Towards Better Visualisation of Alpine Quaternary Landform Features on High-Resolution Digital Elevation Models

Abstract

Alpine topography is formed by a complex series of geomorphological processes that result in a vast number of different landforms. The youngest and most diverse landforms are various Quaternary sedimentary bodies, each characterised by its unique landform features. The formation of Quaternary sedimentary bodies and their features derive from the dominant building sedimentary processes. In recent years, studies of Quaternary sedimentary bodies and processes have been greatly aided by the use of digital elevation models (DEMs) derived by airborne laser scanning (ALS). High-resolution DEMs allow detailed mapping of sedimentary bodies, detection of surface changes, and recognition of the building sedimentary processes. DEMs are often displayed as hillshaded reliefs, the most common visualisation technique, which suffers from the limitation of a single illumination source. As a result, features can be barely visible or even invisible to the viewer if they are parallel to the light source or hidden in the shadow. These limitations become challenging when representing landforms and subtle landscape features in a diverse alpine topography. In this study, we focus on eleven visualisations of Quaternary sedimentary bodies and their sedimentary and morphological features on a 0.5 m resolution DEM. We qualitatively compare analytical hillshading with a set of visualisation techniques contained in the Raster Visualisation Toolbox software, primarily hillshading from multiple directions RGB, 8-bit sky view factor and 8-bit slope. The aim is to determine which visualisation technique is best suited for visual recognition of sedimentary bodies and sedimentation processes in complex alpine landscapes. Detailed visual examination of previously documented Pleistocene moraine and lacustrine deposits, Holocene alluvial fans, scree deposits, debris flow and fluvial deposits on the created visualisations revealed several small-scale morphological and sedimentary features that were previously difficult or impossible to detect on analytical hillshading and aerial photographs. Hillshading from multiple directions resulted in a visualisation that could be universally applied across the mountainous and hilly terrains. In contrast, 8-bit sky view factor and 8-bit slope visualisations created better visibility and facilitated interpretation of subtle and small-scale (less than ten metres) sedimentary and morphological features.

Revealing Subtle Active Tectonic Deformation: Integrating Lidar, Photogrammetry, Field Mapping, and Geophysical Surveys to Assess the Late Quaternary Activity of the Sava Fault (Southern Alps, Slovenia)

“…Small-scale geomorphic indicators were discovered, enabling us to measure the possible displacements that occurred since the end of Late Pleistocene. High-resolution datasets were previously successfully employed in this region to study small-scale geomorphological features to understand landslide and alluvial fan activity [122][123][124] as well as to derive the age of alluvial surfaces [112].…”

Not another hillshade: alternatives which improve visualizations of bathymetric data

“…Use of RVT is much less common in geoscientific studies which represent less than ten percent of the references (RVT, 2023). Among these, RVT is most commonly used to create visualizations in landslide research (Van Den Eeckhaut et al, 2012;Lo et al, 2017;Tsou et al, 2017;Chudýet al, 2019;Knevels et al, 2019;Verbovsěk et al, 2019;Guo et al, 2021) and geomorphology (Atkinson et al, 2014;Carrasco et al, 2020;Toth et al, 2020;Novak and Osťir, 2021;Rolland et al, 2022), while other geoscientific topics are represented by just a few papers (Mateo Laźaro et al, 2014;Djuricic et al, 2016;Favalli and Fornaciai, 2017;Delaney et al, 2018;Favalli et al, 2018;Lkebir et al, 2020;Craven et al, 2021;Delaney, 2022;Jamsěk Rupnik et al, 2022). The large discrepancy between the use of RVT in archeological vs geoscientific studies indicates the unrecognised potential for alternative visualization of elevation data in geosciences.…”

Multi-View Analysis of High-Resolution Geomorphic Features in Complex Mountains Based on UAV–LiDAR and SfM–MVS: A Case Study of the Northern Pit Rim Structure of the Mountains of Lufeng, China

“…Based on the 3D identification results (Figure 5b,c), it could be seen that each ridge extended in a bar from the highest part of the dividing line to the lower part, and some of the ridges The visualization results of the anisotropic sky-view factor (SVF-A) model [59] were able to provide basic mountain features, especially for ridges that rise on the outside. The ridge part would be more rightly illuminated, for the depression part was less illuminated and had a good outline between steep and flat surfaces for steep topography [60]. Thus, the SVF-A visualization result (Figure 5a), the 3D model, and the actual survey results were combined to divide the outside into ten independent ridges (Figure 5a).…”