheville, NC, United StatesDepartment of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United StatesDepartment of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United StatesDepartment of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United StatesDepartment of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United StatesMany 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 cost-effective as a means for increasing the accuracy of county-level forest volume estimates in the United States NFI.https://www.frontiersin.org/articles/10.3389/ffgc.2022.769917/fullspatial Fay-Herriot modelsmodel-assisted analysismodel-based estimationcomposite estimatorsforest inventory |
| spellingShingle | Qianqian Cao Garret T. Dettmann Philip J. Radtke John W. Coulston Jill Derwin Valerie A. Thomas Harold E. Burkhart Randolph H. Wynne Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation Frontiers in Forests and Global Change spatial Fay-Herriot models model-assisted analysis model-based estimation composite estimators forest inventory |
| title | Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation |
| title_full | Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation |
| title_fullStr | Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation |
| title_full_unstemmed | Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation |
| title_short | Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation |
| title_sort | increased precision in county level volume estimates in the united states national forest inventory with area level small area estimation |
| topic | spatial Fay-Herriot models model-assisted analysis model-based estimation composite estimators forest inventory |
| url | https://www.frontiersin.org/articles/10.3389/ffgc.2022.769917/full |
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