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Unmanned aerial systems (UASs) offer a less invasive solution for accessing remote areas and sites, making them valuable in Architecture, Engineering, Construction, and Operation (AECO). Their ease of use, ability to reach previously inaccessible areas, and sensor integration provide new project perspectives. Augmented Reality (AR), which allows for the real-time insertion of virtual elements into physical spaces, is also being explored in the AECO industry. Recognizing the potential of these technologies, this research aims to integrate them for on-site building model visualization. This article presents the development of resources to visualize building design implementation in AR, which is supported by UASs through georeferencing. The system development process included establishing the software architecture, creating interface prototypes, and constructing the model. It was possible to visualize the building model in AR within the real world; however, limitations were identified regarding the UAS used and its Application Programming Interface, which affected the aircraft's programmed trajectory. The contribution of this paper lies in exploring the utilization of georeferenced AR enabled by UAS for visualizing architectural designs on site, detailing the steps and strategies employed to achieve this, highlighting the limitations of the chosen approach, and proposing potential solutions to the issues identified in the research. [ABSTRACT FROM AUTHOR]

In April 2001 a rock fall at the Lärchberg-Galgenwald with boulders of several cubic meters in size did occur, which reached until the 50 to 70 m wide apron of the Federal Highway B96. This event triggered the installation of a fivemeter-high protective dam and the start of a geodetic monitoring program based on rope extensometer measurements and a geodetic survey. This study area is used to test further methods of image processing-based monitoring and to show the advantages and disadvantages with the focus on the main area of the landslide. The two technologies used are structure-from-motion (SfM) and terrestrial laser scanning technology. Both systems work through contactless data acquisition by active and passive recording processes. A data set in the form of a point cloud and a digital surface model with a grid size of 10 cm, which are checked for accuracy on the basis of measured control points, was created across all methods. As a further approach, the fusion of the point clouds from the flight using an unmanned aerial vehicle (UAV) and the laser scan point clouds was carried out. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) photogrammetry is one of the most effective methods for capturing a terrain in smaller areas. Capturing a steep terrain is more complex than capturing a flat terrain. To fly a mission in steep rugged terrain, a ground control station with a terrain following mode is required, and a quality digital elevation model (DEM) of the terrain is needed. The methods and results of capturing such terrain were analyzed as part of the Belca rockfall surveys. In addition to the national digital terrain model (NDTM), two customized DEMs were developed to optimize the photogrammetric survey of the steep terrain with oblique images. Flight heights and slant distances between camera projection centers and terrain are analyzed in the article. Some issues were identified and discussed, namely the vertical images in steep slopes and the steady decrease of UAV heights above ground level (AGL) with the increase of height above take-off (ATO) at 6%-8% rate. To compensate for the latter issue, the custom DEMs and NDTM were tilted. Based on our experience, the proposed optimal method for capturing the steep terrain is a combination of vertical and oblique UAV images. [ABSTRACT FROM AUTHOR]

Earth observation offers a variety of techniques for monitoring and characterizing geomorphic processes in high mountain environments. Terrestrial laserscanning and unmanned aerial vehicles provide very high resolution data with high accuracy. Automatic cameras have become a valuable source of information—mostly in a qualitative manner—in recent years. The availability of satellite data with very high revisiting time has gained momentum through the European Space Agency's Sentinel missions, offering new application potential for Earth observation. This paper reviews the status of recent techniques such as terrestrial laserscanning, remote sensed imagery, and synthetic aperture radar in monitoring high mountain environments with a particular focus on the impact of new platforms such as Sentinel-1 and -2 as well as unmanned aerial vehicles. The study area comprises the high mountain glacial environment at the Pasterze Glacier, Austria. The area is characterized by a highly dynamic geomorphological evolution and by being subject to intensive scientific research as well as long-term monitoring. We primarily evaluate landform classification and process characterization for: (i) the proglacial lake; (ii) icebergs; (iii) the glacier river; (iv) valley-bottom processes; (v) slope processes; and (vi) rock wall processes. We focus on assessing the potential of every single method both in spatial and temporal resolution in characterizing different geomorphic processes. Examples of the individual techniques are evaluated qualitatively and quantitatively in the context of: (i) morphometric analysis; (ii) applicability in high alpine regions; and (iii) comparability of the methods among themselves. The final frame of this article includes considerations on scale dependent process detectability and characterization potentials of these Earth observation methods, along with strengths and limitations in applying these methods in high alpine regions. [ABSTRACT FROM AUTHOR]