Over the years, the accessibility, frequency, and accuracy of digital elevation models (DEMs) evolved. With so much quality data, interpretation of DEMs has become a common source for geographical analysis in various fields, including geodetic survey, engineering, cartography, hydrology, landscape architecture, spatial planning, energetics, archaeology, and many more. DEM is usually visualized with grayscale. Every user seeks certain information from DEM. Interpretation of DEM, when represented with grayscale, is not an intuitive representation of terrain, and some landscape features cannot be detected. Therefore, scientists developed different visualization techniques (methods) of DEM that are effective for interpreting and detecting small landscape features of the terrain. In this master's thesis, we upgraded the Relief Visualization Toolbox (RVT) to be used in ArcGIS Pro geographic information system software. We implemented RVT visualizations and other visualization techniques into ArcGIS Pro as ArcGIS Python raster functions. Featured visualization techniques are: slope gradient, hillshade, multi directional hillshade, Simple Local Relief Model, Multi-Scale Relief Model, sky-view factor, anisotropic sky-view factor, local dominance, Multi-Scale Topographic Position, Visualization for Archeological Topography, Visualization for Archeological Topography Combined, Color Relief Image Map (developed by us), enhanced Multi-Scale Topographic Position version 3 (developed by us). We tested the performance of the created ArcGIS Python raster functions (visualizations) on different computers.
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