DOI: 10.1016/j.foreco.2015.07.002
Scopus记录号: 2-s2.0-84945464088
论文题名: Comparison of uncertainty in per unit area estimates of aboveground biomass for two selected model sets
作者: Shettles M. ; Temesgen H. ; Gray A.N. ; Hilker T.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2015
卷: 354 起始页码: 18
结束页码: 25
语种: 英语
英文关键词: Measurement error
; Model error
; Pacific Northwest
; Sampling error
Scopus关键词: Agriculture
; Biomass
; Errors
; Forestry
; Intelligent systems
; Measurement errors
; Monte Carlo methods
; Above ground biomass
; Forest inventory and analysis
; Instrument comparison
; Model errors
; Pacific Northwest
; Relative standard error
; Sampling errors
; United states department of agricultures
; Uncertainty analysis
; aboveground biomass
; comparative study
; error analysis
; forest inventory
; Monte Carlo analysis
; sampling
; uncertainty analysis
; Pacific Ocean
; Pacific Ocean (Northwest)
; United States
; Pinus contorta
英文摘要: Uncertainty in above ground forest biomass (AGB) estimates at broad-scale depends primarily on three sources of error that interact and propagate: measurement error, model error, and sampling error. Using Monte Carlo simulations, we compare the total propagated error for two sets of regional-level component equations for lodgepole pine AGB, and for two sets of high-precision instruments by accounting for all three of these sources of error. The two sets of models compared included a set of newly-developed component ratio method (CRM) equations, and a set of component AGB equations currently used by the Forest Inventory and Analysis (FIA) unit of the United States Department of Agriculture (USDA) Forest Service.Relative contributions for measurement, model, and sampling error using the current regional equations were 5%, 2% and 93%, respectively, and 13%, 55% and 32%, respectively using the CRM equations. Relative standard error (RSE) values for the current regional and CRM equations with all three error types accounted for were 20.7% and 36.8%, respectively. Results for the model comparisons indicate that per acre estimates of AGB using the CRM equations are far less precise than those produced with the current set of regional equations. Results for the instrument comparisons indicate the terrestrial lidar scanning reduce uncertainty in broad-scale estimates of AGB attributed to measurement error. © 2015. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/65308
Appears in Collections: 影响、适应和脆弱性
There are no files associated with this item.
作者单位: Department of Forest Engineering, Resources, and Management, Oregon State University, 237 Peavy Hall, Corvallis, OR, United States; Forest Analysis and Inventory Branch, USDA, Pacific Research Station, Corvallis, OR, United States
Recommended Citation:
Shettles M.,Temesgen H.,Gray A.N.,et al. Comparison of uncertainty in per unit area estimates of aboveground biomass for two selected model sets[J]. Forest Ecology and Management,2015-01-01,354