Airborne laser scanning is a relatively young and precise technology to directly measure surface elevations. With today’s high scanning rates, dense 3-D pointclouds of coordinate triplets (xyz) can be provided, in which many structural aspects of the vegetation are contained. The challenge now is to transform this data, as far as possible automatically, into manageable information relevant to the user. In this paper we present two such methods: the first extracts automatically the geometry of individual trees, with a recognition rate of over 70% and a systematic underestimation of tree height of only 0.6 metres. The second method derives a pixel map of the canopy density from the pointcloud, in which the spatial patterns of vegetation cover are represented. These patterns are relevant for habitat analysis and ecosystem studies. The values derived by this method correlate well with field measurements, giving a measure of certainty (R2) of 0.8. The greatest advantage of airborne laser scanning is that it provides spatially extensive, direct measurements of vegetation structure which show none of the extrapolation errors of spot measurements. A large challenge remains in integrating these new products into the user’s processing chains and workflows, be it in the realm of forestry or in that of ecosystem research.