Airborne laser scanning data has proven to be a very suitable technique for the determination of digital surface models and is more and more being used for mapping and GIS data acquisition purposes, including the detection and modeling of man-made objects or vegetation. The aim of the work presented here is to segment raw laser scanner data in an unsupervised classification using anisotropic height texture measures. Anisotropic operations have the potential to discriminate between orientated and non-orientated objects. The techniques have been applied to data sets from different laser scanning systems and from different regions, mainly focussing on high-density laser scanner data. The results achieved in these pilot studies show the large potential of airborne laser scanning in the field of 3-D GIS data acquisition.