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

Piloyan Artak () and Konečný Milan
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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

Quaestiones Geographicae, 2017, vol. 36, issue 1, 93-103

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.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:quageo:v:36:y:2017:i:1:p:93-103:n:7

DOI: 10.1515/quageo-2017-0007

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