Thesis deals with acquisition, processing, classification and simple analysis of multispectral images from Sentinel 2 satellite, using the free GIS software QGIS, using its own and implemented tools of other freely available programs (SAGA, GRASS) and plugins. One of the main goals is to create a process which could gain and process satellite images in the best setting for the spectral classification. The classification was performed by Semiautomatic classification plugin (SCP), which is a plugin of software QGIS. Plugin SCP works with multispectral images of satellites e.g. Landsat or Sentinel 2, provides download, preprocessing, and postprocessing tools. It enables controlled spectral classification of remote sensing images based on differences in the reflectance levels of individual objects in spectral bands by training sets. The classification was performed on images with a spatial resolution of 10 meters. The results are evaluated in comparison with the picture, according to the degree of similarity of individual classes and partly in the field. From the statistical data of the classification are calculated simple hydrological analyzes – outflow from the entire catchment area and retention capacity of the catchment area by research according to research of Forestry Research Institute in Zvolen. The results obtained from the classification and applied methods point to the use of the results in more complex research with the necessary land cover.