<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

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

Faculty of Geography and Geology, Yerevan State University,

Department of Geography, Faculty of Science, Masaryk University, Brno,

Quaestiones Geographicae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Land elements have been used as basic landform descriptors in many science disciplines, including soil mapping, vegetation mapping, and landscape ecology. This...

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

Online veröffentlicht: 16. März 2017

Seitenbereich: 93 - 103

Eingereicht: 12. Jan. 2017

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

© Faculty of Geographical and Geological Sciences, Adam Mickiewicz University

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.