Suitability of Digital Elevation Models Generated by Uav Photogrammetry for Slope Stability Assessment (Case Study of Landslide in Svätý Anton, Slovakia)

Abstract

Assessing the accuracy of photogrammetrically-derived digital elevation models (DEMs) from UAV is essential in many geoscience disciplines. The suitability of different DEM devised for slope stability assessment was evaluated in the example of the landslide in Svätý Anton village in Slovakia. Aerial data was acquired during a one-day field campaign in autumn 2014. The point cloud from 218 images (54,607,748 points) was manually classified into 7 different classes for filtering vegetation cover and buildings. Assessment of vertical differences between the UAV derived elevation model and real terrain surface was based on comparison of control points targeted by GPS (337 points) and unclassified and ground classified point cloud for raster elevation models with 1, 5, 10, 20 and 50 cm pixel resolution.

Monitoring of avulsion channel evolution and river morphology changes using UAV photogrammetry: Case study of the gravel bed Ondava River in Outer Western Carpathians

“…These authors reported that topographic mapping applied to DEMs from UAV in environments with minimal surface vegetation established a 0.26 m vertical elevation difference between DEMs from UAV and GPS points. Further, Niethammer et al (2012) and Rusnák et al (2016) concurred that the overriding restriction in geomorphic studies is caused by vegetation impeding topography identification by photogrammetricallyderived DEM in continuously low-vegetation covered areas which cannot be classified or removed.…”

“…() and Rusnák et al. () concurred that the overriding restriction in geomorphic studies is caused by vegetation impeding topography identification by photogrammetrically‐derived DEM in continuously low‐vegetation covered areas which cannot be classified or removed.…”

Image Processing of UAV Imagery for River Feature Recognition of Kerian River, Malaysia

“…However, the optical data acquisition of UAVs cannot pierce through vegetation cover and terrain features [45]. Another limitation of UAV technology is that the region with extensively low vegetation is unclassified in removal from the surface [46], but point cloud acquisition from the ground under the vegetation is possible using UAV LIDAR [47]. Another disadvantage of using small UAV platforms is that it limits the payload, while implementing drone-based imaging to capture temporal images of the same cross-sections is a tedious job.…”

Object-Based Classification of Urban Distinct Sub-Elements Using High Spatial Resolution Orthoimages and DSM Layers

“…These technological advances allow for high-quality mapping of the earth's surface using Orthoimages and also mean that 3D models (meshes) of the earth's surface can be created with high resolution and accuracy. Alongside this, advances in computer hardware and image matching software have also meant that stereo images can be compared faster and more accurately than ever before, thus making photogrammetry a viable alternative to manned aerial photography [18] [19] [20]. In spite of these advantages though, UAVs often have weight and cost restrictions which mean that the sensors used in them are often lower quality than those that would be used during manned aerial photography.…”