Comparison of four types of 3D data for timber volume estimation

The study compares the accuracy of timber volume prediction based on four different three-dimensional remote sensing data sets in one study area in southern Norway: airborne laser scanning (ALS), stereo aerial photogrammetry (AP), satellite interferometric synthetic aperture radar (InSAR) based on the TanDEM-X mission, and satellite radargrammetry based on the TerraSAR-X mission. We fitted linear mixed effects models with vegetation height and density metrics obtained from the remote sensing data sets as explanatory variables. The crossvalidated root mean squared error (RMSE) relative to the observed mean was used as the measure of goodness-of-fit. ALS provided the most accurate prediction at plot level with RMSE = 19%, followed by AP (31%), InSAR (42%), and radargrammetry (44%). At stand level the methods' performances were equally ordered, with RMSE values of 12-23%. Including the variables terrain slope and aspect in the models improved the accuracy of AP, InSAR, and radargrammetry slightly. (C) 2014 Elsevier Inc. All rights reserved.