Displays

Evaluating the multi-hazard performance of river crossing bridges under probable earthquake, flood, and scouring scenarios is a cumbersome task in performance-based engineering. The loss of lateral load capacity at bridge foundations may induce bridges to become highly vulnerable to failure when the effects of scour and floods are combined. Besides, the assessment of local scouring mechanism around bridge piers provides information for decision‐making regarding the pile footing design and for predicting the safety of bridges under critical scoured conditions. Thereby, accurate high-resolution Digital Elevation Models (DEMs) are critical for many hydraulic applications such as erosion, hydraulic modelling, sediment transport, and morphodynamics. In the present study, an automated unmanned aerial vehicle (UAV) based multi-hazard performance assessment system was developed to respond to rapid performance evaluation and performance prediction needs for river crossing reinforced concrete (RC) bridges. The Bogacay Bridge constructed over Bogacay in Antalya, Turkey was selected as the case study. In the developed system, firstly the seasonally acquired UAV measurements were used to obtain the DEMs of the river bed from 2016 to 2019. The transverse cross sections of the river bed that were taken close to the inspected bridge were used to measure the depth of the scoured regions along the bridge piles under the present conditions. Separately, in conjunction with the flood simulation and validation with 2003 flood event (corresponds to Q₅₀=1940 m³/s), the scour depth after maximum probable flood load according to the return period of 500 years (Q₅₀₀=2560 m³/s) were predicted by HEC-RAS software. Afterwards, the 3D finite element model (FEM) of the bridge was constituted automatically with the developed code considering the scoured piles. The flood loads were exerted on the modeled bridge with regard to the HEC-RAS flood inundation map and relevant water depth estimations around the bridge piers. For the seismic evaluation, nonlinear time history analyses (THA) were conducted by using scaled eleven scaled earthquake acceleration records that were acting in both principal axes of the bridge simultaneously by considering maximum direction spectra (SaRotD100) as compatible with the region seismicity. In the analyses; as the scour depth increased, the fundamental periods, shear forces and the bending moments were observed to increase while the pile lateral load capacities diminished. Therefore, the applicability of the proposed system was verified using the case study bridge.

How to cite: Özcan, O. and Özcan, O.: UAV Based Multi-Hazard Vulnerability Assessment System for Bridges Exposed to Scour, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-124, https://doi.org/10.5194/egusphere-egu2020-124, 2020.

Hundreds of thousands of people live and work in areas at risk of flooding, especially into deep valleys over the Italian territory. Floods cause fatalities and considerable economic damages to infrastructures and to private and public properties, besides impacting on fluvial-geomorphic landforms. During the last decade, these extreme events are occourring more frequently, contributing to increase the public awareness on the potential damaging consequences, and on the demand of monitoring and post-event assessment procedures. However, an efficient, systematic and accurate framework of post-event actions aiming to document the impacts of such disasters in terms of flooded areas, meteorological controls, geomorphological and vegetation change, is rare.

On this background, the role of the post-event surveys is fundamental to provide information/data and to increase knowledge for improving forecasting and designing the countermeasures. Flood events documentation consists in a series of field- and desk-based activities that request considerable consuming resources (time and human) and a high level of technical expertise. The post-event analyses, then, should correctly balance the different activities and efforts to reduce time and costs and then become a part routine post-event procedure.

The present study shows the results of a field campaign carried out after a flash flood occurred on June 12th 2019 along a 2 km stretch of Pioverna torrent in Valsassina (Lombardy, Italy). The survey consisted in collecting meteorological data, and video and pictures taken by inhabitants and rescuers for reconstructing field evidences of flood and the peak discharge. Few weeks after the flood, an Unmanned Aerial Vehicle (UAV) captured multiple images that were processed by Structure from Motion (SfM) photogrammetric algorithms, together with permanent Ground Control Points (GCPs) positioned on the riverbed and the streambanks, in order to obtain a high-resolution topography data. The methodology is likely to be truly effective if a pre-event photogrammetric survey is available for the same stretch, as in the present case.

The UAV photogrammetric surveys expected to be able to detect: (i) the geomorphological changes including streambank erosion, sediment deposition and the general stream evolution; (ii) the flood-damaged areas including buildings and roads (useful for estimating economic losses) and hydraulic structures (useful for giving a priority to the restoration works); (iii) the change in vegetation patterns that strongly influence the fluvial geomorphological processes.

In such a perspective, a simple methodology has been developed and applied to obtain a good balance between accuracy, time-consuming, efforts and collected data. In addition, it has been showed how the post-flood campaign has a strategic significance for a wide spectrum of multidisciplinary aspects (damage assessment, hydraulics, and ecology) and allows to rapidly reconstruct the flood event and its consequences. Standardizing such procedure should be extremely important to collect similar data, useful to improve specific guidelines and post-emergency management plans.

How to cite: Cislaghi, A., Moscaritoli, A., Fogliata, P., Sala, P., Morlotti, E., Fontana, M., Sulis, A. N., and Bischetti, G. B.: Unmanned Aerial Vehicle surveys for monitoring and managing river system: a case study in Valsassina (Northern Italy), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6884, https://doi.org/10.5194/egusphere-egu2020-6884, 2020.

One of the potential major consequences of mining activities is the degradation of the surrounding ecosystems by Acid Mine Drainage (AMD). A high-resolution hyperspectral drone-borne survey provides a useful, fast, and non-invasive tool to monitor the acid mine drainage mineralogy in mining sites. In this study, we propose to integrate drone-borne visible-to-near infrared (VNIR) hyperspectral data and physicochemical field data from water and sediments together with laboratory analysis for precise mineralogical and surface water mapping. The Tintillo River is an extraordinary case of the collection of acidic leachates in southwest Spain. This river is highly contaminated, with large quantities of dissolved metals (Fe, Al, Cu, Zn, etc.) and acidity, which later discharged into the Odiel River. At the confluence of the Tintillo and Odiel rivers, different geochemical and mineralogical processes typical of the interaction of very acidic water (pH 2.5 – 3.0) with circum-neutral water (pH 7.0 – 8.0) occur. The high contrast among waters makes this area propitious for the use of hyperspectral data to characterize both rivers and better evaluate mine water bodies with remote sensing imagery. We present an approach that makes use of a supervised random forest regression for the extended mapping of water properties, using the data from collected field samples, as training set for the algorithm. Experimental results show water surface maps that quantify the concentration of dissolved metals and physical-chemical properties along the covered region and mineral classification maps distribution (jarosite, goethite, schwertmannite, etc.). These results highlight the capabilities of drone-borne hyperspectral data for monitoring mining sites by extrapolating the hydrochemical properties from certain and specific areas, covered during field campaigns, to larger regions where accessibility is limited. By following this method, it is possible to rapidly discriminate and map the degree of AMD contamination in water for its future treatment or remediation.

How to cite: Flores, H., Lorenz, S., Jackisch, R., Tusa, L., Contreras, C., and Gloaguen, R.: Integrated Environmental Monitoring of AMD Affected Waters using Hyperspectral Imaging and In-situ Analytics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17124, https://doi.org/10.5194/egusphere-egu2020-17124, 2020.

The availability of consumer remotely piloted aircraft systems (RPAS) has enabled rapidly deployable airborne surveys for civilian applications. Combined with photogrammetric reconstruction techniques, such as Structure-from-Motion (SfM), it has become increasingly feasible to survey large areas with very high resolution, especially when compared with other airborne or spaceborne surveying techniques. A pair of case studies, using an RPAS-based field surveying technique for establishing baseline surface models in steep terrain, are presented for two different natural hazard applications.

The first case study involved a survey over the entire 1000-m length of a snow-free avalanche path on Sætreskarsfjellet in Stryn municipality in Norway. A terrain-aware, multi-battery flight plan was designed to ensure good photographic coverage over the entire avalanche path and 21 ground control points (GCP) were distributed evenly across the path and subsequently surveyed. More than 400 images were collected over a 0.5 km² area, which were processed using a commercial SfM software package. Two digital surface models were reconstructed, each utilizing a different ground control scenario: the first one with the full count of GCP, while the second used only a limited count of GCP, which is more feasible for a repeat survey when avalanche hazard is high. Comparison with data from a pre-existing, airborne LiDAR survey over the avalanche path revealed that the SfM-derived model that utilized only a limited number of GCP diverged significantly from the model that utilized all available GCP. Further differences between the SfM- and LiDAR-derived surface models were observed in areas with very steep slopes and vegetative cover. The same methodology can subsequently be applied during the winter season, after extensive snowfall and/or avalanche events, to deduce relevant avalanche parameters such as snow height, snow distribution and drift, opening of cracks in the snow surface (e.g. for glide avalanches), and avalanche outlines.

The second case study involved a survey over the entire 1000-m length of a debris flow path at Årnes in Jølster, Norway. The Årnes flow, which caused one fatality, was one of the largest of several tens of debris flows that occurred on July 30, 2019. The flows were triggered by an extreme precipitation event around the Jølstravatnet area. Like with the Sætreskarsfjellet avalanche path case study, a terrain-aware flight plan was established and 24 GCP were distributed and surveyed along the debris flow path. Over 400 images were collected over a 0.3 km² area, which were used to reconstruct a high-resolution surface model. Like with the avalanche case study, the SfM-derived model was compared with a pre-existing LiDAR survey-derived digital terrain model. Altitude and volume changes, due to the debris flow event, were calculated using GIS analysis tools.

The utility of the RPAS survey technique was demonstrated in both case studies, despite difficult accessibility for ground control. It is suggested that a real-time-kinematic (RTK)-enabled workflow may significantly reduce survey time and increase personnel safety by minimizing the number of required GCP.

Keywords: Structure-from-Motion, photogrammetry, digital surface model, natural hazards, ground control.

How to cite: Salazar, S., Smebye, H., Frauenfelder, R., Miller, F., Solbakken, E., Humstad, T., and McCormack, E.: Airborne Structure-from-Motion modelling for avalanche and debris flow paths in steep terrain with limited ground control, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20529, https://doi.org/10.5194/egusphere-egu2020-20529, 2020.

Photogrammetric surveys from UAV and LiDAR surveys are two techniques that allow for the production of very high resolution point clouds. The use of these techniques result in a detailed reconstruction of difficult-to-access environments such as underground cavities. A rigorous georeferencing of the acquired data allows for a comparison of the hypogean development of the cave to the overlying territory. This study presents a case of integration between these two techniques, applied to the risk assessment of the collapse of the vaults in a natural cavity in the Trieste Karst (north east Italy). This site is particularly delicate given that on the slope above the cave there is an abandoned stone quarry. In order to survey the quarry above the cave, a flight was performed with UAV, while the cave was surveyed with Laser Scan from the ground. The flight was made using a UAV DJI Phantom RTK, which carried a 20 Mpixel 1“ sensor camera. 8 ha of terrain was surveyed, capturing about 733 high resolution images and surveying 22 GCPs (Ground Control Point) with a GNSS RTK receiver. It was possible to reduce the number of GCPs, since the drone recorded the shooting positions very accurately with the on-board GPS RTK. Data were analyzed using Agisoft Metashape Professional to produce an orthophoto and a DSM (Digital Surface Model) with a ground resolution of 0.02 m and 0.04 m respectively. The point cloud has a density of 586 points/m². The LiDaR survey was carried out using an ILRIS 3D ER laser scanner from Optec. The point cloud has a density of approximately 2500 points/m² and 5 stations were needed to cover the underground development of the cavity. The georeferencing of the data was carried out by roto-translation on geo-referenced benchmarks, surveyed with GPS RTK and total station. The point cloud was processed using Terrascan software (Terrasolid). The two point clouds were aligned, geo-referenced and combined using Polyworks software (Innovmetric), in order to check the thicknesses of the material present above the vault of the cave. The integration of epigean and hypogean data made it possible to identify some critical points related to a vault thickness of approximately 1.5 meters, located at the quarry square. This work made it possible to highlight critical issues difficult to detect without the integrated approach of these different survey methodologies.

How to cite: Martinucci, D., Pillon, S., Bezzi, A., Casagrande, G., Fontolan, G., Potleca, M., Bieker, F., Bratus, A., Manca, P., Blanos, R., and Paganini, P.: Integration of point clouds from UAV photogrammetry and laserscan survey for the assessment of the risk of collapse of the vault of an underground cavity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7669, https://doi.org/10.5194/egusphere-egu2020-7669, 2020.

Geological failures from massive rockfall failures to small landslides of few cubic meters are a major geological hazard in many parts of the world. Based on the latest developments, close-range photogrammetry and individually UAV photogrammetry and Light Detection and Ranging systems have become indispensable tools for geo-experts in order to provide ultra high-resolution 3D models of the failure site. TLS suffers from the fact that is sometimes tricky to capture the holistic area of interest from the ground, while some areas may often be obscured by vegetation or negative inclinations. The science of photogrammetry has long been used to accurately detect and characterize landslide and rockfall failures. Due to the continuously increasing spatial resolution capability of new generation sensors, traditional pixel-based approaches are not capable to cope with the level of detail resulted from those sensors. Mostly, landslides present complex and dynamic geomorphological features with great heterogeneity in their spatial, spectral and contextual properties dependent on the specific failure mechanism. In the current study, an object-based 3D approach for the automated detection of landslide and rockfall hazard is presented based on detailed topographic photogrammetric point clouds and 3D analysis. Recent trends show that close photogrammetry will play a vital role on the geological and engineering geological assessments concerning geo-failures. The results show that object-based approach is closer to human interception due to integration of contextual and semantic, spectral and spatial information rather than translating pixel’s spectral information solely. The current procedure provides a detailed objective quantification of landslide characteristics and automated semantic landslide modelling of the case site.

How to cite: Karantanellis, E., Marinos, V., and Vassilakis, E.: Landslide and Rockfall failures Characterization with Object-Based 3D Analysis , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21880, https://doi.org/10.5194/egusphere-egu2020-21880, 2020.

Railroad corridors in northern Idaho are subject to landslides, debris flows, and rock fall. These geologic hazards have the potential to severely impact railroad assets, profitability, and public safety, particularly when hazardous materials are transported. Recent slope instability and mass movement in these railroad corridors have affected rail operations and emphasized the need for a detailed understanding of geologic hazards and slope dynamics in this region. Idaho Geological Survey (IGS) and Idaho State University (ISU) conducted a series of Unmanned Aircraft Systems (UAS) missions equipped with LiDAR to survey selected landslides. This pilot project acquired high-resolution data at two sites along steep canyon slopes of the Kootenay River and one site along the Moyie River. The selected sites represent a diversity of terrain conditions, coverage area, forest canopy, and mass movement activity. In addition to collecting bare earth models of the landslide areas, this pilot project assessed resolution requirements, canopy penetration, and deployment complexity to provide a baseline for repeat surveys. Best practices for data collection and point cloud alignment for geohazard assessment are highlighted based on variations in terrain cover and slope.

How to cite: Delparte, D., Lifton, Z., and Belt, M.: Geohazard assessment of mass movements along railroad corridors with UAV LiDAR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22574, https://doi.org/10.5194/egusphere-egu2020-22574, 2020.

Geomorphological destabilisations in high mountain areas are often linked to permafrost degradation and changing precipitation intensities, induced by climate change. Considering the complex interaction between meteorological conditions, geology and topography, two alpine mass movements that took place in 2019 in the canton of Valais (Swiss Alps) were investigated with regard to their possible causes. During three consecutive summers (2017-2019), independent surveys were carried out on a high alpine talus slope at Col du Sanetsch (2100 – 2750 m a.s.l.) and an unstable rock face at Grosse Grabe, Mattertal (2600 – 2700 m a.s.l.), using unmanned aerial vehicle (UAV) and terrestrial laser scanning (TLS). The resulting high-resolution topography allows detecting and quantifying small and large geomorphic changes, such as rock tilting, rockfalls, rockslides, erosion and depositions of rock debris by snow avalanche action, debris channel cutting and fill and debris flow deposits. In both study areas, the summer of 2019 was characterized by mass movement events of greater magnitude than the geomorphic activity measured in the summers before.

At Grosse Grabe, the rock face was observed by webcam imagery since 2011, in the background of a rock glacier, which was initially the main object of survey. Isolated rock falls started in January 2017, launching a more accurate survey of the rock face by TLS in July 2017. In the next two summers, the entire unstable part of the rock wall, 70 m high, had been tilting at an increasing rate (1 to 3.3 cm/month). From mid-July until the end of October 2019, consecutive large rock fall events (up to > 10,000 m³) lead to the complete collapse of the monitored rock face (5000 m²), with a total volume of more than 60,000 m³. After the collapse of this heavily fractured, south facing rock face, the long-lasting wet rockfall scar indicated the presence of thawing permafrost ice. Beside the geological characteristics, which are favouring the rock wall instability, the consequences of the multi-decennial significant warming of the permafrost is presumably an implicated factor.

On the talus slope (2 km²) that was surveyed at Col du Sanetsch, a large debris flow event (ca. 20,000 m³ spread over multiple debris flow channels) was observed in the evening of 11 August 2019. Most of the mobilized sediments originated from incision of the talus apex area, while only a small part came from intermediate debris storage within rock wall gullies. An analysis of historical aerial photographs shows that the total displaced volume during the 2019 event exceeds each historical debris flow event that occurred on the talus slope since 1946.

In contrast to Grosse Grabe, where weather conditions have played no role on the development of the instability, the debris flow event at Col de Sanetsch is linked to an intense prefrontal supercell, causing rainfall intensities between 10 and 25 mm/h, in some places in less than 15 minutes. As such events are presumed to become more frequent with climate change, more debris flow events of this type can be expected in the future.

How to cite: Hendrickx, H., Delaloye, R., Nyssen, J., and Frankl, A.: Recent geomorphic destabilization of mountain slopes, a possible link to climate change? Two case studies from Switzerland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7037, https://doi.org/10.5194/egusphere-egu2020-7037, 2020.

The monitoring of landslides using UAVs is particularly convenient as these are dangerous areas that present access difficulties. This study aims to integrate monitoring carried out via traditional techniques (GNSS and total station surveys of benchmarks) with UAV photogrammetric survey, as the latter allows for a precise assessment of the volumes affected by movement. The Masarach landslide, located in Friuli Venezia Giulia (north east Italy), covers an area of approximately 200 ha. Two surveys were carried out two years apart in order to measure displacements of much greater magnitude than instrumental errors. In the first survey, restricted to the most active area, a six rotor UAV was used, with a maximum take-off mass of 4 kg, which carried a 20 Mpixel APS-C camera. 243 high resolution images were captured and 27 GCPs (Ground Control Point) were surveyed with a GNSS RTK reciever. In the second survey a DJI Phantom 4 Pro UAV was used, carrying a 20 Mpixel 1“ sensor camera. 978 high resolution images were captured and 40 GCPs (Ground Control Point) were surveyed with a GNSS RTK reciever. Data were analyzed using Agisoft Metashape Professional to produce an orthophoto and a DSM (Digital Surface Model) with a ground resolution of 0.02 m and 0.04 m respectively. The DSMs were compared in ArcGIS to calculate the moving masses and highlight the areas of greatest instability. It emerged that approximately 10,000 cubic meters of landslide material were transported to the Arzino stream below, with verified displacements on the control point ranging from meters to centimeters. This work made it possible to accurately define the most active portion of the landslide.

How to cite: Pillon, S., Martinucci, D., Bezzi, A., Casagrande, G., Fontolan, G., Bieker, F., and Bratus, A.: Monitoring of a landslide through the use of UAV survey, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7696, https://doi.org/10.5194/egusphere-egu2020-7696, 2020.

Characterising morphological changes in mountain areas is of fundamental importance for science
and engineering. Intense floods usually involve massive sediment transport, which may significantly
alter basin and river characteristics. Sediment erosion and deposition control the dynamics
of morphological structures such as alternate bars and meanders. By using unmanned aerial vehicles
(UAV), it has been possible to obtain high-precision bed elevation data at the sediment scale.
Our project aims to develop a consistent and optimised methodology for monitoring morphological
changes in an Alpine watershed using an UAV. Since 2017, we have been monitoring the Plat de la
Lé area drained by the River Navisence (Zinal, canton Valais, Switzerland). In mountainous regions,
poor accessibility and light conditions make it difficult to set control points on the ground. We first
analysed the relevance and influence of certain ground control points (GCP) on the the accuracy of
the digital elevation model (DEM) obtained from the UAV’s images. Errors in the GCP localisation
were much larger than the DEM resolution. Not only did the GCP number and flight height affect
these errors, as expected, but their positions and orientations also played a part. We then carried
out an additional monitoring campaign to understand the influence of these parameters on the DEM
accuracy. This campaign was ran on two areas: a steep-slope area with irregular topography and
a low-slope area that comprises the river channel and its floodplain. We built DEMs for each area
considering different GCP numbers (in the 3–18 range with 14 additional checkpoints) and flight
heights (in the 40–140-m range). The present study provides guidelines, including an optimal combination
of parameters that significantly reduce errors in the DEM, and a methodology that can be
used for monitoring Alpine watersheds on a regular basis.

How to cite: de Graffenried, B., Pascal, I., Trewhela, T., Martinez, V., and Ancey, C.: Assessing UAV survey performance for geomorphological monitoring of mountain rivers, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8526, https://doi.org/10.5194/egusphere-egu2020-8526, 2020.

Title: Methodology in the use of UAV ( Unmanned Aerial Vehicles ) by Assetto del Territorio sector of Liguria Region.

Authors: Davide Schenone , Daniele Bottero, Mariano Strippoli.

Liguria Region has recently equipped itself with a UAV ( Unmanned Aerial Vehicles ) system, consisting of a DJI Phantom  4 pro, the choice fell on this type of equipment as it guarantees a good quality for photographic shooting combined with an ease of use deriving from the fact of being designed for a consumer market, in fact this model mounts advanced anti-collision systems on board which make it safe to use even in closed places or near tall trees, the latter being a frequent situation in the use carried out by regional technicians.

In addition, maintenance is facilitated as spare parts (essentially batteries and propellers) can be found easily on the main online sites, given the widespread use of the model.

The use of the drone by the Assetto del Territorio consists mainly of two sectors, terrestrial photogrammetry and aerial photogrammetry.

The intervention scenarios are essentially of two types, survey of existing situations, for example, delimitation of landslides that may or may not have evolved, or the survey of post-disaster situations, both hydraulic and gravitational , it is also possible monitor the evolution of phenomena through multitemporal recovery .

The terrestrial photogrammetry it is so far little used by the Region and regarding  the capture of perspective images of buildings, cliffs useful for the relief geomechanical to evaluate rock mass, paleoseismic trenches (for upthrow of fault) etc.

As for the method of data acquisition (images), and the preparation of the flight plan, the DJI GS PRO software for iOS operating systems is used, this software allows to automatically set the flight parameters, simply by drawing on a map the polygon of the area to be surveyed and the flight height, it is also possible to adapt the orientation of the strips to the polygon of the survey.

However, this software does not require the use of a DTM , which takes into account the elevation of the terrain, so in case of relief of slope portions inclined taken the take off from the highest point since the calculation of the frames overlap is carried out assuming that the ground is flat , if it were not so taking off for example in the lower part it could happen that for purely geometric issues in the top part the overlapping of the frames is insufficient to arrive at a correct processing via software.

As regards the processing of immage in order to produce a cloud, depending on the cases of the DTM points and l ' orthophotos the software is normally used Metashape by Agisoft , the workflow typically used is this:

Adding photos

Alignment of photos - maximum resolution

Point cloud creation - medium resolution

DEM creation

How to cite: Schenone, D., Daniele, B., and Strippoli, M.: Methodology in the use of UAV ( Unmanned Aerial Vehicles ) by Assetto del Territorio sector of Liguria Region., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9233, https://doi.org/10.5194/egusphere-egu2020-9233, 2020.

Planpincieux is one of the glaciers located on the Italian side of the Mont Blanc (Italy). This glacier is monitored using a permanent monoscopic time-lapse camera since 2013. In 2019, the frontal part of the glacier has been characterized by a critical acceleration that could trigger a large ice avalanche able to reach the underlying Planpincieux village. During the emergency, the working group composed of Fondazione Montagna Sicura, CNR IRPI and the Aosta Valley Region Authority improved the monitoring system with a ground-based SAR to control the glacier evolution. An important data source used for a better understanding of the structure of the more unstable glacier sector has been the acquisition of a sequence of digital terrain models (DTMs) acquired by unmanned aerial vehicles (UAV) and helicopters. The approach adopted for the DTM generation is the acquisition of a photo sequence and the application of the structure from motion algorithm. The investigated area of the glacier is located in high-mountain environment and is characterized by a complex topography that does not facilitate the use of UAV. But the availability of a sequence of DTMs has been very useful for the improvement of the knowledge of the current state and recent evolution of the Planpincieux Glacier.

How to cite: Giordan, D., Dematteis, N., and Troilo, F.: UAV observation of the recent evolution of the Planpincieux Glacier (Mont Blanc – Italy), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9906, https://doi.org/10.5194/egusphere-egu2020-9906, 2020.

Measuring three-dimensional morphological changes in rocky coasts is essential in protecting the 

coastal areas and evaluating the sediment dynamics therein. In this study, we carried out repeated 

measurements of the three-dimensional morphology of a small rocky island using terrestrial laser 

scanning (TLS) and unmanned aerial vehicle (UAV)-based structure-from-motion (SfM) 

photogrammetry for 5 years. The TLS-derived point cloud data is used to align the UAV-SfM point 

cloud with a better accuracy at a centimeters scale, for which iterative closest point (ICP) method was 

applied. Aligned UAV-derived point clouds were then compared each other to extract changed mass 

for each time period. The extracted point cloud of changed mass was converted to 3D mesh polygons, 

by which the total volume of eroded mass was calculated.

The temporal analysis of the point cloud revealed spatially variable rockfalls and wave cuts. The 

eroded mass volume for each period varied from 10.6 to 527.7 m3, which is equivalent to the horizontal 

erosion rates of 0.03 to 0.63 m/y. The temporal changes in the eroded volume is roughly associated 

with that in the frequency of high tidal waves (higher than 3 m) observed in this area. However, less 

correlation was found with the frequency of large ground shakes by earthquakes. The modern erosion 

rate is lower than the previously reported cliff retreat rates, but this suggests that the small island will 

disappear in decades. Three-dimensional structural analysis will also help understand the dynamic 

processes of the erosion of the bedrock cliffs in the island.

How to cite: Hayakawa, Y. S. and Obanawa, H.: There-dimensional change detection in coastal cliffs using UAV and TLS, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18168, https://doi.org/10.5194/egusphere-egu2020-18168, 2020.

The recent advantages in Remote Piloted Aerial System (RPAS) and 3D Digital/Virtual Outcrop Model (DOM/VOM) development from RGB images (e.g. Structure from Motion, SfM;  Multi Stereo View, MSV; Simultaneous Localization And Mapping, SLAM)  have increased the application of these technology in stability analysis of unstable rock cliffs affected by rock fall due to possibility to perform analysis with higher resolution, accuracy, safety and time-saving to respect the traditional manual techniques, and with higher applicability and affordability to respect the Laser Scanner technology. The principal aims of a geoengineering  inspection of an unstable rock slope are to identify the possible Mode of Failure (MoF) of the rock mass (e.g. planar sliding, wedge sliding, toppling) and to estimate the rock volume that could be involved in a possible failure event. Then these results can be used for further numerical models and applications, as the rock fall simulations, here the uncertainty of the input parameters deeply influence the output results and, therefore, the reliability of the simulation. Due to the novelty of the RPAS-based DOMs, the uncertainty of the stability analysis is not always correctly identified (e.g. uncertainty equal to the DOM accuracy) and, therefore, sometimes the results and conclusion of the analysis could be partially wrong. Identifying and quantifying correctly the uncertainty is really important especially during emergency condition, when crucial decision must be made quickly.

In this study, the uncertainty of the stability analysis of the unstable rock cliff of Gallivaggio (Western Alps, Italy) is deeply investigated due to the possibility to compare the Mode of Failure and the unstable rock volume estimated before the failure event of the 29th May 2018 onto a DOM developed using the RPAS, with those identified and calculated after the failure. In particular, it is shown as uncertainty component of the instrumental error could be almost totally negligible to respect the components of the manual interpretation and analysis, also when no Ground Control Points (GCPs) are used to develop the DOM.

How to cite: Menegoni, N., Giordan, D., and Perotti, C.: Investigating and quantifying the uncertainty beyond the stability analysis of high unstable fractured rock cliff by Remote Piloted Aerial System (RPAS)-based Digital Photogrammetry: the example of the Gallivaggio landslide, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17806, https://doi.org/10.5194/egusphere-egu2020-17806, 2020.

High-mountainous Lake Sevan (Republic of Armenia) laying at an altitude of about 1900 m above sea level is a unique object of remote environmental monitoring due to the multidirectional dynamics of water level over the past 100 years. The artificial decrease in the lake water level began in 1930s, with the most intensive fall (over 10 m) from 1949 to 1962. In the 1990s, there was a slight increase in the level, then water level continued to fall until 2001. According to the current program of Armenian government, the lake level is planned to rise by at least 6 m in the coming years.

The current increase in water level of Lake Sevan leads to activation of both abrasive and accumulative coastal processes, intensification of eutrophication and mass flowering of lake waters. Planned increase in water level also threats residential and recreational facilities which are abundant along shoreline of Lake Sevan. At the same time, the spatial and temporal differentiation between the current intensity of coastal processes and the state of coastal ecosystems is quite significant. In order to reveal the regularities of this differentiation, we preliminary carried out a retrospective large-scale mapping of the shoreline dynamics of Lake Sevan using archival and modern cartographic small-scaled materials and high-detailed remote sensing data for the period of over 100 years. Based on the results of interpretation of the mosaic of large-scale aerial imagery of 1960s different types of coasts were identified; the speed of receding of the lake shoreline during the period of its maximum decline was reconstructed.

For several chosen key coastal areas, characterized by the most significant changes in shoreline and different types of current coastal processes, since 2018 we have been conducting operational remote monitoring of the coastal zone from light-weight UAVs DJI Phantom 4 Pro. UAV surveys are conducted at the low altitude range (100–200 m) with the use of both optical and thermal cameras. Resulted multitemporal UAV data are dense photogrammetric point clouds (with the density more than 300 points per sq. m), three-dimensional digital surface and terrain models with spatial and vertical resolution up to 10 cm, ultrahigh-detailed orthoimagery with the spatial extent about 1 sq. km. Thematic interpretation of acquired UAV data resulted to detailed land cover mapping of key coastal areas, reliable detection of local sources of water pollution, identification of buildings and facilities more threatened to inundation under the different scenarios of water level rising. The integral synthetic assessment is made for the current environmental state of coastal ecosystems under risk. Among more vulnerable ecosystems are coastal lagoons with associated wetland complexes and planted coastal forests which being degraded and damaged as a result of increase in lake level and inadequate management can substantially contribute to the deterioration of integral water quality in Lake Sevan.

The study is supported by the RFBR project no. 18-55-05015-Arm_a.

How to cite: Medvedev, A., Telnova, N., Alekseenko, N., and Koshkarev, A.: The use of UAV data for environmental monitoring of the coastal area of Lake Sevan, Armenia under the increase in water level, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19748, https://doi.org/10.5194/egusphere-egu2020-19748, 2020.

The use of unmanned aerial vehicles (UAV) for ground surface measurements in natural hazard studies has strongly increased in recent years. Multi-temporal 3D point clouds derived from light detection and ranging (LiDAR) sensors and photogrammetric techniques including structure-from-motion (SfM) and dense image matching (DIM) have become important tools for monitoring the activity of geomorphic processes. However, due to georeferencing errors and measurement inaccuracies, change detection with centimeter precision remains challenging, especially in study areas covered by vegetation. This study aims at quantifying the influence of low vegetation on the vertical uncertainties of 3D point clouds in a study area mostly covered by meadows and pastures with different grass heights. 3D point clouds derived from UAV-SfM and UAV-LiDAR are compared to terrestrial ground surface measurements of a differential global navigation satellite system (dGNSS) receiver in order to quantify the vertical uncertainties and to detect advantages/disadvantages of the different sensors. The results indicate that neither method is able to detect the ground surface under dense low vegetation with centimeter precision, and that surface displacement rates derived from multi temporal analyses can be highly influenced by changes in vegetation height between surveys.

How to cite: Fischer, S., Hormes, A., Adams, M. S., Zieher, T., Bremer, M., Rutzinger, M., and Otto, J.-C.: Quantifying the influence of low vegetation on vertical uncertainties of 3D point clouds derived from UAV-based ground surface measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20468, https://doi.org/10.5194/egusphere-egu2020-20468, 2020.

Mountain environments are particularly vulnerable to ongoing climatic and environmental changes. Specifically, alpine grasslands are seriously threatened by shallow erosion which has been increasingly detected during the last decades on alpine meadows and pastures. It has been suggested that a high plant species diversity of alpine grassland communities may increase the erosion resistance of soils, mainly through positive effects on root length, number of root tips and foliage abundance. Moreover, high plant biodiversity has shown to stabilize water channels by giving slope instability. Against this background, we used Earth Observation to map grassland communities and to understand the link between species diversity and the presence of shallow erosion spots in an alpine region.

Our study site is within the valley of Funes in South Tyrol, Italy where shallow erosion spots have multiplied in the last years and decades. The study site is over 2300 m above sea level and covers an area of approximately 5 ha. We mapped the grassland vegetation in this area with using different technologies: The main data source was a hyperspectral image with overall 28 spectral bands (506 nm to 896 nm) and a 5 cm spatial accuracy acquired from a UAV flight campaign in 04.09.2019. Our reference data set comprised detailed ground measurements within 50x50 centimeter plots. Overall, we acquired field spectroradiometer measurements covering the spectral range from 339 nm to 2500 nm (1024 spectral bands), ground-based hyperspectral measurements and sampled the different grassland communities within the plots. Based on the data integration of two different scaled field measurements and the UAV mapping we were able to detect the main grassland community occurrences and hotspots in species-level with high accuracy.

How to cite: Papp, L., Mejia-Aguilar, A., Sonnenschein, R., Tonin, R., Loebmann, M., Geitner, C., Rutzinger, M., Mayr, A., and Lang, S.: Mapping of high-elevation alpine grassland communities based on hyperspectral UAV measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22013, https://doi.org/10.5194/egusphere-egu2020-22013, 2020.

Mountainous areas bring unique challenges for surveying and natural hazard monitoring – inaccessibility, dangerous terrain, snow coverage and line-of-sight problems often make it next to impossible to perform ground-based monitoring or even to provide a good vantage point for close-range sensing (e.g. terrestrial laser scanning (TLS) or terrestrial photogrammetry). Airborne or satellite-based methods are often the only way to gain information about geodynamically active sites. Here, structure-from-motion (SfM) photogrammetry from unmanned aerial vehicle (UAV) imagery in particular can provide an inexpensive and easily implemented monitoring option. The Vigilans research project attempts to evaluate the feasibility of UAV-photogrammetry against more established surveying methods (e.g. in situ data from extensometers or total stations).

Our study site Marzellkamm is located in the Central Ötztal Alps of Western Austria. The active rock slope deformation we are monitoring in Vigilans lies at 2450-2850 m asl. on a SE-facing slope. Annual displacement rates of up to 1.5 m/year in the early 2010’s triggered monitoring and research interest. Due to the remote location, mitigation methods were not implemented, but a hiking trails was relocated. Orthoimage photogrammetry and ground-based monitoring instrumentation (extensometers, terrestrial laser scanning, total station measurements combined with GNSS and geodetic surveys) collected data 1971-2019.

In the last years, movement along the slope has slowed down considerably. The rather slow current movements provide a valuable challenge for detection, with rates of <0.05 m/year occurring in the more stable upper sections, while the NW section in particular still shows pronounced movement of up to 0.3 m/year. For this reason, Marzellkamm provides excellent evaluation for new methods such as UAV-SfM.

In three separate missions between summer 2018 to fall of 2019, UAV-SfM 3D-models of the site were created for displacement rate evaluations; it is planned to continue this monitoring for a total of three years as part of the Vigilans project. Photogrammetric missions were performed in conjunction with total station measurements of more than 30 ground control points.

The required level of precision is becoming achievable and affordable with new RTK/PPK-equipped (Real-Time-Kinematics/Post-Processed Kinematics) UAVs. However, evaluating the resulting 3D-- model in terms of movement rates remains non-trivial. The most common algorithm for change detection in point clouds, M3C2, is not well-suited to detect a laterally moving surface as a whole, as it detects changes along the normal orientation of a surface (such as subsidence). Therefore, the point cloud needs to be very selectively reduced, requiring complex filtering operations and expert input as well as expensive software packages.

This contribution will present a workflow to simplify such evaluation, based on 2.5D (DEM-based) algorithms such as IMCORR and DoD (Difference-of-DEMs), in comparison with the more complex 3D-pointcloud based processing. The presented workflow is based on Agisoft Metashape and Open-Source software tools QGIS and Saga GIS. It aims to streamline UAV-based surveying work, 3D-model generation and simplified change detection into a repeatable and easily automatable framework. Special emphasis will be put on estimating the quality of the recorded data.

How to cite: Demmler, C., Adams, M., and Hormes, A.: From UAV-photogrammetry to displacement rates – monitoring slope deformations in Alpine terrain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8468, https://doi.org/10.5194/egusphere-egu2020-8468, 2020.

The Project “BLUESLEMON – BT Beacon and Unmanned Aerial System technologies for Landslide Monitoring” is funded by provincial funds of South Tirol Italian Autonomous Province and it is developed with the support of Beacon Südtirol-Alto Adige project (funded by the south tyrolean European Regional Development Fund – www.beacon.bz.it) under the supervision of the NOI Techpark Südtirol/Alto Adige as support for consultancy, networking and R&D project backing for the use of UAS in alpine environments.

The project “BLUESLEMON” aims to develop a low-cost automatic system for monitoring landslide surface displacement through the integration of Bluetooth (BT) Beacons localization and UAS also named Remotely Piloted Aircraft System (RPAS) technologies. Two subsystems will assemble the final setup: the ground sensors technology and the periodic localization system composed by UAV and beacon reader. These are designed as an inseparable integrated architecture and each individual subsystem cannot operate on the supposed landslide areas without the cooperation of the other one. Thus, a main challenge consists in the identification of low-power-consumption and high-precision Bluetooth devices, as well as in the development of a UAV platform capable to work even at a limit of feasibility considered for an Alpine scenario (e.g. -20 °C at 2500 m asl). To prevent undesirable collisions with surrounding structures (e.g. trees, powerlines and funicular railways), the UAV platform will be equipped with obstacle-detection sensors and collision-avoidance algorithms.

The proposed architecture aims to exceed the state-of-the-art methodologies by obtaining a single low-cost system adaptable for the inspection of movements related to different types of gravity-driven natural hazards (e.g. slow-moving earth flows, discontinuities in rock walls). In addition, the expected autonomy of the system will allow to avoid the risky operations in-situ. Nowadays, the current methodologies (with or without UAS) are characterized by a high level of criticality in extreme environments such as the alpine surroundings. The solutions of the project’s requirements are of great interest for future reconfigurations of the developed system, in order to extend its use for search and rescue operations in dangerous conditions. Therefore, the suggested method will represent a strong novelty in the reference sector and lead to further application developments with considerable added value elements.

How to cite: Bojeri, A., Giannotta, G., Kofler, C., Mai, E., Mayrguendter, S., Scarton, G., Seppi, S., Steger, S., and Quagliotti, F.: A novel application of Unmanned Aerial Systems (UASs) in alpine environment for monitoring gravity-driven natural hazards: BLUESLEMON project, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18030, https://doi.org/10.5194/egusphere-egu2020-18030, 2020.