In the master thesis, the methods of remote data sensing and processing determined the number and volume of woody debris in torrential streams. A true orthophoto image of the area, NDVI vegetation index, the point cloud and the raster layer of the digital surface model were created. With the obtained layers and four different methods the volume of woody debris was calculated. The methods were based on a cloud point (minimum convex 3D object), raster cells, lengths and polygon widths. Multispectral imagery has been proven to be a useful tool in recognizing woody debris manually. Inferior results were achieved by the method of automatic determination of woody debris. The method was based on the classification of the NDVI vegetation index, filtering of surfaces and classification of logistic regression. With the method of classification, we successfully determined 46 pieces of woody debris from a total of 144. The best method for volume calculation was the point cloud where woody debris was overestimated by 33%.