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The availability of digital elevation model (DEM) delivered by airborne laser scanning (ALS) opens new horizons in the geomorphological research, especially in the landslide studies. This detailed geomorphological information allows for mapping of landslide affected areas using DEM data only. In order to map landslide areas in the automatic manner using machine learning classification algorithms and only DEM, generation of several DEM derivatives is needed. These first and second order derivatives provide information about specific properties of the terrain. However, involving a set of topographic features in the machine learning process increases significantly time of computations. Moreover, the topographic features are correlated since they are generated using the same DEM. The objective of this study is an in-depth exploration of the topographic information provided by the DEM data as well as the …