Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.foreco.2017.04.046 |
Updating national forest inventory estimates of growing stock volume using hybrid inference | |
Condes, Sonia1; McRoberts, Ronald E.2 | |
2017-09-15 | |
发表期刊 | FOREST ECOLOGY AND MANAGEMENT |
ISSN | 0378-1127 |
EISSN | 1872-7042 |
出版年 | 2017 |
卷号 | 400 |
文章类型 | Article |
语种 | 英语 |
国家 | Spain; USA |
英文摘要 | International organizations increasingly require estimates of forest parameters to monitor the state of and changes in forest resources, the sustainability of forest practices and the role of forests in the carbon cycle. Most countries rely on data from their national forest inventories (NFI) to produce these estimates. However, because NFI survey years may not match the required reporting years, techniques for updating NFI-based estimates are necessary. The main aim was to develop an unbiased method to update NFI estimates of mean growing stock volume (m3/ha) using models to predict annual plot-level volume change, and to estimate the associated uncertainties. Because the final large area volume estimates were based on plot-level model predictions rather than field observations, hybrid inference was necessary to accommodate both model prediction uncertainty and sampling variation. Specific objectives were to compare modelling approaches, to assess the utility of Landsat data for increasing model prediction accuracy, to select the most accurate method, and to compare model-based and design-based uncertainty components. For four monospecific forest types, data from the 2nd and 3rd Spanish NFI surveys together with site variables and Landsat images were used to construct models to predict NFI information for the year of the 4th NFI survey. Data from the 3rd and 4th surveys were used to assess the accuracy of the model predictions at both plot-level and large area spatial scales. The most accurate method used a set of three models: one to predict the probability of volume removals, one to predict the amount of removed volume, and one to predict gross annual volume. Incorporation of Landsat-based variables in the models increased prediction accuracy. Differences between large area estimates based on plot-level field observations for the 4th NFI survey and estimates based"on the model predictions were minimal for all four forest types. Further, the standard errors of the estimates based on the model predictions were only slightly greater than standard errors based on the field observations. Thus, model predictions of plot-level growing stock volume based on field and satellite image data as auxiliary information can be used to update large area NFI estimates for reporting years for which spectral data are available but field observations are not. Finally, variances of means are underestimated unless hybrid inferential methods are used to incorporate both model prediction uncertainty and sampling variation. For the two forest types for which the two sources of uncertainty were of the same order of magnitude, the under-estimation was non-negligible. (C) 2017 Elsevier B.V. All rights reserved. |
英文关键词 | Remote sensing Annual volume change Annual volume increment Growth model Uncertainty |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000406732100006 |
WOS关键词 | LANDSAT-TM DATA ; BIOMASS ESTIMATION ; EUROPEAN FORESTS ; HEDMARK COUNTY ; FIELD PLOTS ; MODELS ; FUTURE ; GROWTH ; AREA ; VEGETATION |
WOS类目 | Forestry |
WOS研究方向 | Forestry |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/23808 |
专题 | 气候变化 |
作者单位 | 1.Univ Politecn Madrid, Sch Forest Engn & Nat Environm, Dept Nat Syst & Resources, Madrid, Spain; 2.US Forest Serv, Northern Res Stn, 1992 Folwell Ave, St Paul, MN 55108 USA |
推荐引用方式 GB/T 7714 | Condes, Sonia,McRoberts, Ronald E.. Updating national forest inventory estimates of growing stock volume using hybrid inference[J]. FOREST ECOLOGY AND MANAGEMENT,2017,400. |
APA | Condes, Sonia,&McRoberts, Ronald E..(2017).Updating national forest inventory estimates of growing stock volume using hybrid inference.FOREST ECOLOGY AND MANAGEMENT,400. |
MLA | Condes, Sonia,et al."Updating national forest inventory estimates of growing stock volume using hybrid inference".FOREST ECOLOGY AND MANAGEMENT 400(2017). |
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