COMPARATIVE ANALYSIS OF AUTOMATIC PATTERN MORPHOMETRICAL LANDFORM CLASSIFICATIONS BASED ON DIGITAL ELEVATION MODELS

Abstract

The paper presents a comparative analysis of automatic geomorphometric classifications based ondigital elevation models using different methods, in particular, the method of classifying landforms basedon the topographic position index (TPI) and the geomorphon method. For the purpose of comparativeanalysis of the classification results, these methods were tested on two key square-configured areas withdifferent terrain morphology oriented along the main sides of the horizon within the Dnipro region. As aresult of the study, it was found that the topographic surface patterns identified by the geomorphon methodprovide more accurate and reliable results in large-scale studies compared to the use of TPI. It was foundthat the method based on the topographic position index is the most suitable for medium- and smallscalemapping, since it showed less details with the same parameters of the outer search radius. The mainproblem of geomorphometric analysis is that a clear delineation of landforms is often impossible becausethey do not have clear boundaries, and thus the interpretation of these forms, despite the mathematicalbasis of classifications, is still quite subjective. For the first time in Ukraine, a new digital elevationmodel FABDEM with a spatial resolution of 1 arc second was tested for large-scale geomorphometric analysis in key areas, and its advantages and disadvantages were identified in comparison with othersimilar global models. The study clarified the basic terminology of geomorphometric research, proposedUkrainian-language equivalents to the classes of terrain forms developed in foreign literature. Thenecessity of distinguishing between types of digital models, namely, digital elevation model (DEM)and digital surface model (DSM) in the context of understanding the terrain as an organization of theelevation field was substantiated. The application of automatic classifications will solve the problem ofthe high cost and complexity of manual analysis of landforms and will accelerate the creation of largescalegeomorphological maps with nationwide coverage.