Effects of terrain slope and aspect on the error of ALS-based predictions of forest attributes

摘要

Wall-to-wall forest management inventories with the area-based method using airborne laser scanner (ALS) data are operational in many countries. With this method, empirical relationships are established between ALS metrics and ground reference observations of forest attributes, and wall-to-wall predictions can be made over large areas. However, the prediction errors may be influenced by terrain slope and aspect because the properties of the ALS point cloud are dependent on these factors. Two datasets covering wide ranges of terrain slope and aspect, collected in the western part of Norway, were analysed. The first dataset represented sample plots from an ordinary operational forest management inventory and the second dataset were collected as an experimental dataset where clusters of sample plots were distributed on slopes with different inclinations. Six forest attributes were predicted using non-linear regression and the prediction errors were analysed using univariate-and multivariate analysis of variance. The results showed that slope and aspect affected the prediction errors, but that the effects were small in magnitude. Thus, the current study concludes that terrain effects seem to be negligible in operational forest inventories.