This thesis is interested in detection of lying deadwood from airborne laser scanning data. Thesis shows solutions of few authors, which are interested in this problematic, in more detail. Thesis explains solutions by using object-oriented image analysis, Line Template Matching or using edge detection algorithms. Thesis shows the use of these methods, their accuracy and applications with a view into the future. Thesis also provides her own solutions of this problematics which are based on using some available tools and applications of some geographic information systems. The first is automated method, which is based on creating raster representation of digital terrain model, with near-ground layer, where are identified lying tree stems by using edge detection algorithm. The other solution is semi-automated method. This method is based on normalized height cross section through point cloud, its filtration and manual selection points which represent lying tree stems. The whole process is evaluated in eCoginition software by multiresulotion segmentation and manual classification.