The idea of this project is to compare the performance of different machine learning algorithms on tomographic SAR data. To reduce the dimensionality of the and ultimately to increase computational time and get rid of any noise - the tomogram is represented by a number of descriptive features. Finally, the performance (computational time and classification accuracy) of the selected machine learning algorithms on the different feature representations of the data should be compared with the performance on the original data (Tomogram).