Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of Above-Ground Biomass Change in Oregon, USA
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 uncerta...
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| Format: | Article |
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MDPI AG
2022-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/23/6024 |
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| author | Francisco Mauro Vicente J. Monleon Andrew N. Gray Olaf Kuegler Hailemariam Temesgen Andrew T. Hudak Patrick A. Fekety Zhiqiang Yang |
| author_facet | Francisco Mauro Vicente J. Monleon Andrew N. Gray Olaf Kuegler Hailemariam Temesgen Andrew T. Hudak Patrick A. Fekety Zhiqiang Yang |
| author_sort | Francisco Mauro |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T17:33:45Z |
| format | Article |
| id | doaj.art-5eeeefaa0b5b429f9c2af3ae4257c32e |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T17:33:45Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-5eeeefaa0b5b429f9c2af3ae4257c32e2023-11-24T12:04:25ZengMDPI AGRemote Sensing2072-42922022-11-011423602410.3390/rs14236024Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of Above-Ground Biomass Change in Oregon, USAFrancisco Mauro0Vicente J. Monleon1Andrew N. Gray2Olaf Kuegler3Hailemariam Temesgen4Andrew T. Hudak5Patrick A. Fekety6Zhiqiang Yang7Forest Biometrics and Measurements Laboratory, Department Forest Engineering, Resources and Management, Oregon State University, Corvallis, OR 97331, USAUS Forest Service Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331, USAUS Forest Service Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331, USAUS Forest Service Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331, USAForest Biometrics and Measurements Laboratory, Department Forest Engineering, Resources and Management, Oregon State University, Corvallis, OR 97331, USAUS Forest Service, Rocky Mountain Research Station, 1221 S Main St, Moscow, ID 83843, USANatural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USAUS Forest Service Rocky Mountain Research Station, Ogden, UT 84401, USAQuantifying 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.https://www.mdpi.com/2072-4292/14/23/6024endogenous-poststratificationmodel-assisted estimatorsgeneralized regression estimator (GREG)carbondisturbancesabove ground biomass |
| spellingShingle | Francisco Mauro Vicente J. Monleon Andrew N. Gray Olaf Kuegler Hailemariam Temesgen Andrew T. Hudak Patrick A. Fekety Zhiqiang Yang Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of Above-Ground Biomass Change in Oregon, USA Remote Sensing endogenous-poststratification model-assisted estimators generalized regression estimator (GREG) carbon disturbances above ground biomass |
| title | Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of Above-Ground Biomass Change in Oregon, USA |
| title_full | Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of Above-Ground Biomass Change in Oregon, USA |
| title_fullStr | Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of Above-Ground Biomass Change in Oregon, USA |
| title_full_unstemmed | Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of Above-Ground Biomass Change in Oregon, USA |
| title_short | Comparison of Model-Assisted Endogenous Poststratification Methods for Estimation of Above-Ground Biomass Change in Oregon, USA |
| title_sort | comparison of model assisted endogenous poststratification methods for estimation of above ground biomass change in oregon usa |
| topic | endogenous-poststratification model-assisted estimators generalized regression estimator (GREG) carbon disturbances above ground biomass |
| url | https://www.mdpi.com/2072-4292/14/23/6024 |
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