Monitoring of anthropogenic landslide activity with combined UAV and Lidar-derived DEMS a case study of the Czerwony wawoz landslide (SW Poland. Western Sudetes)

Abstract

The paper presents the results of fieldwork and geodetic surveys carried out on a landslide in Wleń (Western Sudetes, Izerskie Foothills). This reactivated landslide occured firstly in 2011 and later on 16th July 2016, following heavy rainfall in the Lower Silesia region, and covered an area of ca. 1100 m 2 above the renovated "Leśny Dwór" guesthouse in Wleń town. The main scarp of the landslide is built of strongly deformed Upper Permian (Zechstein) heterolithic deposits, composing the marginal part of the Wleń Graben -a NW-SE elongated, tectonic subunit within the North Sudetic Synclinorium. The landslide was a consequence of undercutting of steep slopes of the Bóbr River valley by anthropogenic activities and loading of the slope surface by blocks and pedestrian paths in the vicinity of the guesthouse. Monitoring of landslide activity was performed using the initial surface model of the slope subjected to mass movements, LiDAR elevation data, as well as 3D point cloud data from a nonmetric camera on an Unmanned Aerial Vehicle (UAV). They were used to construct digital elevation models (DEMs) of the area covered by the landslide. The DEM from photogrammetric UAV data was processed using Structure from Motion (SfM) technology. The obtained dataset was verified by additional measurement series from terrestrial laser scanning (TLS). Cite this article as: KowalskiA, Wajs J, Kasza D: Monitoring of anthropogenic landslide activity with combined UAV and LiDAR-derived DEMs -a case study of the Czerwony Wawóz landslide (SW Poland, Western Sudetes).

Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection

“…For this purpose, we decided not to use interpolation during this research, neither to extract TIN data format files, to minimise the corresponding error. Many researchers seem to start utilising the differentiated maps or the M3C2 algorithm and point cloud comparison in landslide detection, flood events, or even in forests' analysis [14,[69][70][71]. There are applications, where high-quality texture reconstruction is needed, as in fault slip rates assessment or signal absorption-based surveys [15][16][17][18][19].…”

Measuring Annual Sedimentation through High Accuracy UAV-Photogrammetry Data and Comparison with RUSLE and PESERA Erosion Models

“…This multi-vector analysis denotes the complexity of the microsurface, which cannot be accurately represented by 2.5D DEM data and the interpolation method [83]. The M 3 C 2 algorithm that we selected as the baseline for surface change detection is currently used in a broad field of geo-research applications, such as landslides, flood events, post-fire erosion, and forests [44,45,[118][119][120]. In this study, we managed to achieve a cm-accuracy of the microsurface reconstruction, leading to high-accuracy sediment pathway and distribution delineation.…”