This session covers both new scientific approaches and state-of-the-art techniques for investigating landslides, including Earth Observation (EO), Geophysical Surveying (GS) and close-range Remote Sensing techniques (RS).
A series of remarkable technological progresses are driven new scientific opportunities to better understand landslide dynamics worldwide, including integrated information about rheological properties, water content, rate of deformation and time-varying changes of these parameters through seasonal changes and/or progressive slope damage.
This session welcomes innovative contributions and lessons learned from significant case studies and/or original methods aiming to increase our capability to detect, model and predict landslide processes at different scales, from site specific to regional studies, and over multiple dimensions (e.g. 2D, 3D and 4D).
A special emphasis is expected not only on the particularities of data collection from different platforms (e.g. satellite, aerial, UAV, Ground Based...) and locations (e.g. surface- and borehole-based geophysics) but also on new solutions for digesting and interpreting datasets of high spatiotemporal resolution, landslide characterization, monitoring, modelling, as well as their integration on real-time EWS, rapid mapping and other prevention and protection initiatives. Examples of previous submissions include using one or more of the following techniques: optical and radar sensors, new satellite constellations (including the emergence of the Sentinel-1A and 1B), Remotely Piloted Aircraft Systems (RPAS) / Unpiloted Aerial Vehicles (UAVs) / drones, high spatial resolution airborne LiDAR missions, terrestrial LIDAR, Structure-from-Motion (SfM) photogrammetry, time-lapse cameras, multi-temporal DInSAR, GPS surveying, Seismic Reflection, Surface Waves Analysis, Geophysical Tomography (seismic and electrical), Seismic Ambient Vibrations, Acoustic Emissions, Electro-Magnetic surveys, low-cost sensors, commercial use of small satellites, Multi-Spectral images, etc. Other pioneering applications using big data treatment techniques, data-driven approaches and/or open code initiatives for investigating mass movements using the above-described techniques will also be very welcomed.
GUEST SPEAKER (to be confirmed). Previous guest speakers include prof. J. Chambers (British Geological Survey - UK) and prof. D. Jongmans (Isterre, Université Grenoble Alpes - France).
vPICO presentations: Mon, 26 Apr
Over 2700 gravitational movements are recorded as polygons in the inventory of the Aosta region (3261 km2, Northern Italy). The surface affected by gravitational processes is about 20% of the overall surface area of the Aosta region and corresponds mostly to deep seated slope deformations, landslides and rock slope collapses. In addition, a complete set of multitemporal INSAR data has been recently made available for the same area (SqueeSAR processing by TRE, for both ascending and descending orbits, from October 2014 to February 2020).
In a first step, the distribution of INSAR data was analyzed with respect to landcover and radar geometric deformations. Main outcomes are:
- About 732’000 points were found by INSAR corresponding to a total average density of ~220 pts/km2.
- 0% of points have velocities below 1 mm/y, 20.4% between 1 and 10 mm/y, and only 0.6% more than 1 cm/y.
- The landcover is forested over 30% of the surface, covered by low vegetation on steep slopes for 46% and unvegetated for 24%, Points density are respectively 146, 200 and 369 pts /km2.
- Less than 5% of the Aosta region is affected by radar layover or shadowing. But, considering the slope direction as possible vector of displacement, 60% of INSAR velocities are underestimated of 50% or more when projected on the line of sight of the satellite (of course most of the time these are not the same slopes for ascending and descending orbits).
In a second step, we assessed the information provided by INSAR for the landslides recorded in the IFFI inventory:
- 29% of the polygons of the IFFI inventory do not include INSAR pts. However, those are mostly small zones, corresponding to only 9% of the total surface mapped as affected by gravitational movements. Most of large instabilities have INSAR points. 52% of the polygons have INSAR points from both ascending and descending orbits, and 19% from only one orbit.
- 68% of IFFI polygons have all their INSAR velocities slower than 5mm/y (for both orbits). It doesn’t mean automatically that these instabilities are dormant or slow moving, because for about half of them INSAR velocities strongly underestimate expected real velocities because of unfavorable projection on the line of sight of the satellites.
- 55 instabilities show INSAR velocities between 50 and 10 mm/y, and 31 faster than 10 mm/y.
Finally, an independent inventory was made using only the INSAR data and then compared to the IFFI inventory. In order to handle the data, a minimum velocity 2.5 mm/y was selected.
- 1437 instabilities were mapped in this inventory, covering 308 km2, for 2702 instabilities over 604 km2 in the IFFI inventory.
- About 60% of the moving area detected looking only at the INSAR data are visible on only one orbit (ascending or descending).
- 62 clusters of INSAR points with velocities higher than 1 cm/y and not in the IFFI polygons were detected. Among them, 4 sites with significant extensions will require further geological investigations.
How to cite: Derron, M.-H., Bossuat Pahud, D., Thuegaz, P., Bertolo, D., and Jaboyedoff, M.: Assessment of multitemporal INSAR data for establishing regional landslides inventories, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4550, https://doi.org/10.5194/egusphere-egu21-4550, 2021.
With the advances of ESA’s Sentinel-1 InSAR (Interferometric Synthetic Aperture Radar) mission there are freely available remote sensing ground deformation observations all over the globe that allows continuous monitoring of natural hazards and structural instabilities. The Digital Environment initiative in the UK aims to include these remote sensing data in the effort of forecasting and mitigating hazards across the UK.
However, analyses of low coherence areas (e.g. forested and vegetated areas) with conventional InSAR methodologies are difficult to perform due to the limiting factor of temporal and geometric decorrelation. Even the application of the permanent scatterer (PS) technique may not be successful when there is a low density of stable radar targets. Using artificial reflectors with high radar cross section (RCS) can be a way of overcome this limitation and achieve measurements with a good signal-to-clutter ratio (SCR).
In order to be able to include Sentinel-1 data in the UK’s Digital Environment it is important to understand the advantages and limitations of these observations and interpret them appropriately. The Hollin Hill landslide observatory in North Yorkshire is used by the British Geological Survey in their efforts to understand landslide processes, and to trial new technologies and methodologies for slope stability characterisation and monitoring.
We present InSAR results of the Hollin Hill landslide where a variety of ground-based geophysical measurements (e.g. GPS, Electric resistivity tomography, meteorological observations) are available for comparison with InSAR data. We use Sentinel-1 InSAR data acquired between Oct 2015 and Jan 2021 to study the behaviour of this landslide. We find that the Line of Sight component of the down-slope movement is 2.7 mm/yr in the descending track, and 7.5-7.7 mm/yr in the ascending track. The InSAR measurements also highlight the seasonal behaviour of this landslide.
In July 2019 six corner reflectors were installed to improve the coherence of the InSAR measurements, especially in the ascending acquisition mode. We present comparison with ground-based measurements such as the movement recorded by the GPS measurements of the pegs of the ERT survey or the moisture recorded by the various instruments at the site, and show the improvement introduced by the corner reflectors.
In addition we present results of an experiment that explores the use of smaller corner reflectors for potential urban applications of infrastructure monitoring. A single corner reflector needs to be at least ~67cm wide and tall to be seen by the Sentinel-1 satellites. We show that by placing 4 reflectors with 33cm dimensions in the same pixel coherent signal can be acquired. It is feasible to install small reflectors on bridges, tall buildings, or incorporate “corner-like” features in newly built structures,but care needs to be taken on the precise spacing of the reflectors to avoid destructive interference. Continuous monitoring of infrastructure with remote sensing and machine learning can alert to potential failures where further investigation is needed.
How to cite: Kelevitz, K., Chambers, J. E., Boyd, J., Novellino, A., Jordan, C., Biggs, J., Selvakumaran, S., Hooper, A., and Wright, T. J.: Using corner reflectors for enhancing landslide and infrastructure monitoring in the UK, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5133, https://doi.org/10.5194/egusphere-egu21-5133, 2021.
Geological hazards related to ground movements are difficult to assess at a regional scale due the lack of detailed information on the occurrence of the phenomena and the large number of potential vulnerable elements in the territory. Therefore, progress in analyzes at the regional scale can be a very useful tool for risk management.
This work, developed in the Alt Urgell and La Cerdanya counties (Catalunya, NE Spain) has served as the basis for the geological risk identification associated with ground movements. The methodology is based on the use of the Active Deformation Areas (ADA) detected by medium resolution radar satellite interferometry (Sentinel-1A and Sentinel-1B). The goal is to obtain a quick and semi-automatically classification of the ADAs according to the probable geological phenomena origin (landslides, rockfalls and subsidence).
This ADA classification is based on current data (DTM and geology) and easy to implement with GIS, takes in account: (i), landslide inventories, to allow the direct validation of the geological phenomenon; (ii) geology -information of the geological units type-; (iii) slope terrain -morphology-, determines the classification of the movement cause, depending on the slope, they are more or less prone to the generation of geological phenomena (e.g. slopes <35º: landslides); and (iv) land uses, determines the potential impact on vulnerable areas (e.g. high, in urbanized areas; low, in natural environments). This methodology provides an ADA first geological susceptibility categorization that allows optimizing and prioritizing efforts in detailed geological and geomorphological characterization works.
The clustering of scattering points gave a result of 361 ADA (over an area of around 2,000 km2), 145 was classified as potentially generated by a geological phenomenon (126 susceptible to landslides, 7 as rockfalls, 7 as subsidence and 5 as landslides or rockfalls) and 215 were classified as other causes.
Ideally, validation is based on contrasting the ADA with actual inventory data. However, the lack of complete and exhaustive inventories require validation based on classic methods such as photointerpretation and field work. All areas were checked by means of geomorphological analysis to ensure their susceptibility: 143 has identified as caused by geological phenomena, 153 has related with geological depositional process (rocky ground) and 65 has discarded.
This work has been supported by the European Commission under the Interreg V-A-POCTEFA programme (grant no. Mompa – EFA295/19).
How to cite: Fabregat, I., Casanovas, J., Marturià, J., Buxó, P., and Barra, A.: Semi-automated assessment of geological phenomena of Active Deformation Areas (ADA) detected by radar interferometry in Alt Urgell and Cerdanya, Catalonia (Spain), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12368, https://doi.org/10.5194/egusphere-egu21-12368, 2021.
Based on geomorphological criteria, large-scale slow gravitational deformation affecting entire mountain flank, often being referred as Deep-Seated Gravitational Slope Deformation (DSGSD), have been shown to affect most of the reliefs worldwide. For instance in the European Alps, these deformation patterns were identified in several areas such as the Aosta Valley (Martinotti et al., 2011) or the Mercantour massif (Jomard, 2006). DSGSD inventories based on visual interpretation of scarps and field mapping were then compiled (e.g. Crosta et al., 2013) revealing the widespread occurrence of DSGSD. However, many aspects of these large-scale gravitational processes remain unclear and in particular their present-day activity and temporal evolution remain largely unknown.
The present study aims at characterizing the spatial extent of DSGSD, and their velocity, at the scale of Western Alps through InSAR time series analysis using NSBAS processing chain (Doin et al., 2001). We used the whole SAR Sentinel-1 archive, between 2014 and 2018, with an acquisition every 6 days, on an ascending track. The processing was adapted to fit the specific conditions of the Alps (seasonal snow cover, strong local relief, vegetation and strong atmospheric heterogeneities). In particular we implemented a correction using the ERA 5 weather model and we used snow masks in winter allowing to select long temporal baseline interferograms with as little snow as possible. As we specifically aim to study deformation patterns at the scale of valley flanks, an average high-pass filter on moving subwindows has been applied to the interferograms prior to the implementation of time-serie inversions. This step strongly reduced the impact of residual atmospheric delays.
The resulting velocity map in the line of sight (LOS) of the satellite reveals ubiquitous gravitational deformation patterns over the whole Western Alps, with localized patches of moving slopes showing sharp discontinuities with stable surrounding areas. We used radar geometry and InSAR measurement quality factors as indicators to identify the most trusted areas and to extract an inventory of potential DSGSD with their spatial extent. Doing so, we identified more than two thousands slowly deforming areas characterized by LOS velocities from 4 to 20 mm/year. We then compared the geometries of our “InSAR-detected-deforming-slopes” with previously published DSGSD inventories. Good agreements were found for example in the Aosta valley where most of the deforming areas from our velocity map are falling into the DSGSD outlines of Crosta et al. (2013). Currently, we continue to investigate the potential of this large-scale velocity map for DSGSD understanding and we plan to use artificial intelligence to search for possible generic properties between the detected sites.
How to cite: André, P., Doin, M.-P., Mathey, M., Zerathe, S., Vassallo, R., and Baize, S.: Four years of InSAR time series analysis reveals an unprecedent inventory of active DSGSD in the Western Alps, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12693, https://doi.org/10.5194/egusphere-egu21-12693, 2021.
In this work, the A-DInSAR techniques are applied in a mountainous area located in the Central South of Asturias (N Spain), where there are significant landslide and subsidence phenomena. The main aim of this study is detecting and analysing ground deformations associated to slope instabilities and subsidence processes. For this, 113 SAR images, provided by Sentinel-1A/B between January 2018 and February 2020, were acquired and processed by means of PSIG software (developed by the Geomatics Division of the CTTC). The results show a velocity range between -18.4 and 10.0 mm/year, and minimum and maximum accumulated ground displacements of -35.0 and 17.5 mm. This study has made possible to differentiate local sectors with recent deformation related to landslide incidence, urban/mining subsidence, and land recuperation due to aquifer recharge. This work corroborates the reliability and usefulness of the A-DInSAR processing as a powerful tool in the study and analysis of geological hazards on regional and local scales using Sentinel-1 data collection, showing also the high difficulty of processing mountainous areas with few urban sectors.
How to cite: Cuervas-Mons, J., Domínguez-Cuesta, M. J., Mateos-Redondo, F., Monserrat, O., and Barra, A.: Ground motion detection in Central South Asturias (N Spain) by using Sentinel-1 SAR data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-28, https://doi.org/10.5194/egusphere-egu21-28, 2021.
SAR Interferometry (InSAR) has been proven to be effective for measuring landslides deformation. However, the accuracy of InSAR application of landslide mapping and monitoring is limited by the complex atmospheric distortion in alpine valley areas. The sparse external atmospheric data cannot accurately reflect the complex heterogeneous atmosphere in alpine valley areas. The conventional atmospheric delay corrections based on InSAR phase are weakened by the presence of confounding signals (e.g., tropospheric delays, deformation signals, and topographic errors) and spatial heterogeneity of the troposphere.
In this study, we propose the multi-temporal moving-window linear model to estimate the stratified tropospheric delay. The linear relationship between the multi-temporal interferometric phases and the local terrain is estimated using moving windows and then we retrieve the vertical stratified atmospheric phase over the whole scene. Taking into account the deformation information and phase unwrapping errors, the model is solved by an iterative robust estimation algorithm weighted by both deformation rates and residual unwrapping phases.
We first compared our model with four other InSAR atmospheric delay correction methods: traditional empirical linear model, REA5 numerical atmospheric model, GACOS, and temporal/spatial filtering method. The results demonstrated that our proposed model has the best performance on atmospheric delay correction over the reservoir of the Lianghekou hydropower station using Sentinel-1 datasets. Meanwhile, our model was less affected by randomly turbulent phase and phase unwrapping errors, which significantly improves the accuracy of landslide deformation detection and monitoring.
Then, we integrated the multi-temporal moving window atmospheric delay correction model into the STAMPS-SBAS program. The high-precision wide-area time series deformation over the reservoir area can be obtained through iterating phase unwrapping and atmospheric delay correction. In particular, the phase unwrapping errors were gradually corrected during the iteration process. The improvement of the proposed model on the landslide investigations was validated through using UAV images and field surveys. Some landslides that have not been identified in the traditional time-series InSAR results can be identified after atmospheric delay correction by the proposed model.
How to cite: Wang, Y., Dong, J., Zhang, L., Liao, M., and Gong, J.: Refined InSAR landslides deformation monitoring with tropospheric delay correction using multi-temporal moving-window linear model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5493, https://doi.org/10.5194/egusphere-egu21-5493, 2021.
Landslides and floods are the two most important geohazards in Sweden. Due to the climate change effects, it is believed that the risk of occurring these geohazards will increase in Sweden causing for example the land to become more prone to landslides. Additionally, due to the isostatic uplift caused by the retreating of the ice sheet, approximately 10,000 years ago, marine sediments involving marine clays have become exposed above sea level in Scandinavia. Infiltration of fresh water has (and is) leached the salt from the pores within the marine clays leading to the formation a special kind of clay known as the quick clay in the northern countries. These glacial clays and postglacial silts cause more ground surface instability and become slops more prone to trigger landslides, which is the case for concentration of the most landslides in the southwest of Sweden. Hence, quick-clay landslides are common geohazards in Nordic countries, which potentially could cause a considerable economical and live cost. The most recent Gjerdurm landslide in Norway was of this kind quick-clay related.
In recent years, an area close to the Göta River of southeast of Sweden has been the subject of numerous surface and airborne geophysical surveys for detailed subsurface mapping and delineation of the quick-clay and sediments hosting them including the very undulating the crystalline bedrock. These existing studies including access to borehole observations and geotechnical studies motivated us to study also long-term surface deformation in order to study climate effects, erosion, precipitation and underlying quick-clay presence in this area and neighboring regions. We employed radar data with Syntenic Aperture Radar (SAR) interferometry techniques. To this end, Sentinel-1 data from 2015 to 2019 were processed with the Small BAsline Subset (SBAS) technique to estimate time-series displacements and to generate deformation map for that region. The initial results show that the heterogenous deformation observed in the study area with maximum subsidence rate of -22 mm/yr. The deforming areas appear to be located on regions with the thickest column of the clay near the river where we anticipate also thicker quick-clay layers present. The quick-clays in this region overlie a thick (ca. 20 m) coarse-grained layer interpreted from the surface geophysical measurements to be associated with the formation and triggering of quick-clays in the area. With such a large surface deformation and the underling geology, we observe two phenomena in the study. A possible sudden risk of quick-clay landslide but also a long-term creeping of clays and destabilizing effect that may accelerate erosion at the river bank causing more landslides in the future. The cause of the large deformation is still unclear and will be investigated together with hydrogeological and geophysical data available in the study. This study however provides compelling evidence of major surface deformation that should be considered for long-term risk mitigation and planning.
How to cite: Malehmir, A., Darvishi, M., and Nilfouroushan, F.: Integration of InSAR and ground-based geophysical measurements to study an area prone to quick-clay landslide in Sweden, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15677, https://doi.org/10.5194/egusphere-egu21-15677, 2021.
Monitoring ground surface motion is a key information to locate active landslides and possibly detect failure onsets but also to better understand their mechanical behavior in relation with environmental forcing. In-situ and remote technologies are available to provide measures of the ground displacement with different advantages and limitations (in terms of spatial coverage, sampling frequency, etc.). Image matching techniques have been commonly used to detect and measure landslide acceleration but this is often limited to a small amount of images. In the recent years, the number of optical satellite constellations have significantly increased providing global coverage with a frequent revisit time at medium to high spatial resolution and an open access policy (e.g. Sentinel 2, Landsat 7/8). These datasets present new perspectives for the monitoring of slow (cm/day) to moderate (m/month) landslide motion and poses challenges to discriminate between the different spatio-temporal sources (e.g. rainfall correlated signal, noise, seasonal signal, etc.) present in the time -series.
We investigate the use of spatiotemporal ICA/PCA decomposition on optical displacement stacks of landslide areas. The main goal aims at testing 1) the capability of ICA/PCA analysis to detect relevant deformation deformation sources in the case of landslide monitoring and 2) the possibility to improve the time-series inversion of landslide motion by removing spatiotemporal sources that can result from seasonal sun exposition or geometric inaccuracies. We use the MPIC-OPT-Slide service of the GeoHazards Exploitation Platform (GEP) to compute several correlograms and displacement fields (>500 per site) from Sentinel-2 acquisitions on the slow-moving La Valette landslide (Alpes-de-Haute-Provence, France) and the moderately-moving Aiguilles-Pas de l’Ours landslide (Hautes-Alpes, France). We show that in case of steady-state deformation, the noise can be significantly removed around the active parts of the slope. In the case of more complex deformation evolution, pertinent sources can be manually isolated but the choice of the number of sources and their automatic selection remain challenging.
How to cite: Provost, F. and Malet, J.-P.: Spatiotemporal ICA/PCA decomposition of optical displacement field stacks: perspective for landslide time series inversion, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15756, https://doi.org/10.5194/egusphere-egu21-15756, 2021.
Slow-moving landslides exhibit persistent but non-uniform motion at low rates which makes them exceptional natural laboratories to study the mechanisms that control the dynamics of unstable hillslopes. Here we leverage 4.5+ years of satellite-based radar and optical remote sensing data to quantify the kinematics of a slow-moving landslide in the tropical rural environment of the Kivu Rift, with unprecedented high spatial and temporal resolution. We measure landslide motion using sub-pixel image correlation methods and invert these data into dense time series that capture weekly to multi-year changes in landslide kinematics. We cross-validate and compare our satellite-based results with very-high-resolution Unoccupied Aircraft System topographic datasets, and explore how rainfall, simulated pore-water pressure, and nearby earthquakes control the overall landslide behaviour. The landslide exhibited seasonal and multi-year velocity variations that varied across the landslide kinematic units. While rainfall-induced changes in pore-water pressure exerts a primary control on the landslide motion, these alone cannot explain the observed variability in landslide behaviour. We suggest instead that the observed landslide kinematics result from internal landslide dynamics, such as extension, compression, material redistribution, and interactions within and between kinematic units. Our study provides, a rare, detailed overview of the deformation pattern of a landslide located in a tropical environment. In addition, our work highlights the viability of sub-pixel image correlation with long time series of radar-amplitude satellite data to quantify surface deformation in tropical environments where optical data is limited by persistent cloud cover and emphasize the importance of exploiting synergies between multiple types of data to capture the complex kinematic pattern of landslides.
How to cite: Dille, A., Kervyn, F., Handwerger, A., d’Oreye, N., Derauw, D., Mugaruka Bibentyo, T., Samsonov, S., Malet, J.-P., Kervyn, M., and Dewitte, O.: When image correlation is needed: combining very dense radar-amplitude and optical times series for unravelling the complex dynamics of a not so slow slow-moving landslide in the tropics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10627, https://doi.org/10.5194/egusphere-egu21-10627, 2021.
The analysis of surface displacement and velocity fields from time series of terrestrial optical images is a useful tool for monitoring gravitational instabilities. It allows to define the state of instability of the slope, its evolution in time, its spatial coverage and to identify if the movement is progressing. Other types of information can also be extracted from landslide surface velocity fields such as the tangential and normal deformation or the strain fields that highlight areas of compression/extension (Travelletti et al., 2014) that can even allow to assess the mechanical properties of the moving mass (Baum et al., 1998). However, applying such advanced approaches necessitates to be able to compute the 3D displacements and deconvolute the normal and tangential displacements.
Landslide ground motion can be measured by various geodetic techniques either in-situ and point-based, or remote and giving access to spatially distributed information. In this study, we privileged a low-cost remote sensing method based on the use of a Single Lens Reflex (SLR) cameras. We acquired data at high frequency (i.e., time-lapse photography) from two fixed cameras at the Montgombert landslide.
The velocity fields were extracted from a time series of 13 images by applying the TSM (Tracing Surface Motion; Desrues et al. 2019) code. To detect tangential and normal displacements, we developed a methodology to construct the 3D displacements directly from the correlation results from the pairwise combination of the two monoscopic velocity fields, and further conducted a deformation analysis.
To estimate the thickness of the moving mass from the 3D displacements derived from the stereoscopic optical images, we propose a methodology based on the law of mass conservation (i.e., displacement incompressible) by invoking the rheology of the material involved (Booth et al., 2013). In order to take into account, in this model, a more complex slip geometry, we introduced a disbonding parameter that marks the presence of a dislocation area at the top limit of the moving mass which traduces a non-zero velocity at the sliding surface.
We present the methodology of reconstruction of the 3D displacements with a stereoscopic approach and of estimation of the landslide thickness by applying them to the Montgombert use case (Savoie, French Alps). The calculated displacement fields are consistent with in-situ data and the estimated depths, suggesting a shallow sliding, are consistent with geotechnical information.
How to cite: Desrues, M., Toussaint, R., and Malet, J.-P.: Image stereoscopic models for the advanced analysis of landslide deformation and thickness, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14194, https://doi.org/10.5194/egusphere-egu21-14194, 2021.
In March of 2015 there was probably the most studied rain event that ever occurred in the Atacama Desert. Three days of heavy rain impacted the southern region, with peak amounts of 85 mm locally. Different approaches have been used to study this event, including field observations, isotopic analysis and examination of InSAR data. During February of 2019 there was another rain event in the northern Atacama Desert, during which over 160 mm of rain fell on the eastern part of the Atacama, and the influence on the surface is still unknown. This study examines both events. The two study areas have different relationships to the rain: the 2015 event is analyzed within the area in which it rained, whereas the 2019 study area is 60 km away from the heavy rain, connected by surface water drainage. Results of particular interest are the variable responses of the different types of surface materials (e.g., varying classes of terrain roughness and mineralogy) and the identification of locations of erosion and deposition.
We examine multispectral satellite imagery from the Landsat 8 satellite, an approach that has some advantages over other methods. Advantages include its free access, a longer historical record that may allow examination of more events, and the existence of observations at multiple wavelengths which allows evaluation of mineral phase changes due to the rain, vegetation increment and changes in the type of material.
In this work we apply Change Vector Analysis (CVA) (Bruzzone and Fernandez, 2000) to Landsat 8 OLI images to, first, validate the multispectral satellite CVA results using as ground truth the InSAR permanent coherence loss from the 2015 event. Then we apply the method to identify changes due to the 2019 rain event. We compared these results to our field observations.
Our results indicate that: 1) CVA applied to Landsat bracketing the 2015 rain event identifies the depositional and erosional areas, correlating well to permanent changes detected by InSAR coherence loss. 2) Surface materials react variably, and some categories of materials changed more due to a rain than others. 3) Spectral analysis and CVA do not detect mineralogic phase responses documented by surface data. 4) Wind driven changes were also detected in some areas. 5) Field observations reveal that erosion and deposition are always well identified by the algorithm as long as the extent of change is larger than the pixel size. 6) The distribution of changes is dependent on surface slope.
Lorenzo Bruzzone and Diego Fernández Prieto. Automatic Analysis of the Difference Image for Unsupervised Change Detection. Technical Report 3, 2000. DOI: 10.1109/36.843009
How to cite: Olivares, L., Jordan, T., Philpot, W., and Lohman, R.: Two extreme rain events over the Atacama Desert and their consequences on the surface: Insights from Change Vector Analysis applied to Landsat 8 OLI imagery, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12996, https://doi.org/10.5194/egusphere-egu21-12996, 2021.
Shallow landslide mapping is an important procedure for landslide assessment and is the first step to susceptibility, vulnerability, and risk analysis. Knowing the exact location of occurrence of this kind of natural hazard makes it possible to trace spatio-temporal patters and evaluate topographic influences. Landslides are very frequent along the Brazilian south and southeastern coast, where mass movements are triggered by heavy rainfall almost every year in the summer season (Dec-Mar), causing harm to society, such as the destruction of buildings, other infrastructure, and economic and human losses. Landslide recognition and mapping are poorly developed in Brazil, since no mapping guidelines exist, as well as due to low investments in mass movement prevention and mitigation actions. Thus, this research aimed to evaluate the use of freely accessible Google Earth Pro images for shallow landslides recognition and mapping. The study area is located in Itaóca and Apiaí counties, São Paulo state, in Ribeira Valley region, Brazil. Itaóca and Apiaí were affected by mass movements in January 2014, resulting in several economic and infrastructure damages, and 25 fatalities. The most recent post-event images available in Google Earth Pro were used, dated as of 08/10/2014. The visual criteria for landslide scars recognition and mapping were the absence of vegetation, shape and size, drainage network distance, slope position, planar rupture surface, and altimetric variation. As a reference for manual mapping contour and hydrography curves of 1:10.000 scale from the Geographic and Cartographic Institute of the State of São Paulo (for areas belonging to the municipality of Itaóca) and contour and hydrography curves of 1: 50.000 scale from the Brazilian Institute of Geography and Statistics (for the sectors belonging to the municipality of Apiaí) were used. The results showed that Google Earth Pro images are suitable for landslide recognition and mapping in a tropical environment. A total of 1,850 shallow landslides scars from the 2014 event with different sizes were mapped, where the smallest has 14 m² and the largest 9,539 m². They occurred under different morphological and lithological conditions, where most landslides are concentrated at slopes between 20 and 30°, south and southeast orientation, elevations of 600 to 800 m, concave curvatures, and in Quartz-Monzonite and Biotite Monzogranite rocks. The advantage of Google Earth images is that they are very high resolution data and free to access and use for everybody. However, the periods available on the software are limited. The event occurred in January of 2014 but it was only possible to access study area images of October of 2014, nine months after the event. In this way, it is important to verify if the mapping process is influenced by environmental changes, for example, vegetation recovery, that may cause interference for the visual interpretation. The inventory can be used as a basis for further analysis, such as for creating susceptibility and hotspot maps. Such products help to better understand shallow landslide dynamics in the study area, allowing comparison with other environments, and can support spatial planning and decision making of government authorities.
How to cite: Dias, H. C., Hölbling, D., and Grohmann, C. H.: Shallow landslide mapping using freely accessible images: a case study in the Ribeira Valley, Brazil, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-65, https://doi.org/10.5194/egusphere-egu21-65, 2021.
Among the several adopted methods for the kinematic analysis of the possible modes of failure that could affect a rock slope, the Markland test is the most used. Whereas, it has the advantage of being simple and fast, it has some limits, as the impossibility to manually consider the several different slope orientations and their interaction with the discontinuity dimensions and positions.
Recently, the improvements in the Remote Piloted Aerial System (RPAS) digital photogrammetry techniques for the development and mapping of Digital Outcrop Models (DOMs) have given the possibility of developing new automatized digital approaches. In this study, ROKA (ROck slope Kinematic Analysis) algorithm is presented. It is an open-source algorithm, written in MATLAB language, which aims to perform the kinematic analysis of the stability of a rock slope using the discontinuity measurements collected onto 3D DOMs. Its main advantage is the possibility to identify the possible critical combination between the 3D georeferenced discontinuities and the local surface of the slope. In particular, the critical combinations that can activate the planar sliding, flexural toppling, wedge sliding and direct toppling modes of failures can be detected and highlighted directly on the DOM. Hence, the ROKA algorithm can make the traditional approach for the kinematic analysis of a rock slope more effective, allowing not only to simplify the analysis, but also to increase its detail. This can be very important, in particular, for the analysis of large and complex rock slopes.
How to cite: Menegoni, N., Giordan, D., and Perotti, C.: An algorithm for the 3D ROck Slope Kinematic Analysis (ROKA) based on RPAS digital photogrammetry data., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12323, https://doi.org/10.5194/egusphere-egu21-12323, 2021.
Analysis of the stability conditions of rock masses starts from detailed geo-structural surveys based on a systematic and quantitative description of the systems of discontinuities. Traditionally, these surveys are performed by implementing the classical geomechanical systems, available in the scientific literature since several decades, through the use of simple tools such as the geological compass to measure dip and dip direction directly on the discontinuity systems, and to fully describe their more significant physical characteristics (length, spacing, roughness, persistence, aperture, filling, termination, etc.). In several cases, this can be difficult because the discontinuities, or even the rock face, cannot be easily accessible. To have a complete survey, very often the involvement of geologists climbers is required, but in many situations this work is not easy to carry out, and in any case it does not cover the whole rock front.
Today, to solve these problems, traditional geomechanical surveying is implemented by innovative remote techniques using, individually or in combination, instruments such as terrestrial laser scanners and unmanned aerial vehicles to build a point cloud.
This latter permits to extract very accurate data on discontinuities for stability analyses, based on areal and non-point observations. In addition, the point cloud allows to map sub-vertical walls in their entirety in much shorter times than traditional surveying.
At this regard, two rock slopes were detected in the Sorrento Peninsula (Campania, southern Italy) with techniques that include traditional mapping, dictated by the guidelines of the International Society for Rock Mechanics, and the remote survey, through laser scanning and drone photogrammetry. The data obtained were processed automatically and manually through the Dips, CloudCompare and Discontinuity Set Extractor softwares.
In the present contribution we highlight the limits and advantages of the main data collection and the processing techniques, and provide an evaluation of the software packages currently available for the analysis and evaluation of discontinuities, in order to obtain a better characterization of the rock mass.
How to cite: Caccia, A., Palma, B., and Parise, M.: Comparing traditional geomechanical and remote sensing techniques for rock mass characterization , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10147, https://doi.org/10.5194/egusphere-egu21-10147, 2021.
The use of high resolution 3D point clouds and digital terrain models (DTM) from laserscanning or photogrammetry becomes more and more state of the art in landslide studies. Based on a multi-temporal terrestrial laserscanning (TLS) dataset of the deep-seated compound rockslide Laatsch, South Tyrol, we present a multi-method approach to characterize processes such as sliding, falling, toppling, and flows. Sliding is the predominant process of the Laatsch rockslide, accompanied by secondary processes such as rockfall, debris flows and erosion. The presented methods are applicable to all kind of 3D point clouds and not limited to TLS data. For remote sensing-based landslide analyses a distinction between two classes of surface processes is necessary: i) processes where the original surface is destroyed and no correlations between the shape and texture of the pre- and post-failure surfaces can be found (falls, rapid flows, rapid slides) and ii) processes where the surface is displaced without major surface changes (slow slides, slow flows and toppling). For processes where the original surface is destroyed, the distance between the pre- and post-failure terrain surface is measured with the aim to delineate the scarp and depositional area, and to quantify the failure volume as well as the scarp thickness. With DTMs of differences (DoD), the distance is measured along the plumb line. DoDs can be used to quickly and reliably assess the volume and extent of fall processes on flat to moderate slopes. For steep or even overhanging terrain, a 3D distance measurement approach must be used, where the distance is measured along the local surface normal. After 3D distance measurement, the volume of steep scarp areas can be calculated by first rotating, the point cloud into the horizontal plane (by making use of the average surface normal) and by interpolating the rotated 3D distance measurement values into a grid. Summing up the distances and multiplying with the cell area of the grid yields the scrap rupture volume. Remote sensing-based analyses of sliding and toppling processes are more complex compared to fall processes because the displaced surface patch must be detected in both surveys. Displacement analyses based on image correlation of ambient occlusion shaded relief images, together with DTMs of both epochs, are used to analyse the displacement of the entire rockslide area. The result is a map with displacement vectors. Disadvantages of image correlation are the coarse spatial resolution and the inability, as it is a 2.5D approach, to deal with steep slope parts. To analyse the displacement and toppling of steep rock walls a combination of the 3D distance measurement approach and an iterative closest point (ICP) based approach is applied. The 3D distance measurement values are clustered and used for a segmentation of the point cloud. In a next step, the ICP is applied on each of the resulting segments. This approach can deal with 3D displacements. The results are still sensitive towards the geometric contrast within the segments and not fully automated yet.
How to cite: Fey, C., Voit, K., Wichmann, V., Zangerl, C., and Mair, V.: Multi-method approach for high resolution 3D data based process analyses of compound rock slides, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1385, https://doi.org/10.5194/egusphere-egu21-1385, 2021.
Rapid mapping of landslides plays an important role in both science and emergency management communities. It helps people to take the appropriate decisions in quasi-real-time and to diminish losses. With the increasing advancement in high-resolution satellite and aerial imagery, this task also increased the spatial accuracy, providing more and more accurate maps of landslide locations. In accordance with the latest developments in the fields of unmanned aerial vehicles and artificial intelligence, the current study is focused on providing an insight into the process of mapping landslides from full-motion videos and by means of artificial intelligence. To achieve this goal, several drone flights were performed over areas located in the Romanian Subcarpathians, using Quadro-Copters (DJI Phantom 4 and DJI Mavic 2 Enterprise) equipped with a 12 MP RGB camera. The flights were planned and executed to reach an optimal number of pictures and videos, taken from various angles and heights over the study areas. Using Structure from Motion techniques, each dataset was processed and orthorectified. Similarly, each video was processed and transformed into a full-motion video, having coordinates allocated to each frame. Samples of specific landslide features were collected by hand, using the pictures and the video frames, and used to create a complete database necessary to train a Mask RCNN model. The samples were divided into two different datasets, having 80% of them used for the training process and the rest of 20% for the validation process. The model was trained over 50 epochs and it reached an accuracy of approximately 86% on the training dataset and about 82% on the validation dataset. The study is part of an ongoing project, SlideMap 416PED, financed by UEFISCDI, Romania. More details about the project can be found at https://slidemap.geo-spatial.ro.
How to cite: Sandric, I. C., Ilinca, V., Irimia, R., Chitu, Z., Jurchescu, M., and Plesoianu, A.: Mapping landslides using drone's full-motion videos, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11179, https://doi.org/10.5194/egusphere-egu21-11179, 2021.
Mass movements in peatlands are poorly understood. This is because of the unusual geotechnical properties of the materials (organic soils) and a paucity of well-constrained case studies. At the end of June 2020, a large peat slide occurred on Shass mountain, several kilometres northeast of the village of Drumkeeran in Co. Leitrim, north-western Ireland. The source area of the peat slide is an area of blanket bog within a Special Area of Conservation (SAC). This area is characterised by a topographic slope of 3-5°. On recently published Landslide Susceptibility Maps it was classified as ‘moderately low’ to ‘low’.
To understand this peat slide’s genesis and impact on the landscape, post-slide site investigations and aerial surveys were undertaken in the following days and weeks. These included: photogrammetry and LiDAR surveys via UAVs and crewed aircraft; Ground Penetrating Radar (GPR) profiling; in-situ peat depth measurements, soil coring and a vegetation survey. These data were complemented by pre-and post-slide radar satellite data (Sentinel-1) and were compared to high-resolution pre-slide aerial imagery and digital surface models (DSMs) captured in August 2017 and April 2020.
Mapping and DSM differencing show a source area of 7 ha, from which ~ 171,000 m3 of peat flowed 6.6 km down a river channel. The height/run-out ratio was 0.035; the run-out/volume ratio was 0.038. Peak flow or run-up heights near the source area were >4 m. Video, field and satellite evidence indicates that the peat was highly liquified. It deposited in three zones: upstream of a small bridge, which acted as a partial dam and on two floodplain areas. About 45 ha were covered with peat up to 1-3 m thick, these deposits generally thin downstream. Radar intensity data support local accounts that most of this material failed retrogressively and redeposited within 24 hours.
Data from the nearest meteorological station, 27 km to the west, show that the region experienced a relatively dry period (118 mm of precipitation) in the 2.5 months before the landslide, and a period of exceptionally high rainfall (53 mm) three days immediately beforehand. Flow pathway analysis indicates a natural drainage convergence in the upper catchment. The landslide possibly started here and regressed upslope into ~5 ha of well-drained bog, afforested in 1996, located at the head of the catchment. The areas to the south and east comprise of a mosaic flushes, wet heath, and blanket bog vegetation.
The peat depth was assessed by both GPR data (calibrated by coring), which shows the base of the peat and probing. It ranged from 2-5 m. This accords with a typical 2-4 m thickness of failed peat from DSM differencing. Coring also revealed a ~50cm thick layer clay at the base of the peat. These preliminary results highlight the potential importance of local drainage patterns and localised clay layers in increasing peat-slide susceptibility on low-angle slopes. This characterization underpins further investigation into the multifarious factors causing peat slides, which may be exacerbated by climate change.
How to cite: Connolly, J., Holohan, E., Bourke, M., Cruz, C., Farrell, C., Foyle, F., Habib, W., Halpin, R., Henry, T., Hrysiewicz, A., Long, M., Johnson, P., McKeon, C., and Trafford, A.: Characterisation of the 2020 Drumkeeran peat landslide: a large peat slide in Ireland. , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13007, https://doi.org/10.5194/egusphere-egu21-13007, 2021.
The area of the present day Muzalkow Arch Geopark located on the border of Poland and Germany was subjected to a long term mining of lignite and other rock raw materials that ceased in the 70’ties of the 20th Century. The present-day geomorphological landscape of the research area is characterised by numerous and differentiated forms of anthropogenic origin (e.g. artificial lakes, subsidence troughs, sink holes, waste heaps) associated with underground and subsequently opencast mining of lignite in complex geological and tectonic conditions that result from glaciotectonic processes of subsequent stages of accumulation and weathering. It is thought that the area is presently subjected to geodynamic processes associated with weathering of exposed areas (lignite outcrops and waste heaps), destruction of shallow underground workings (subsidence troughs, sink holes) and changing hydrogeological conditions of the rock mass. The scale of these secondary deformations is presently unknown and these processes pose a threat the present day tourist development of the area, such as: sudden development of discontinuous terrain deformations, slope instability, flooding and subsequent dying of vegetation, etc.
Geodetic surveying and remote sensing (terrestrial, aerial and satellite) observations have been employed, apart from other in-situ investigations (geophysical and geological prospecting), to study the processes in one of the former coal mining fields in the geopark.
In this study preliminary results of selected geodetic field investigations, i.e. terrestrial laser scanning of a sink hole that showed on the surface in Autumn 2019 and UAV photogrammetric monitoring of an artificial waste rock tips have been reported. It has been found, based on mapping of old mining maps in GIS, that the sink hole is directly related to old shallow underground workings. Maximum depth of the analysed sink hole below ground level is 5.5 m and volume of subsidence is 35 m3. The location is being monitored to check if the geometry changes in time.
Whereas, comparison of digital elevation models of the investigated waste heap (one of three measured so far) showed development of gully erosion and downward movement of the weathered material. The deposition of material at the bottom of the heap averaged over a dozen cm and maximum of over 50 cm for a half year Summer period (from 15.05.2020 to 07.11.2020).
The presented results constitute a first approximation of 3D mapping and modelling the post-mining deformations in glaciotectonic landscape and constitute part of an ongoing research project financed from the Polish National Science Centre OPUS funds (no 2019/33/B/ST10/02975).
How to cite: Blachowski, J., Becker, M., Buczyńska, A., Bugajska, N., Janicki, D., Koźma, J., Kwaśny, L., Wajs, J., and Warchala, E.: Remote Sensing based investigation of secondary mining deformation processes in a postglacial landscape of the Muzakow Arch Geopark (Western Poland) – preliminary results, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2458, https://doi.org/10.5194/egusphere-egu21-2458, 2021.
Monitoring landslides is essential to understand their dynamics and to reduce the risk of human losses by raising warnings before a failure. A decade ago, a decrease of apparent seismic velocity was detected several days before the failure of a clayey landslide, that was monitored with the ambient noise correlation method. It revealed its potential to detect precursor signals before a landslide failure, which could improve early warning systems. To date, nine landslides have been monitored with this method, and its ability to reveal precursors before failure seems confirmed on clayey landslides. However three challenges remain for operational early-warning applications: to detect velocity changes both rapidly and with confidence, to account for seasonal and daily environmental influences, and to check for potential instabilities in measurements. The ability to detect a precursory velocity change requires to adapt the processing workflow to each landslide: the key factors are the filtering frequency, the correlation time window, and the choice of temporal resolution. The velocity also fluctuates seasonally, by 1 to 6% on the reviewed landslide studies, due to environmental influences, with a linear trend between the amplitude of seasonal fluctuations and the filtering frequency over the 0.1–20 Hz range, encompassing both landslide and non-landslide studies. The environmental velocity fluctuations are caused mostly by groundwater levels and soil freezing/thawing, but could also be affected by snow height, air temperature and tide depending on the site. Daily fluctuations should also occur on landslides, and can be an issue when seeking to obtain a sub-daily resolution useful for early-warning systems. Finally, spurious fluctuations of apparent velocity—unrelated to the material dynamics—should be verified for. They can be caused by changes in noise sources (location or spectral content), in site response (change of scatterers, attenuation, or resonance frequency due to geometrical factors), or in inter-sensor distance. As a perspective, the observation of seismic velocity changes could contribute in assessing a landslide stability across time, both during the different creeping stages occurring before a potential failure, and during its reconsolidation after a failure.
Main references :
- Le Breton M., Bontemps N., Guillemont A., Baillet L., Larose E., 2021. Landslide Monitoring Using Seismic Ambient Noise Correlation: Challenges and Applications, Earth Science Reviews, In press
- Larose, E., Carrière, S., Voisin, C., Bottelin, P., Baillet, L., Guéguen, P., Walter, F., Jongmans, D., Guillier, B., Garambois, S., Gimbert, F., Massey, C., 2015. Environmental seismology: What can we learn on earth surface processes with ambient noise? Journal of Applied Geophysics 116, 62–74. https://doi.org/10.1016/j.jappgeo.2015.02.001
- Mainsant, G., Larose, E., Brönnimann, C., Jongmans, D., Michoud, C., Jaboyedoff, M., 2012. Ambient seismic noise monitoring of a clay landslide: Toward failure prediction. J. Geophys. Res. 117, F01030. https://doi.org/10.1029/2011JF002159
How to cite: Larose, E., Le Breton, M., Bontemps, N., Guillemont, A., and Baillet, L.: Updates on ambient noise correlation for landslide monitoring, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16532, https://doi.org/10.5194/egusphere-egu21-16532, 2021.
Seismic sensors installed in areas prone to rockfalls provide a continuous record of the phenomenon, allowing real-time detection and characterization. Detection of small scale rockfalls (< 0.001 m3), that might be precursors of larger events, can be worthwhile for early warning systems of rockfalls. However, seismic signals are closely dependent on the characteristics of the event and on the geotechnical characteristics of the ground, making the detection of small rockfalls complex and requiring detailed in-situ analyzes. For this reason, an experiment was carried out on the UB experimental site (Puigcercós Cliff, Catalonia, NE Spain) on 6th-7th of June 2013, where 21 rocks with volumes ranging from 0.0015 m3 to 0.0004 m3 were thrown from the top of the cliff (200 m long and 27 m high) and the seismic signals were registered with three 3D short period seismic sensors located at different distances from the rock wall: 57 m, 67 m, and 107 m.
The recorded seismic signals have a frequency content between 10-30 Hz, and the duration of the peak amplitudes varied between 0.3 and 0.6 s. Based on these characteristics, different phases of the dynamics of the rockfalls were identified, including main impacts, rebounds, flights, rolling and final stop of the events. The furthest station recorded the lowest frequency and amplitude values, limiting our ability to detect those blocks smaller than 0.0015 m3. Comparing the results with the nearest station, seismic attenuation phenomena is detectable even at distances of 50 m.
After the experiment, a permanent seismic station was installed in the area, at 107 m from the cliff. Using LiDAR and 2D imagery monitoring, two naturally triggered rockfalls were identified on 30th and 31st August 2017 (0.28 m3 and 0.25 m3 respectively). Based on the results from the experiment and an automatic detection system, these main events and prior minor events have been found in the continuous seismic records of this permanent station. The characteristics of these natural detachments differ partially from the artificially triggered rockfalls during the experiment, since the geometry of the seismic signals is different. The observed shapes of the natural detachments are similar to that of granular flows, much more continuous than the sharp shapes that were observed in the isolated blocks of the experiment. This shows the possibility of incorporating seismic stations for the automatic detection and initial characterization of rockfalls and its effectiveness in detecting frequencies of occurrence.
In order to evaluate the possibility of estimating rockfall volumes, diverse energy ratios (Es/Ep) were calculated. However, precise volume estimation is not possible. Nevertheless, the combination of seismic data with LiDAR and photographic techniques allows accurate new volume calculations of rockfalls to be incorporated progressively into the study of rockfalls.
ACKNOWLEDGMENTS: The authors would like to acknowledge the financial support from CHARMA (CGL2013-40828-R) and PROMONTEC (CGL2017-84720-R AEI/FEDER, UE) projects, Spanish MINEICO. We are also thankful to Origens UNESCO Global Geopark.
How to cite: Telletxea, B., Tapia, M., Guinau, M., Royán, M. J., Roig Lafon, P., Blanch, X., Khazaradze, G., Suriñach, E., Furdada, G., Garcia-Sellés, D., Abellán, A., and Vilaplana, J. M.: Identification and characterization of rockfalls using seismic signals, LiDAR, and imagery. Advances on real-time detection, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13149, https://doi.org/10.5194/egusphere-egu21-13149, 2021.
On 12 May 2008, the mountainous area of Longmenshan, which separates the Tibetan Plateau from the Sichuan Basin, was hit by the 8.0 Ms Wenchuan earthquake which triggered about 200,000 landslides, some of which caused river damming with the formation of temporary lakes. Failures of the landslide dams can induce severe flooding downstream, therefore, it is important to study their structure and mechanical properties in order to evaluate their stability conditions.
The present study investigates the landslide dam deposits of a rock avalanche triggered in Yang Jia Gou, in Sichuan Province, using single-station three component recordings of ambient noise, with the aim of obtaining information about thickness and mechanical properties of the deposits from their resonance properties. Three noise measurement campaigns and two ERT surveys were conducted to support data interpretation. The data were analyzed using the traditional Nakamura’s technique, HVNR, and the innovative technique HVIP, both based on the calculation of ratios between horizontal and vertical amplitude of ground motion. Both methods revealed the presence of resonance peaks, a major one at lower frequency, and a minor one at higher frequencies, representative of the deposit layering. HVNR showed a considerable instability in terms of amplitude of H/V, likely because this technique analyzes the entire noise wave field recorded, so to be subject to a large variability related to a variable composition of the noise field. This problem does not affect the HVIP method, which is based on the analysis of the ellipticity of Rayleigh waves, isolated from the recording.
Rayleigh wave ellipticity curves were used as targets in the inversion phase to obtain the velocity profile of the site. The subsoil model was constrained by the data derived from the resistivity profiles. The results revealed: different velocity layers inside the deposit; lateral variations in thickness, in accordance with the higher frequency peak, and in mechanical properties, with an increase of stiffness, probably due to a major portion of rocky blocks; an increase in thickness of the entire deposit, probably because of the irregularities of the substrate.
Further investigations are in progress through other kinds of noise analysis exploiting the synchronization of simultaneous recordings. This can provide additional constraints (to be derived from the dispersion of group velocity of Rayleigh waves) and aid resolving interpretation ambiguities.
How to cite: Capone, P., Del Gaudio, V., Wasowski, J., Hu, W., Venisti, N., and Li, Y.: Integration of ambient noise and ERT data to investigate the structure of the Yang Jia Gou rock avalanche deposits (Sichuan - China), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4578, https://doi.org/10.5194/egusphere-egu21-4578, 2021.
Bedrock geometry, geological discontinuities, geotechnical units and shear surfaces/bands control the deformation patterns and the mechanisms of slope instabilities. Seismic P-wave refraction tomography is useful to detect these features because P-wave velocity significantly decreases in fractured and weathered rocks relative to consolidated ones, and because lateral changes of velocity can highlight alternation of dipping fracture zones and consolidated rocks. Acquiring this information at high spatial resolution is of paramount importance to model landslide behaviour.
The Viella slope instability (Hautes-Pyrénées, France) is a complex and deep-seated (> 80 m) landslide which has reactivated in Spring 2018 as a consequence of both a 100-yr return period flash flood (Bastan torrent) which affects the lower part of the slope, and a major rockslide (> 100.000 m3) modifying the stress conditions in the upper part. The landslide, which covers an area of ca. 650 000 m², is primarily composed of schists with different degrees of weathering, forming several kinematic units with surface velocities in the range [0.5 – 5] mm.month-1. Many buildings and infrastructures (roads, bridge) are progressively damaged (cracks, progressive tilting) and scarps and lobes develop at the surface delineating the kinematic units.
In order to model the evolution of the landslide and design possible mitigation measures (drainage, slope reprofiling), a 3D seismic survey has been carried out in summer 2020. The survey was designed to provide a highly detailed velocity model untill 100 m depth, highlighting possible lithological and mechanical contrasts as well as water preferential flow paths. The acquisition was carried out using 71 3C miniaturized seismic sensors buried at ca. 30 cm in the ground and spaced with an average intertrace of 70 m in accordance with slope topography. IGU16HR-3C 5Hz SmartSolo geophones of the DENSAR service (EOST) were used. The seismic array was recording continuously from June, 22nd to July, 21st 2020 at a sampling rate of 500 Hz. 370 controlled seismic sources were triggered at 122 locations using blank 12-gauge shotgun cartridges, Seismic Impulse Source Systemshots, 90-kg Propelled Energy Generator shots and a Mechatronics Lightning source generating P and S-waves with mono-frequency and sweep signals between 5 and 60 Hz of maximum 80 s length.
We present the results of this active P-wave traveltime tomography. We first discuss the quality of the recorded signals related to each different type of source, given the noise and attenuation conditions at Viella. Because the signals were challenging to detect a methodology based on manual picking was used, supported by automatic detection tools and considerations regarding the network geometry in an a priori velocity model.
The P-wave model was obtained using the inversion library pyGIMLI, which permits an accurate description of the topography, and provides a spatial discretization adapted to the problem. To supplement and constrain the interpretation of the P-wave velocity model, borehole information as well as a 3D resistivity model of the zone are available. With regards to these data, the geometric features and physical parameters of the main geological structures of the landslide are discussed.
How to cite: Lajaunie, M., Broucke, C., Malet, J.-P., Hibert, C., Sénéchal, G., Rousset, D., and Ferhat, G.: Dense 3D seismic traveltime tomography to understand complex deep landslide structures, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9891, https://doi.org/10.5194/egusphere-egu21-9891, 2021.
With this note, we show a three-dimensional reconstruction of the basal surface of a large-scale and deep-seated rock-slide located in Northern Apennines (Northern Italy), obtained by integrating direct observations from boreholes and data from multi-methods geophysics. This type of landslides is so intrinsically complex and extended, that borehole investigations alone are generally insufficient to fully characterize the inner structures. To overcame such limitations, geophysical surveys are employed extensively (Bogoslovsky and Ogilvy 1977; Bruno and Marillier 2000; Bichler et al. 2004; Jongmans and Garambois 2007). In this study, we integrated multi-parameter data derived from 400 m of DC electrical resistivity tomography (ERT), 466 m of P-wave seismic refraction tomography (SRT), 420 meters of P-wave seismic reflection profile (SRF) together with 156 HVSR seismic noise recordings processed with spectral ratio methodology (Nakamura 1989). To constrain the inversion of the HVSR and migrate to the spatial domain the SRF, the P-wave velocity domains from SRT profiles were used after comparison with stratigraphic data. Moreover, the ERT profile fitted the geometrical features depicted by SRF profile. By means of all these data, we managed to map the surface exhibiting the highest acoustic impedance and the most relevant spatial continuity, which, according to the stratigraphic data, is to be ascribed to the basal interface between the fractured flysch rock masses involved in deep-seated sliding and the underlying undamaged bedrock. Comparison with inclinometer data also showed, presently, the active sliding surfaces match the mapped interface only in some locations, whereas in other they are shallower. This indicates that the mapped basal surface can be considered the envelope of the maximum volume involved, in the past, by the mass movement, and that part of such volume is nowadays no longer moving. The integration of multi-geophysical surveys, in this case, proved to be a valuable way to spatialize evidences collected by boreholes, providing the basis for a three-dimensional geological model of the slope that can later on be used for modelling purposes.
Bichler, A., P. Bobrowsky, M. Best, M. Douma, J. Hunter, T. Calvert, and R. Burns. 2004. “Three-Dimensional Mapping of a Landslide Using a Multi-Geophysical Approach: The Quesnel Forks Landslide.” Landslides 1 (1): 29–40. https://doi.org/10.1007/s10346-003-0008-7.
Bogoslovsky, V A, and A A Ogilvy. 1977. “GEOPHYSICAL METHODS FOR THE INVESTIGATION OF LANDSLIDES.” GEOPHYSICS 42 (3): 562–71. https://doi.org/10.1190/1.1440727.
Bruno, F., and F. Marillier. 2000. “Test of High-Resolution Seismic Reflection and Other Geophysical Techniques on the Boup Lanslide in the Swiss Alps.” Surveys in Geophysics 21 (4): 333–48.
Jongmans, Denis, and Stéphane Garambois. 2007. “Geophysical Investigation of Landslides: A Review.” Bulletin de La Societe Geologique de France 178 (2): 101–12. https://doi.org/10.2113/gssgfbull.178.2.101.
Nakamura, Y. 1989. “Method for Dynamic Characteristics of Subsurface Using Microtremor on the Ground Surface.” Proc. 20th JSCE Earthquake Eng. Symposium.
How to cite: Critelli, V., Ronchetti, F., Corsini, A., Berti, M., and Di Paola, G.: Integration of multi-parameter geophysical data to the structural mapping of a landslide’s subsurface, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10592, https://doi.org/10.5194/egusphere-egu21-10592, 2021.
In the world, various natural calamities, like earthquakes and massive rainfalls sometimes combined with windstorms, can trigger multiple landslide events that can occur in groups of hundreds to thousands in a region, over a short time span. Therefore, there is a growing need to be able to intervene quickly to accurately map the impacted areas. To this end, VHR optical images ensure best performances in terms of spatial accuracy but, for rapid mapping, they present limitations due to the possible presence of cloud cover as, often, the first cloudless image is available with an unacceptable time delay, see, e.g., the cases of strong earthquakes of Chile 2017, Nepal 2015 and Ecuador 2016. A possible solution may stand in the combined exploitation of optical and SAR data. In this study, deep-learning convolution neural networks (CNNs) techniques have been used to compare and combine the mapping and classification performances of optical images (from Sentinel-2) and SAR images (from Sentinel-1). The training and test zones used to independently evaluate the performance of CNNs on different datasets are located in the eastern Iburi subprefecture in Hokkaido, where, at 03.08 local time (JST) on September 6, 2018, a Mw 6.6 earthquake triggered about 7837 coseismic landslides. We analyzed the conditions before and after the earthquake exploiting SAR and optical data by means of a series of CNNs implemented in Python that point out the locations where the Landslide class is predicted as more likely. As expected, the CNN run on optical images proved itself excellent for the landslide detection task, achieving an overall accuracy of 98.48% while a CNN based on the combination of ground range detected (GRD) data (SAR) achieved an overall accuracy of 95.54%. Despite this, the integrated use of SAR data allows for a rapid mapping even during storms and under cloud cover and seems to provide a comparable accuracy than optical change detection. We believe that, in the near future, such classification accuracy might even increase with the availability of new, VHR SAR products, such as the 50 cm x 50 cm resolution imagery from the Capella-2 satellite.
How to cite: Nava, L., Catani, F., and Monserrat, O.: Rapid mapping of landslides by Deep-Learning of combined optical and SAR data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13181, https://doi.org/10.5194/egusphere-egu21-13181, 2021.
Landslides are common natural disasters around the globe. Understanding the accurate spatial distribution of landslides is essential for landslide analysis, prediction, and hazard mitigation. So far, many techniques have been used for landslide mapping to establish landslide inventories. However, these techniques either have a low automation level (e.g., visual interpretation-based methods) or a low generalization ability (e.g., pixel-based or object-based approaches); and improvements are required for landslide mapping. Therefore, we have developed an interactive, user-friendly web portal for landslide labeling. The web portal takes multi-temporal satellite images as inputs. A deep learning model will first detect landslide-suspicious areas in the image and present results to users for validation. Users can then review and annotate these machine-labeled landslides through a user-friendly interface. Users’ editions on landslide annotation will further improve the accuracy of the deep learning model. Two landslide-affected regions in Washington were selected to test the capability of our web portal for landslide mapping. The detected landslides were validated by expert labelers. The results indicated that our annotation tool was able to produce landslide maps with high precision, a high rate of annotation, and reduced human efforts.
How to cite: Pei, T., Nagendra, S., Banagere Manjunatha, S., He, G., Kifer, D., Qiu, T., and Shen, C.: Utilizing an interactive AI-empowered web portal for landslide labeling for establishing a landslide database in Washington state, USA, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13974, https://doi.org/10.5194/egusphere-egu21-13974, 2021.
In the Yosemite National Park, it has been shown that large granitic exfoliation sheets can be subject to spectacular daily deformations (with cracks opening and closing with a magnitude of up to 15 mm over 24 hours). These thermal deformations, observed during hot summer days, are known to contribute greatly to rock falls. However, it is questionable whether this kind of deformation only occurs with exfoliation flakes (which have very particular shapes), or if it can be observed on more common rock faces geometries. Moreover, does this phenomenon only occur during hot summer days or also in other seasons?
To answer these questions, cracks and slabs in two sedimentary rock walls were monitored over 24-hour cycles, in summer and winter. The first site is in the massive limestones of the old quarry of St-Triphon (in the Swiss Prealps), the second one in the cliff of la Cornalle (near Lausanne), an intercalation of poorly consolidated sandstone and marls. Air and contact temperature loggers, a pyranometer to measure the incident solar radiation and crackmeters were used in situ. Thermal images were acquired every 20 minutes (surface thermocouples sensors and aluminum reflectors are used to constrain the surface emissivity and the environmental radiative temperature).
First it was shown, that during sunny days, the amplitude of the daily variation of the rock surface temperature is as large in winter than in summer (up to 30°C). As expected, this amplitude is larger in the detached slab than in the massive rock mass. In both sites, the deformation measured in the cracks reach about 0.2 mm. Depending on the slab geometry and its “attachment points” with the main rock mass, an increase of temperature can correspond to a closing or to an opening of the cracks. In conclusions, however these daily deformations are about two orders of magnitude smaller than those measured in the Yosemite big walls, they appear to occur also in “common” rock faces all around the year. On the long term, these deformations will contribute to the rock weakening at sub-surface conditions.
How to cite: Derron, M.-H., Maillard, L., Fei, L., Jaboyedoff, M., and Guérin, A.: Thermal imaging and rock slabs deformation due to daily solar radiation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16549, https://doi.org/10.5194/egusphere-egu21-16549, 2021.
InfraRed Thermography (IRT) spread quickly during the second half of the 20th century in the military, industrial and medical fields. This technique is at present widely used in the building sector to detect structural defects and energy losses. Being a non-destructive diagnostic technique, IRT was also introduced in the Earth Sciences, especially in the volcanology and environmental fields, yet its application for geostructural surveys is of recent development. Indeed, the acquisition of thermal images on rock masses could be an efficient tool for identifying fractures and voids, thus detecting signs of potential failures.
Further tests of thermal cameras on rock masses could help to evaluate the applicability, advantages and limits of the IRT technology for characterizing rock masses in different geological settings.
We present some results of IRT surveys carried out in the coastal area of Polignano a Mare (southern Italy), and their correlation with other remote sensing techniques (i.e. Terrestrial Laser Scanning and Structure from Motion). The case study (Lama Monachile) is represented by a 20 m-high cliff made up of Plio-Pleistocene calcarenites overlying Cretaceous limestones. Conjugate fracture systems, karst features, folds and faults, were detected in the rock mass during field surveys. In addition, dense vegetation and anthropogenic elements, which at places modified the natural setting of the rock mass, represent relevant disturbances for the characterization of the rock mass. In this context, IRT surveys were added to the other techniques, aimed at detecting the major discontinuities and fractured zones, based on potential thermal anomalies.
IRT surveys were carried out in December 2020 on the east side of the rock mass at Lama Monachile site. Thermal images were acquired every 20 minutes for 24 hours by means of a FLIR T-660 thermal imager mounted on a fixed tripod. Ambient air temperature and relative humidity were measured during the acquisition with a pocketsize thermo-hydrometer. A reflective paper was placed at the base of the cliff to measure the reflected apparent temperature. In addition, three thermocouple sensors were fixed to the different lithologic units of the rock face. These parameters, together with the distance between the FLIR T-660 and the rock face, were used in order to calibrate the thermal imager and correct the apparent temperatures recorded by the device, during the post-processing phase. Successively, vertical profiles showing the temperature of the rock face over time were extracted from the thermograms. Thermal anomalies were correlated with stratigraphic and Geological Strength Index profiles, obtained by means of field surveys and Structure from Motion techniques. The presence of fracture and voids in the rock mass was also investigated.
How to cite: Loiotine, L., La Salandra, M., Andriani, G. F., Apicella, E., Jaboyedoff, M., Parise, M., and Derron, M.-H.: Implementation of InfraRed Thermographic surveys in complex coastal areas: the case study of Polignano a Mare (southern Italy), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3264, https://doi.org/10.5194/egusphere-egu21-3264, 2021.
The project “Geo-information Services for Landslides in the Alps (eo4alps-landslide)” has the main objective of exploiting the potential of new satellite data coupled to advanced modelling for gravitational hazards assessment in the Alpine region. The two-year project starts in early 2021 and consists of a broad consortium of universities, geological consultancies, ICT companies and geological services. More than 20 authorities and other stakeholders responsible for landslide disaster risk management are actively involved in all project phases. “eo4alps-landslide” aims at ensuring that satellite-based Earth Observation (EO) products are increasingly and more efficiently used in practice for science and operational DRM procedures. “eo4alps-landslide” produces harmonised and advanced landslide inventories and susceptibility/hazard maps for the Alps based on InSAR and optical ground motion services and landslide-specific models embedded in the Geohazards Exploitation Platform (GEP). These EO-based services and products can be complemented by local datasets and terrain data from the end users directly in GEP. Planned products of “eo4alps-landslide” includes 1) automatic landslide detection using satellite optical and InSAR-based services, 2) harmonised and advanced landslide catalogues resulting from the satellite based detection and local inventories, 3) susceptibility/hazard maps consisting of possible landslide source areas and landslide type-specific runout modelling. Further fields of application and products will be adapted to the needs of end users. The methods will be generic in order to be used at several spatial scales from Tier 1 (region) to Tier 2 (municipality) and Tier 3 (local slope). Furthermore, the products of “eo4alps-landslide” will be compatible with products and services of other “eo4alps” initiatives, as well as with the European Ground Motion Service (EGMS).
How to cite: Malet, J.-P., Michoud, C., Oppikofer, T., Crosta, G. B., Frattini, P., Pacini, F., Garcia Robles, J., and Foumelis, M.: Landslide Geo-Information Services for the Alps, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3358, https://doi.org/10.5194/egusphere-egu21-3358, 2021.
Heavy rainfall can trigger thousands of landslides, which have a significant effect on the landscape and can pose a hazard to people and infrastructure. Inventories of rainfall triggered landslides are used to improve our understanding of the physical mechanisms that cause the event, in assessing the impact of the event and in the development of hazard mitigation strategies. Inventories of rainfall-triggered landslides are most commonly generated using optical or multispectral satellite imagery, but such imagery is often obscured by cloud-cover associated with the rainfall event. Cloud-free optical satellite images may not be available until several weeks following an event. In the case where rain falls over a long period of time, for example during the monsoon season or successive typhoon events, the timing of the triggered landslides is usually poorly constrained. This lack of information on landslide timing limits both hazard mitigation strategies and our ability to model the physical processes behind the triggered landsliding.
Satellite radar has emerged recently as an alternative source of information on landslides. The removal of vegetation and movement of material due to a landslide alters the scattering properties of the Earth’s surface, thus giving landslides a signal in satellite radar imagery. Satellite radar data can be acquired in all weather conditions, and the regular and frequent acquisitions of the Sentinel-1 constellation, could allow landslide timing to be constrained to within a few days. Satellite radar data has been successfully used in detecting the spatial distribution of landslides whose timing is known a-priori (for example those triggered by earthquakes). Here we demonstrate that time series of Sentinel-1 satellite radar images can also be used to achieve the opposite: the identification of landslide timing for an event whose spatial extent is known.
We analyse radar coherence and amplitude times series to identify changes in the time series associated with landslide occurrence. We compare pixels within each landslide with nearby pixels outside each landslide that have been identified to be similar in pre-rainfall Sentinel-1 and Sentinel-2 imagery. We test our methods on rainfall-triggered landslides in Nepal and Japan, both of which are mountainous countries that experience regular heavy rainfall events that are often obscured by cloud cover in optical satellite imagery.
How to cite: Burrows, K., Marc, O., and Remy, D.: Establishing the timings of rainfall-triggered landslides using Sentinel-1 satellite radar data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11028, https://doi.org/10.5194/egusphere-egu21-11028, 2021.
In order to study the effect of the different consolidation pressure, loading-unloading path and gravel content on the shear modulus of the small strain of sliding zone soil, a set of consolidation bender element test device was developed. The device consists of three parts: a consolidation system, a deformation measuring system, and a shear wave testing system. The consolidation system is composed of a traditional consolidation instrument and the plexiglass cylinder box. The sample is cylindrical in shape and has a size of 50 mm×50 mm. The consolidation displacement is measured by a digital display micrometer. Shear wave testing system is a wave velocity measurement system made of piezoelectric ceramic. The experimental results show that the device can control the consolidation pressure and measure the vertical deformation, measure the shear wave velocity of the sliding zone soil in real-time, and then study the variation rule of the small strain shear modulus of the sliding zone soil with gravels. The shear modulus of the sliding zone soil increases with an increase in the consolidation pressure. The shear modulus of the unloading of sliding zone soil is larger than that of loading. Under the loading pressure of 200 kPa and 400 kPa, the shear modulus of the sliding zone soil first decreases and then increases with an increase in the gravel content. In the process of unloading, the shear modulus of the sliding zone soil increases with an increase in the gravel content.
How to cite: Chen, Y.: Bender Element Test and Numerical Simulation of Sliding Zone Soil with Gravels of Huangtupo Landslide, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14480, https://doi.org/10.5194/egusphere-egu21-14480, 2021.
The eastern part of the transboundary UNESCO Global Geopark Muskau Arch and the southern part of the Landscape park of the same name include four areas that are the subject of research in a project financed by the OPUS National Science Centre (No. 2019/33/B/ST10/02975).
The Muskau Arch is a unique moraine structure created as a result of the multi-stage influence of the Scandinavian ice sheet. Its most characteristic geomorphological feature are parallel sequences of land surface depressions, separated by local moraine hills.
The area in question covers the former German and Polish mine “Babina”, active between 1920 and 1972. Brown coal, ceramic clay and glass sands deposits were exploited with underground and opencast methods, resulting in a variety of anthropogenic transformations in the entire region.
The internal geological structure of the Muskau Arch, identified by drilling and mining works, indicates the presence of many zones, which differ in terms of the style of glacial-tectonic sediment deformation.
As part of the project, geophysical research (gravimetric and seismic) and geotechnical drilling were carried out providing new information on the character and scale of anthropogenic transformations of the glaciotectonic area, as well as the origins of anthropogenic and natural terrain deformations.
The developed gravimetric maps combine the geomorphological forms of the terrain and surface deformations with the geological structure and anthropogenic or natural changes. The qualitative interpretation is based on the analysis of the distribution, size and amplitude of gravity anomalies reflecting the bulk density of the sediments that make up the studied medium. Negative anomalies reflect the shortage of masses, which, as a natural factor, should be associated with the presence of weathering brown coal seams, their extent and dip. They are also generated by anthropogenic processes related to mining exploitation and translate into post-mining voids, zones of continuous consolidation and subsidence trough and post-mining heaps. Anomalies with positive amplitudes show the presence of tills, glacial sands and clays.
The results of measurements along seismic cross-sections confirmed the high glaciotectonic involvement within the Tertiary formations, showed the framework character of the top of the underlying (Cretaceous) deposits and allowed for the interpretation of lithostratigraphic boundaries.
Additionally, geotechnical drilling to a depth of 12 m was carried out in selected places using an impact system (Stitz) and a geotechnical light probe (Dynamic Penetration Light). The drillings were made in places that differed in the type of human interference: heaps, surface sinkholes, as well as in places intact by mining activities. The data from the drilling will be used for the geological and engineering analysis of morphological disturbances in the next tasks, including the construction of the model using the finite element method.
The natural and anthropogenic geomorphological forms of various origins that co-occur in the area of the UNESCO Global Geopark Muskau Arch constitute a part of the global geological and cultural heritage of a great importance in Poland and in Europe. Research which aim at discovering the genesis of these transformations can greatly contribute to our understanding of the modern-day environmental changes.
How to cite: Warchala, E., Becker, M., Blachowski, J., Buczyńska, A., Bugajska, N., Janicki, D., Koźma, J., Kwaśny, L., and Wajs, J.: Anthropogenic transformations in the glaciotectionical area in the Polish part of the Muskau Arch, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7996, https://doi.org/10.5194/egusphere-egu21-7996, 2021.
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