Automatic relief classification versus expert and field based landform classification for the medium-altitude mountain range, the Sudetes, SW Poland

The main purpose of the study is to compare the results of automatic classification of landforms performed as unsupervised classification and manual (expert) morphographic landform classification derived from field mapping and recognition of long-term trends in landform evolution. Two test areas in the Sudetes Mountains (SW Poland) were selected, each representing a different type of relief. The Jelenia Góra Basin is an example of denudational hilly granite topography, with inselbergs, other residual hills, and basins, whereas the northern part of the Bystrzyckie Mountains is a faulted plateau underlain by sedimentary and metamorphic rocks. The setup of the classification involved a DEM derived from digitalization of 1:25,000 maps, a filter mask of 20 × 20 pixels (500 × 500 m), k-median cluster analysis, and consideration of four dimensions (relative height, slope, combined curvature, and aspect). We used a statistical criterion to decide the level of classification, i.e. the number of homogeneous groups returned. Output maps show the results of classification into five (Jelenia Góra Basin) or six groups (Bystrzyckie Mountains), later confronted with nine-group classification. In both areas automatic classification for k = 5 ÷ 6 performed well and the principal features of relief are well captured, despite very different landform patterns and long-term geomorphic histories. Slope and curvature are the main variables to differentiate individual terrain units (landforms), with an additional role of aspect in the faulted and tilted plateau. For k > 6 aspect becomes the main variable in the hilly relief and the pattern of terrain units becomes more fragmented, adversely impacting on the clarity of interpretation, while surfaces in the faulted plateau setting are further subdivided according to slope and curvature. The match between ‘expert’ maps and the results of automatic classification varies, depending on the landforms considered. While certain landforms are clearly associated with one particular group yielded by automatic classification, others fall into a number of groups and do not have distinctive signatures, despite different origins.