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Semi-Automated Classification of Landform Elements in Armenia Based on SRTM DEM using K-Means Unsupervised Classification

Author

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  • Piloyan Artak

    (Faculty of Geography and Geology, Yerevan State University, Armenia)

  • Konečný Milan

    (Department of Geography, Faculty of Science, Masaryk University, Brno, Czechia)

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.

Suggested Citation

  • Piloyan Artak & Konečný Milan, 2017. "Semi-Automated Classification of Landform Elements in Armenia Based on SRTM DEM using K-Means Unsupervised Classification," Quaestiones Geographicae, Sciendo, vol. 36(1), pages 93-103, March.
    • Handle: RePEc:vrs:quageo:v:36:y:2017:i:1:p:93-103:n:7
    DOI: 10.1515/quageo-2017-0007
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