Publication details
Semi-Automated Classification of Landform Elements in Armenia Based on SRTM DEM using K-Means Unsupervised Classification
| Authors | |
|---|---|
| Year of publication | 2017 |
| Type | Article in Periodical |
| Magazine / Source | Quaestiones geographicae |
| MU Faculty or unit | |
| Citation | |
| web | open access verze článku |
| Doi | https://doi.org/10.1515/quageo-2017-0007 |
| Field | Earth magnetism, geography |
| Keywords | Landform Elements; K-Means; Unsupervised Classification; Armenia |
| Attached files | |
| Description | 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. |