NH3.5

Landsliding is the downslope movement of surface material under the force of gravity, initiated when gravitational and other types of shear stresses within the slope exceed the shear strength of the material that forms the slope. Often, landslides pose a physical and environmental threat to communities living in landslide-prone areas. While much landslide research focuses on monitoring techniques to define the background of the landslide (extent, volume, velocity, magnitude) one of the main goals of the Geological Surveys (GS) are to support and understand the regional and local geology to identify areas susceptible to landslides. With this perspective, a questionnaire on landslides monitoring techniques was distributed among GS of Europe to define which techniques are most widly used at GS and to distinguish those that can be considered as powerful tool for landslide mapping, monitoring, hazard analysis, and early warning, according to the type of geological settings. The initial results of the questionnaire showed that the most commonly used monitoring techniques are geotehnical and mapping, followed by remote sensing and hydrological techniques. Among the 849,543 landslide records evidenced by the Geological Surveys of Europe in the paper of Herrera et al. (2017), we found only 47 landslides that have been monitored. However, only landslides that directly threatning the population and infrastructure or landslides with a volume greater than 10,000 m³ have been monitored. Compared to other research (Hague et al., 2016; Froude and Petley, 2018) the questionnaire showed that the fundamental basis for any geologically-related study is geological field mapping. The results of this traditional method are commonly compiled and interpreted together with boreholes, other advanced geodetic (UAV photogrammetry, TLS, GNSS, GBInSAR), and geophysical techniques (electrical resistivity, seismic refraction, GPR). One of the critical survey findings shows on starting landslide monitoring after the failure, only 3% of observed landslides have been monitored before the occurrence. Considering these results, we evaluate the landslide-monitoring techniques and reveal different monitoring strategies between the GS of Europe.

Froude, M.J. and Petley, D. (2018) Global fatal landslide occurrence from 2004 to 2016. Natural Hazards and Earth System Sciences, 18. pp. 2161-2181

Haque U, Blum P, da Silva PF, Andersen P, Pilz J, Chalov SR, Malet J-P, Auflič MJ, Andres N, Poyiadji E, Lamas PC, Zhang W, Peshevski I, Pétursson HG, Kurt T, Dobrev N, García-Davalillo JC, Halkia M, Ferri S, Gaprindashvili G, Engström J, Keellings D (2016) Fatal landslides in Europe. Landslides 13:1–10

Herrera, G., Mateos, R. M., García-Davalillo, J. C., Grandjean, G., Poyiadji, E., Maftei, R., Filipciuc, T.C., Jemec Auflič, M., Jež, J., Podolszki, L., Trigila, A., Iadanza, C., Raetzo, H., Kociu, A., Przyłucka, M., 446 Kułak, M., Sheehy, M., Pellicer, X. M., McKeown, C., Ryan, G., Kopačková, V., Frei, M., Kuhn, D., 447 Hermanns, R. L., Koulermou, N., Smith, C. A., Engdahl, M., Buxó, P., Gonzalez, M., Dashwood, C., 448 Reeves, H., Cigna, F., Liščák, P., Pauditš, P., Mikulėnas, V., Demir, V., Raha, M., Quental, L., Sandić, C., and Jensen, O. A. (2018) Landslide databases in the Geological Surveys of Europe, Landslides, 15, 450: 359-379.

How to cite: Jemec Auflič, M., Herrera, G., María Mateos, R., Poyiadji, E., Quental, L., Severine, B., Peternel, T., Podolszki, L., Iadanza, C., Kociu, A., Warmuz, B., Jelének, J., Hadjicharalambous, K., Peterson Becher, G., Dashwood, C., Liščák, P., Minkevičius, V., Todorović, S., and Jørgen Møller, J.: Landslides monitoring techniques review in the Geological Surveys of Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8536, https://doi.org/10.5194/egusphere-egu21-8536, 2021.

Are we justified in referring to all landslides as natural hazards? With the effects of climate change, landslide incidences are increasing all over the world, and many of them accompany floods and occur due to extreme weather events. It has been unequivocally established that humans are responsible for global climate change. Further, landslides also occur in deforested areas. Even if one were to discount the effects of deforestation on climate change and the subsequent occurrence of landslides, one cannot ignore the fact that deforestation leads to slope instabilities in multiple ways. It decreases the effective retaining strength of the slope materials and also exposes more slope material to weathering and consequent leaching. Thus, deforestation and climate change, caused directly or indirectly by human beings, have a significant bearing on landslide occurrence. Furthermore, several catastrophic landslides in recent times have occurred due to indiscriminate human activity, such as constructing dams and other structures on fragile slopes, blasting slopes for road construction without providing adequate toe support, excessive mining, constructing faulty retaining structures on unstable slope material, etc. Over the years, such human activity has resulted in landslides of all types and at various scales. Whether a landslide is natural, caused due to anthropogenic factors, or a combination of the two, the investigation approach and monitored parameters remain the same; we still need to identify the various causative factors and quantify their rates of change over time in the run up to the landslide event. However, we need a paradigm shift in our perspective and treatment of landslides. We need to accept that human activity is, or can be, responsible for landslide occurrence. With this change in perspective, we would monitor slopes with an increased awareness that human actions could negatively impact slope stability. This, in turn, would entail monitoring at every stage to ensure that no human activity adversely impacts the natural balance, thus paving the way for truly sustainable development. We would be doing great disservice to the investigation and monitoring of landslides by such preconceived notions as all landslides are natural hazards. It is high time that we accept our part in compounding the problem of landslide occurrences and come up with solutions to monitor the impact of human activity on the environment to prevent landslides.

How to cite: Ramanathan, K. and Vasudevan, N.: Anthropogenic causes of landslides and their implications for monitoring, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6933, https://doi.org/10.5194/egusphere-egu21-6933, 2021.

The launch of the Sentinel-1 constellation by the European Copernicus Program, primarily devoted to scientific community research, has allowed acquiring huge volumes of radar images with worldwide coverage and a short temporal sampling (12 days reduced to 6 days thanks to their position at 180° in the same orbit). The systematic collection of imagery and the repeated processing of each new pair of images acquired opened the unprecedent possibility of conducting a continuous monitoring of Earth surface deformations, such as subsidence and slope instabilities over different geomorphological settings. At present, Tuscany, Veneto and Valle d’Aosta regions (Italy) are benefiting from systematical Sentinel-1-based monitoring of geological and geomorphological hazards. The promising outcomes so far obtained constitute a decisive step towards near-real-time monitoring and therefore a valid support for geohazard risk management activities. Retracing the pattern set by the encouraging results from the three Italian Regions, an operating workflow chain is proposed in the framework of an operational monitoring service, from the collection of satellite images to the possibility of conducting field surveys. The procedure is based on 4 different steps: i) continuous collection of Sentinel-1 images, constant data processing through an MT-InSAR (Multi-Temporal Interferometric Synthetic Aperture Radar) technique and exploitation of a data-mining algorithm able to retain only meaningful Measurement Points (MP) in terms of abrupt change of displacement rate; ii) radar-interpretation of the filtered MP for the detection of the possible causes of the anomalies through the use of ancillary informative layers or pre-existing databases; iii) dissemination of the relevant radar-interpreted information to hydrological risk managing actors by a direct alert or periodic bulletins; iv) field investigation, preliminary risk assessment and possible remedial works design. The procedure was successfully applied gathering evidence of its usefulness in practical terms. The cases of the Bosmatto landslide (Valle d’Aosta Region) and the case of the Zeri Landslide (Tuscany Region) which belong to two alpine and apennine environments, respectively, are reported. In the first example, in response to a relevant acceleration interpreted from the MP available on the area of interest, an alert was sent to the regional officers who increased their awareness related to the risk posed by the Bosmatto Landslide. In the second example, a monitoring bulletin which is periodically delivered for the Tuscany Region pointed out the meaningfulness and persistency of anomalies identified in the Zeri municipality. This led the regional authorities to conduct a site investigation oriented to the assessment of preliminary risks. The presented results highlight the effective benefits-cost ratio, the high precision and the short amount of time required to complete the procedure representing a best practice for the early detection of ground deformation events.

How to cite: Festa, D., Confuorto, P., Del Soldato, M., Bianchini, S., and Casagli, N.: From Sentinel-1 data processing to field survey: an operating workflow for the continuous monitoring of the Earth surface deformations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9629, https://doi.org/10.5194/egusphere-egu21-9629, 2021.

Landslide activity is an important information for landslide hazard assessment. However, an information gap regarding up to date landslide activity is often present. Advanced differential interferometric SAR processing techniques (A-DInSAR), e.g. Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) are able to measure surface displacements with high precision, large spatial coverage and high spatial sampling density. Although the huge amount of measurement points is clearly an improvement, the practical usage is mainly based on visual interpretation. This is time-consuming, subjective and error prone due to e.g. outliers. The motivation of this work is to increase the automatization with respect to the information extraction regarding landslide activity.

This study focuses on the spatial density of multiple PSI/SBAS results and a post-processing workflow to semi-automatically detect active landslides. The proposed detection of active landslides is based on the detection of Active Deformation Areas (ADA) and a subsequent classification of the time series. The detection of ADA consists of a filtering of the A-DInSAR data, a velocity threshold and a spatial clustering algorithm (Barra et al., 2017). The classification of the A-DInSAR time series uses a conditional sequence of statistical tests to classify the time series into a-priori defined deformation patterns (Berti et al., 2013). Field investigations and thematic data verify the plausibility of the results. Subsequently the classification results are combined to provide a layer consisting of ADA including information regarding the deformation pattern through time.

How to cite: Kalia, A. C.: Classification of landslide activity based on spaceborne interferometric SAR at the Moselle Valley, Germany, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11873, https://doi.org/10.5194/egusphere-egu21-11873, 2021.

Interferometric Synthetic Aperture Radar (InSAR) enables detailed investigation of surface landslide movements but lacks information about subsurface recognition/identification. It can be obtained by means of direct measurements (e.g., geotechnical data) and geophysical techniques. InSAR observations, seismic noise measurements, and geotechnical data were integrated to assess the deformation on the ground surface and to determine the depth of the failure surface of the Villa de Independencia landslide, Cochabamba (Bolivia) affecting the village. It is a compound slow-moving landslide (total area approximatively 3.8·10⁶ m²) composed by three sub-blocks slide exhibiting diverse geometries, multiple failure surfaces, and magnitudes.

For investigating the spatiotemporal characteristics of the landslide motion, Sentinel-1 time series from October 2014 to December 2019 were analysed. A new geometric inversion method was also proposed to determine the best-fit sliding direction and inclination of the landslide. Results of the Sentinel-1 time series show two substantial accelerations in early 2018 and 2019, coinciding with an increment of precipitations in the late rainy season. It allows supposing the rainy as the most likely triggers of the identified accelerations.

The seismic noise measurements (more than one hundred spreaded over the whole landslide), analysed according to the Vertical to Horizontal Spectral Ratio technique (H/V), were calibrated and validated by means of the geotechnical data derived by three boreholes and 13 between rock and soil samples. H/V data allowed identifying the different dynamic characteristics of the three sub-blocks: movements are possibly due to the different properties of shallow and deep slip surfaces. The landslides caused damage on the edifices, probably mainly caused by the shallow slip interface (located at a mean depth of 5 m) since the foundation depth of the buildings is at most 2 m. In the town centre a deeper failure surfaces, approximatively with depth between 15 and 75 m, can be identified which may be responsible for its different direction and acceleration magnitude of sliding (inferred by InSAR) compared to the other parts of the landslides. Finally, the determination of the slip surface depths allowed to estimate the overall landslide volume assessed approximatively 9.18·10⁷ m³.

The study shows the great potential for landslide motion characterization and mechanism investigation by combing InSAR, seismic noise and geotechnical measurements.

How to cite: Pazzi, V., Del Soldato, M., Song, C., Yu, C., Li, Z., Cruz, A., and Utili, S.: InSAR, seismic noise, and geotechnical data to assess landslide activity and geometry: the Villa de Independencia (Cochabamba, Bolivia) case study, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12300, https://doi.org/10.5194/egusphere-egu21-12300, 2021.

Transportation corridors in mountain regions are often situated at the bottom of narrow valleys. Changing slope stability conditions can put these routes at critical risk. Slope stabilization works (e.g., rock scaling, blasting) or structural protection measures (e.g., rock sheds, reinforced embankments, tunnels) are not always feasible or may not be cost-effective due to low average daily traffic or the expected event size. Route SP29 is the main connection road to Santa Catarina, a popular tourist resort in the Frodolfo River Valley, Lombardy, Italy. The Ruinon landslide is a major slope instability involving approximately 30 million m³ of rock and debris and causes repeated rockfalls that can reach as far as the road. 

We present a Doppler radar system for real-time rockfall detection and immediate road closure in case of an event. The rockfall radar permanently monitors the landslide area from the opposite side of the slope with a range of more than 1 km to the upper scarp. Radar technology works reliably regardless of visibility, i.e. in rain, fog or snowfall as well as at night. After an initial calibration period in summer 2020, we activated automatic road closure and reopening in case of a rockfall event; upon detection of rockfall in a defined region of interest, the radar system automatically switches the traffic lights to red. If the rock fall event reaches a defined zone near the road or the road itself, it remains closed and requires manual reset after site inspection with webcams at the radar site and the traffic lights. If the rockfall event remains above the road, then the radar system automatically releases the road again after 90 seconds. Automatic notifications about the status are sent to authorized user via email and SMS. In addition to the deployment of the alarm system using Doppler radar, the embankment along the endangered road section was reinforced and raised. These combined measures of protection structures and alarm system aim at maximising the opening hours of the street while providing the highest possible level of protection. Between July (installation) and December 2020, 60 rockfall events caused a road closure, with the road being automatically reopened by the system in approximately 85% of cases.

How to cite: Wahlen, S., Stähly, S., Schmid, L., Meier, L., Carlà, T., and Casagli, N.: Real-time Rockfall Detection System with Automatic Road Closure and Reopening using Doppler Radar Technology at the Ruinon Landslide, Italy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14818, https://doi.org/10.5194/egusphere-egu21-14818, 2021.

The presence of roads is closely linked with the activation of land degradative phenomena such as landslides. Factors such as ineffective road management and design, local rainfall regimes and specific geomorphological elements actively influence landslides occurrence. In this context, recent developments in digital photogrammetry (e.g. Structure from Motion; SfM) paired with Remotely Piloted Aircraft Systems (RPAS) increase our possibilities to realize low-cost and recurrent topographic surveys. This allows the realization of multi-temporal (hereafter 4D) and high-resolution Digital Elevation Models (DEMs), fundamental to analyse geomorphological features and quantify processes at the fine spatial and temporal resolutions at which they occur. In this research is presented a 4D comparison of geomorphological indicators describing a landslide-prone agricultural system, so as to detect the noticed high-steep slope failures. The possibility to analyse the evolution of landslide geomorphic features in steep agricultural systems through high-resolution and 4D comparison of such indicators is still a challenge to be investigated. In this research, we considered a case study located in the central Italian Alps, where two shallow landslides (L1, L2) were activated below a rural road within a terraced vineyard. The dynamics of the landslides were monitored through the comparison of repeated DEMs (DEM of Difference, i.e. DoD), that reported erosion values of above 20 m³ and 10 m³ for the two landslides zones and deposition values of more than 15 m³ and 9 m³ respectively. The elaboration of Relative Path Impact Index (RPII) highlighted the role played by the road in the alteration of surface water flow directions. Altered water flows were expressed by values between 2σ and 4σ of RPII close to the collapsed surfaces. The increasing of profile curvature and roughness index described landslides evolution over time. Finally, the multi-temporal comparison of features extraction underlined the geomorphological changes affecting the study area. The computation of the quality index underlined the accuracy of features extraction. This index is expressed in a range between 0 (low accuracy) and 1 (high accuracy) and resulted equal to 0.22 m, regarding the landslide observed during the first RPAS survey (L1-pre); 0.63 m, concerning the same landslide detected during the second RPAS survey (L1-post); 0.69 m for L2. Results prove the usefulness of high-resolution and 4D RPAS-based SfM surveys for the investigation of landslides triggering due to the presence of roads at hillslope scale in agricultural systems. This work could be a useful starting point for further studies of landslide-susceptible zones at a wider scale, to preserve the quality and the productivity of affected agricultural areas.

How to cite: Mauri, L., Straffelini, E., Cucchiaro, S., and Tarolli, P.: RPAS-SfM 4D mapping of shallow landslides activated in a steep terraced vineyard, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2368, https://doi.org/10.5194/egusphere-egu21-2368, 2021.

This project aims at the use of Unmanned Aircraft Systems (UAS) applications for mapping. Geomorphological mapping of features and changes with the use of UAS, in cases of floods, landslides, stream flows, etc. has been growing rapidly in recent years. It is combined with traditional mapping methods as well as modern technologies such as Geographic Information System (GIS). Our work concerns landslide hazard in the study area of Chios, in particular along the Chios - Kardamila road in the Mersinidi - Miliga region with a record of landslides and particular geological interest. During the field survey a) three-dimensional model of the slope was made across the road using UAS and the apropriate software, b) point cloud, c) a mosaic orthophotomap and d) a Digital Surface Model (DSM). After the data collection components material we followed detailed geological and tectonic mapping with enormous accuracy because the innovative technologies provided us multiple data compared to older methodologies. The exploitation of the Structure from Motion provided us with information of the inaccessible parts of the study area.

How to cite: Spyrou, N.-I., Stanota, E. S., Andreadakis, E., Skourtsos, E., Lozios, S., and Lekkas, E.: Mappıng wıth the use of uas. Project plannıng and adjustment: the case of Mersınıdı landslıdes (Chıos Island, NE Aegean), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14380, https://doi.org/10.5194/egusphere-egu21-14380, 2021.

Billions of passive Radiofrequency tags are produced by the Radio-Frequency Identification (RFID) industry every year to identify goods remotely. Enhanced RFID adds the capacity for localisation and sensing that can be used in earth science for long-term and spatially dense monitoring with low-cost tags. Localisation has been used already to monitor displacements of coarse sediment and landslides over several metres. Sensing capabilities have been developed in laboratories, but never implemented on real fields. This work presents the first RFID sensing application in earth science, using the simplest 1-bit sensor to detect millimetric motion of unstable rocks. The application required designing custom RFID tags adapted for outdoor usage at long range, adapting the data acquisition of an existing tag microcircuit, and designing a sensor that triggers when displacement exceeds a few millimetres, which threshold displacement can be adapted for each sensor. In complement, the system embeds displacement sensing to measure larger displacements> 5 mm, using the phase-based measurement already deployed on landslides. The presentation display results from laboratory tests and from an implementation in a real site in Eastern France. The advantages and drawbacks of the method are discussed, as well as the future potential RFID sensors that could monitor unstable terrains.

Author’s published work on the topic:

Le Breton, M., Baillet, L., Larose, E., Rey, E., Benech, P., Jongmans, D., Guyoton, F., 2017. Outdoor UHF RFID: Phase Stabilization for Real-World Applications. IEEE Journal of Radio Frequency Identification 1, 279–290.

Le Breton, M., Baillet, L., Larose, E., Rey, E., Benech, P., Jongmans, D., Guyoton, F., Jaboyedoff, M., 2019. Passive radio-frequency identification ranging, a dense and weather-robust technique for landslide displacement monitoring. Engineering Geology 250, 1–10.

Le Breton, M., 2019. Suivi temporel d’un glissement de terrain à l’aide d’étiquettes RFID passives, couplé à l’observation de pluviométrie et de bruit sismique ambiant (PhD Thesis). Université Grenoble Alpes, ISTerre, Grenoble, France.

Le Breton, M., Baillet, L., Larose, É., Rey, E., Jongmans, D., Guyoton, F., Benech, P., 2020. Passive RFID, a new technology for dense and long-term monitoring of unstable structures: review and prospective. (No. EGU2020-19726). Presented at the EGU2020, Copernicus Meetings. https://doi.org/10.5194/egusphere-egu2020-19726

Le Breton M., 2020, Suivi de terrains instables à l'aide d'un réseau dense de capteurs RFID: Émergence de nouvelles applications, presented at Journées Nationales de Géotechnique et de Géologie de l'ingénieur (JNGG), Jean Goguel Award public session, 2021.

How to cite: Le Breton, M., Grunbaum, N., Baillet, L., and Larose, É.: Monitoring rock displacement threshold with 1-bit sensing passive RFID tag, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15305, https://doi.org/10.5194/egusphere-egu21-15305, 2021.