SEMI-AUTOMATED CLASSIFICATION OF LANDFORM ELEMENTS IN ARMENIA BASED ON SRTM DEM USING K-MEANS UNSUPERVISED CLASSIFICATION - Piloyan, Artak; Konečný, Milan (Quaestiones Geographicae, 2017)
Land elements have been used as basic landform descriptors in many science disciplines, including soil mapping, vegetation mapping, and landscape ecology. This paper presents a semi-automatic method based on k-means unsupervised classification to analyze geomorphometric features as landform elements in Armenia. First, several data layers were derived from DEM: elevation, slope, profile curvature, plan curvature and flow path length. Then, k-means algorithm has been used for classifying landform elements based on these morphomertic parameters. The classification has seven landform classes. Overall, landform classification is performed in the form of a three-level hierarchical scheme. The resulting map reflects the general topography and landform character of Armenia.