Semi-automated classification of landform elements in Armenia based on SRTM DEM using k-means unsupervised classification
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Date
2017
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Wydział Nauk Geograficznych i Geologicznych Uniwersytetu im. Adama Mickiewicza
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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.
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Quaestiones Geographicae vol. 36 (1), 2017, pp. 93-103
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0137-477X