SEMI-AUTOMATED CLASSIFICATION OF LANDFORM ELEMENTS IN ARMENIA BASED ON SRTM DEM USING K-MEANS UNSUPERVISED CLASSIFICATION
Vol. 36 No. 1 (2017), Articles
Vol. 36 No. 1 (2017)

SEMI-AUTOMATED CLASSIFICATION OF LANDFORM ELEMENTS IN ARMENIA BASED ON SRTM DEM USING K-MEANS UNSUPERVISED CLASSIFICATION

Articles
https://doi.org/10.1515/quageo-2017-0007
Published 15.03.2017
Artak Piloyan
Faculty of Geography and Geology, Yerevan State University, Armenia
Armenia
Milan Konečný
Department of Geography, Faculty of Science, Masaryk University, Brno
Czechia
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Piloyan, A., & Konečný, M. (2017). SEMI-AUTOMATED CLASSIFICATION OF LANDFORM ELEMENTS IN ARMENIA BASED ON SRTM DEM USING K-MEANS UNSUPERVISED CLASSIFICATION. Quaestiones Geographicae, 36(1), 93–103. https://doi.org/10.1515/quageo-2017-0007
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Abstract

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.

https://doi.org/10.1515/quageo-2017-0007
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