In our contribution, we conduct a thematic literature review on trajectory estimation using a decentralized multi-sensor system based on robotic total stations (RTS) with a focus on unmanned aerial system (UAS) platforms. While RTS are commonly used for trajectory estimation in areas where GNSS is not sufficiently accurate or is unavailable, they are rarely used for UAS trajectory estimation. Extending the RTS with integrated camera images allows for UAS pose estimation (position and orientation). We review existing research on the entire RTS measurement processes, including time synchronization, atmospheric refraction, prism interaction, and RTS-based image evaluation. Additionally, we focus on integrated trajectory estimation using UAS onboard measurements such as IMU and laser scanning data. Although many existing articles address individual steps of the decentralized multi-sensor system, we demonstrate that a combination of existing works related to UAS trajectory estimation and RTS calibration is needed to allow for trajectory estimation at sub-$\mathrm{c}$$\mathrm{m}$ and sub-$0.01$ gon accuracies, and we identify the challenges that must be addressed. Investigations into the use of RTS for kinematic tasks must be extended to realistic distances (approx. 300–500 m) and speeds (>2.5 m s⁻¹). In particular, image acquisition with the integrated camera must be extended by a time synchronization approach. As to the estimation of UAS orientation based on RTS camera images, the results of initial simulation studies must be validated by field tests, and existing approaches for integrated trajectory estimation must be adapted to optimally integrate RTS data.

As part of the DFG research group “Sensitivity of high alpine geosystems to climate change since 1850” (SEHAG), high-resolution multibeam sonar data was collected from the proglacial Grastallake in the Ötztal valley during a boat survey in the summer of 2025. The Grastallake has an area of approximately 63,000 m², a maximum depth of approximately 16 m, and lies at an altitude of 2,584 m. The lake is situated in a former cirque, and its shores and the surrounding are partly composed of loose material and partly of solid rock. In the western part, there is a large whaleback with already known Egesen-moraines on top. On the southern and eastern shores, larger active debris flow cones are coupled to the lake, with meltwater runoff from the higher Grastalferner glacier flowing into the lake as a perennial stream via the eastern debris flow cone. Due to the permanent inflow from the glacier and the topographic conditions of the catchment area, the eastern debris flow cone is very active and has intensively been reshaped by several extreme debris flow events during the last years.The bathymetric data was collected using a Norbit multibeam sonar (WBMS), which was supplemented by an SBG INS system (dual GNSS patch antenna system, SBG Eclipse D) by Kalmar Systems. Since the underwater topography of the lake was unknown and its high turbidity due to the glacier inflow, the first step was to conduct a rough survey of the lake. This step made it possible to create a coarse depth map on site in order to identify spots with shallow water, determine the system settings, and draw up a navigation plan along strips. After field work the recorded data was processed using Quinertia for trajectory calculation and Opals for strip adjustment. This resulted in a final 3D point cloud with an average point density of 400 points per square meter, which was converted to raster data in order to perform spatial analyses.Using the data, geomorphological forms were mapped in a first step. In addition to a previously unknown late glacial moraine section, the underwater deposits of recent debris flows became visible. In addition to mapping, geomorphological structures were used for spatial analysis, such as comparing the depositions of debris flows above and below the water. Since the data is very well suited for mapping underwater structures, this case study demonstrates the enormous potential of bathymetric data acquired by multibeam sonar measurements, that has rarely been used for geomorphological studies to date. Multitemporal analysis in the sense of a 4D analysis could only be carried out to a limited extent in this case study. However, with the data now available, multitemporal analysis, i.e., quantification of sediment input into lakes, will also be possible in the future. This would then enable assessments to be made of the hazard potential of newly formed lakes in the proglacial area and of their lifespan.

The increasing occurrence of extreme weather events has a far reaching impact on all types of ecosystems. This includes submerged ecosystems, where floods and droughts influence the flora and fauna. Monitoring such submerged landscapes and their aquatic vegetation has gained interest in recent decades, and advances in remote sensing technology allow detailed mapping of those ecosystems. There, changes in vegetation extent throughout such extreme weather events remain insufficiently quantified, as comprehensive data sets before and after extreme weather events are rarely obtained. Thus, this study presents an extensive case study for a vegetated pond in Lower Austria, which was subjected to major flooding during the September 2024 flood in Austria. The presented data set includes aerial imaging and bathymetric LiDAR data for six epochs over three years, four before the flood and two after. This study presents the near-extinction of the submerged vegetation after the flood event and puts the results into perspective with the seasonal changes before the flood. For the three half-year periods before the flood event, the height of the vegetation shows a median fluctuation between −0.3 m to 1 m over the pond, while the change in vegetation height after the flood event has a median value of approximately −2.9 m. Although the seasonal changes are in alignment with the expected values, based on current research regarding the type of macrophytes present in the study area, the post-flood changes present a significant decrease in the overall vegetation. This, along with changes in turbidity, indicates a long-term impact on the pond and outlines the impact of extreme weather events on aquatic ecosystems. In general, the case study presents insights into rarely documented changes due to extreme weather events and provides a remote sensing approach to quantify changes in aquatic landscapes.