Laser-assisted selection of field plots for an area-based forest inventory
暂无分享,去创建一个
[1] Ron Wehrens,et al. The pls Package: Principal Component and Partial Least Squares Regression in R , 2007 .
[2] A. Finley,et al. Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory , 2013 .
[3] Terje Gobakken,et al. Reliability of LiDAR derived predictors of forest inventory attributes: A case study with Norway spruce , 2010 .
[4] E. Næsset. Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data , 2002 .
[5] E. Næsset,et al. Laser scanning of forest resources: the nordic experience , 2004 .
[6] Terje Gobakken,et al. Different plot selection strategies for field training data in ALS-assisted forest , 2010 .
[7] Harald Martens,et al. Reliable and relevant modelling of real world data: a personal account of the development of PLS Regression , 2001 .
[8] Terje Gobakken,et al. Assessing effects of laser point density, ground sampling intensity, and field sample plot size on biophysical stand properties derived from airborne laser scanner data , 2008 .
[9] Aloysius Wehr,et al. Airborne laser scanning—an introduction and overview , 1999 .
[10] Michele Dalponte,et al. The role of ground reference data collection in the prediction of stem volume with LiDAR data in mountain areas , 2011 .
[11] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[12] S. Wold,et al. The multivariate calibration problem in chemistry solved by the PLS method , 1983 .
[13] G. Baskerville. Use of Logarithmic Regression in the Estimation of Plant Biomass , 1972 .
[14] M. Maltamo,et al. The k-MSN method for the prediction of species-specific stand attributes using airborne laser scanning and aerial photographs , 2007 .
[15] GrafströmAnton,et al. Improving forest field inventories by using remote sensing data in novel sampling designs , 2013 .
[16] Carl-Erik Särndal,et al. Model Assisted Survey Sampling , 1997 .
[17] E. Næsset,et al. Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser , 2008 .
[18] Terje Gobakken,et al. Comparing regression methods in estimation of biophysical properties of forest stands from two different inventories using laser scanner data , 2005 .
[19] S. Engelsen,et al. Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .
[20] Terje Gobakken,et al. Improved estimates of forest vegetation structure and biomass with a LiDAR‐optimized sampling design , 2009 .
[21] Jennifer L. R. Jensen,et al. Estimation of biophysical characteristics for highly variable mixed-conifer stands using small-footprint lidar , 2006 .
[22] A. Hossain,et al. A comparative study on detection of influential observations in linear regression , 1991 .
[23] R. Cook. Detection of influential observation in linear regression , 2000 .
[24] E. Næsset. Practical large-scale forest stand inventory using a small-footprint airborne scanning laser , 2004 .
[25] S. Magnussen,et al. Derivations of stand heights from airborne laser scanner data with canopy-based quantile estimators , 1998 .
[26] J. Holmgren. Prediction of tree height, basal area and stem volume in forest stands using airborne laser scanning , 2004 .
[27] W. W. Carson,et al. Accuracy of a high-resolution lidar terrain model under a conifer forest canopy , 2003 .