Lidar supported estimators of wood volume and aboveground biomass from the Danish national forest inventory (2012-2016)
作者： Steen Magnussen , Thomas Nord-Larsen , Torben Riis-Nielsen
DOI: 10.1016/J.RSE.2018.04.015
关键词: Aboveground biomass 、 Forest resource 、 Physical geography 、 Estimator 、 Lidar 、 Estimation 、 Volume (thermodynamics) 、 Remote sensing 、 Environmental science 、 National forest 、 National forest inventory
摘要: Abstract National forest inventories (NFI) provide estimates of resources at the national and regional level but are also increasingly used as basis for mapping based on remotely sensed data. Such maps procure local may improve precision estimates. Supported by a countrywide airborne laser scanning (circa 2014) land-use map 2014), direct (DI), model-assisted (MA), model calibrated (MC) wood volume (V) aboveground biomass (AGB) densities in areas derived from Danish NFI (2012–2016) presented. Nonlinear models with three LiDAR metrics to predict V AGB forested areas. According these models, predicted values sample plots missed field inventory was lower than those visited field; we therefore opted estimation multiple (stochastic) imputations. MA country suggested 2% both errors 45% estimated DI results. MC were close an error approximately 40% yet 5% greater error. Multiple imputations had strongest impact estimates, only weak
harvard.edu
sci-hub.se 参考文章(74)
Thaddeus Tarpey, R. Todd Ogden, Eva Petkova, Ronald Christensen, A Paradoxical Result in Estimating Regression Coefficients The American Statistician. ,vol. 68, pp. 271- 276 ,(2014) , 10.1080/00031305.2014.940467
S Magnussen, D Burgess, Stochastic resampling techniques for quantifying error propagations in forest field experiments Canadian Journal of Forest Research. ,vol. 27, pp. 630- 637 ,(1997) , 10.1139/X97-049
AM Mosammam, Geostatistics: Modeling Spatial Uncertainty ,(1999)
Marc Bouvier, Sylvie Durrieu, Richard A. Fournier, Jean-Pierre Renaud, Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data Remote Sensing of Environment. ,vol. 156, pp. 322- 334 ,(2015) , 10.1016/J.RSE.2014.10.004
Bengt Swensson, Jan Hȧkan Wretman, Carl-Erik Särndal, Model assisted survey sampling ,(1997)
Elizabeth Koehler, Elizabeth Brown, Sebastien J.-P. A. Haneuse, On the Assessment of Monte Carlo Error in Simulation-Based Statistical Analyses The American Statistician. ,vol. 63, pp. 155- 162 ,(2009) , 10.1198/TAST.2009.0030
Roderick JA Little, Donald B Rubin, None, Statistical Analysis with Missing Data ,(1987)
Ronald E. McRoberts, Erik Næsset, Terje Gobakken, Inference for lidar-assisted estimation of forest growing stock volume Remote Sensing of Environment. ,vol. 128, pp. 268- 275 ,(2013) , 10.1016/J.RSE.2012.10.007
Morton B. Brown, Alan B. Forsythe, Robust Tests for the Equality of Variances Journal of the American Statistical Association. ,vol. 69, pp. 364- 367 ,(1974) , 10.1080/01621459.1974.10482955
Thomas Nord-Larsen, Johannes Schumacher, Estimation of forest resources from a country wide laser scanning survey and national forest inventory data Remote Sensing of Environment. ,vol. 119, pp. 148- 157 ,(2012) , 10.1016/J.RSE.2011.12.022