Derivation of Dominant Height and Yield Class of Forest Stands by Means of Airborne Remote Sensing Methods

In forest management and planning there is a permanent need of up-to-date information on forest areas. Digital photogrammetry and airborne laser scanning (ALS) can provide 3-D information on the forest canopy over large areas. In particular, canopy height models (CHM) derived by subtracting the digital terrain model (DTM) from the digital surface model (DSM) provide promising possibilities to determine forest attributes, including tree/stand height and timber volume. In the current study, an ALS-based and a photogrammetric CHM (normalized using an ALS-DTM) were used to estimate forest growth between 2006 and 2011. It was investigated if the CHM can be used to derive dominant height and to estimate the yield power in terms of the yield class of a forest stand. Two approaches were tested. The first approach relies on the conventional input that is also used in the field, i.e. dominant height and stand age, with the tree height obtained from remote sensing data and the age of the stand by field measurement. lathe second approach, the yield class was derived from dominant height and height growth, both obtained from remote sensing data. While with the first approach satisfying results could be achieved, the second approach was not successful. Yield class estimation is very sensitive to the input variable height growth, which could not be derived with sufficient accuracy from the CHMs used in the study. It is expected that in the future the estimation of yield class will be more accurate due to longer observation periods, e.g. 10 years, and due to the availability of CHM time series with more than two points in time.