1,721,079 research outputs found
Infrared thermographic surveys for landslide mapping and characterization: the Rotolon DSGSD (Norther Italy) case study
No full textOn November 4th 2010, after several days of intense rainfall, a huge mass (about 225000 m3) detached from the debris cover of the Rotolon landslide, converging within the Rotolon Creek river bed, and evolving into a mobile debris flow that damaged various infrastructures, putting on high risk three villages located along the creek banks. After this event the National Department of Civil Protection (DPCN) appointed the Earth Sciences Department of the Firenze University (DST-UNIFI) to start a GB-InSAR (ground based interferometric synthetic aperture radar) monitoring activity, in order to support the local authorities for the emergency management by analyzing the landslide displacements and evaluating the residual risk. During this phase accurate geomorphological and infrared thermographic (IRT) surveys were also carried out, in order to study the landslide morphological features, with the aim of improving the radar displacement data interpretation. The obtained geomorphological map suggests that the debris production and detachment are hazardous phenomena that involve the surficial detrital cover of a bigger and more complex landslide. The latter has the characteristics of a deep seated gravitational slope deformation (DSGDS)
A review of the advantages and limitations of geophysical investigations in landslide studies
Full text linkLandslide deformations involve approximately all geological materials (natural rocks, soil, artificial fill, or combinations of these materials) and can occur and develop in a large variety of volumes and shapes. The characterization of the material inhomogeneities and their properties, the study of the deformation processes, and the delimitation of boundaries and potential slip surfaces are not simple goals. Since the ‘70s, the international community (mainly geophysicists and lower geologists and geological engineers) has begun to employ, together with other techniques, geophysical methods to characterize and monitor landslides. Both the associated advantages and limitations have been highlighted over the years, and some drawbacks are still open. This review is focused on works of the last twelve years (2007-2018), and the main goal is to analyse the geophysical community efforts toward overcoming the geophysical technique limitations highlighted in the 2007 geophysics and landslide review. To achieve this aim, contrary to previous reviews that analysed the advantages and limitations of each technique using a “technique approach,” the analysis was carried out using a “material landslide approach” on the basis of the more recent landslides classification
Kinematic reconstruction of a deep-seated gravitational slope deformation by geomorphic analyses
No full textOn 4 November 2010, a deep-seated gravitational slope deformation (North Italy) reactivated with sudden ground movement. A 450,000 m2 mountainous area moved some metres downslope, but the undeniable signs were only connected to the triggering of a debris flow from the bulging area’s detrital cover and the presence of a continuous perimeter fracture near the crown area. Based on two detailed LiDAR surveys (2 m × 2 m) performed just a few days before and after the event, a quantitative topographic analysis was performed in a GIS environment, integrating morphometric terrain parameters (slope, aspect, surface roughness, hill shade, and curvature). The DEMs analysis highlighted some morphological changes related to deeper as well as shallow movements. Both global and sectorial displacements were widely verified and discussed, finally inferring that the geometry, persistence, and layout of all movements properly justify each current morphostructure, which has the shape of a typical Sackung-type structure with impulsive kinematics. Moreover, a targeted field survey allowed specific clues to be found that confirmed the global deduced dynamics of the slope deformation. Finally, thanks to a ground-based interferometric radar system (GB-InSAR) that was installed a few days after the reactivation, the residual deep-seated gravitational slope deformation (DSGSD) movements were also monitored. In the landslide lower bulging area, a localized material progression of small entities was observed for some months after the parossistic event, indicating a slow dissipation of forces in sectors more distant from the crown area
Joint detection and classification of rockfalls in a microseismic monitoring network
Full text linkA rockfall (RF) is a ubiquitous geohazard that is difficult to monitor or predict and poses a significant risk for people and transportation in several hilly and mountainous environments. The seismic signal generated by RF carries abundant physical and mechanical information. Thus, signals can be used by researchers to reconstruct the event location, onset time, volume and trajectory, and develop an efficient early warning system. Therefore, the precise automatic detection and classification of RF events are important objectives for scientists, especially in seismic monitoring arrays. An algorithm called DESTRO (DEtection and STorage of ROckfalls) aimed at combining seismic event automatic detection and classification was implemented ad hoc within the MATLAB environment. In event detection, the STA/LTA (short-time-average through long-time-average) method combined with other parameters, such as the minimum duration of an RF and the minimum interval time between two continuous seismic events is used. Furthermore, nine significant features based on the frequency, amplitude, seismic waveform, duration and multiple station attributes are newly proposed to classify seismic events in a RF environment. In particular, a three-step classification method is proposed for the discrimination of five different source types: RFs, earthquakes (EQs), tremors, multispike events (MSs) and subordinate MS events. Each component (vertical, east–west and north–south) at each station within the monitoring network is analysed, and a three-step classification is performed. At a given time, the event series detected from each component are integrated and reclassified component by component and station by station into a final event-type series as an output result. By this algorithm, a case study of the seven-month-long seismic monitoring of a former quarry in Central Italy was investigated by means of four triaxial velocimeters with continuous acquisition at a sampling rate of 200 Hz. During this monitoring period, a human-induced RF simulation was performed, releasing 95 blocks (in which 90 blocks validated) of different sizes from the benches of the quarry. Consequently, 64.9 per cent of EQs within 100 km were confirmed in a one-month monitoring period, 88 blocks in the RF simulation were classified correctly as RF events and 2 blocks were classified as MSs given their small energy. Finally, an ad hoc section of the algorithm was designed specifically for RF classification combined with EQ recognition. The algorithm could be applied in slope seismic monitoring to monitor the dynamic states of rock masses, as well as in slope instability forecasting and risk evaluation in EQ-prone areas
Microseismic signal denoising and separation based on fully convolutional encoder–decoder network
Full text linkDenoising methods are a highly desired component of signal processing, and they can separate the signal of interest from noise to improve the subsequent signal analyses. In this paper, an advanced denoising method based on a fully convolutional encoder–decoder neural network is proposed. The method simultaneously learns the sparse features in the time–frequency domain, and the mask-related mapping function for signal separation. The results show that the proposed method has an impressive performance on denoising microseismic signals containing various types and intensities of noise. Furthermore, the method works well even when a similar frequency band is shared between the microseismic signals and the noises. The proposed method, compared to the existing methods, significantly improves the signal–noise ratio thanks to minor changes of the microseismic signal (less distortion in the waveform). Additionally, the proposed methods preserve the shape and amplitude characteristics so that it allows better recovery of the real waveform. This method is exceedingly useful for the automatic processing of the microseismic signal. Further, it has excellent potential to be extended to the study of exploration seismology and earthquakes
Emergency management of the 2010 Mt. Rotolon landslide by means of a local scale GB-InSAR monitoring system
No full textBetween October 31st and November 2nd 2010 the whole Veneto region (north-eastern Italy) was hit by heavy and persistent rainfall, which diffusely triggered floods and slope failures. In this framework on November 4th 2010 a detrital mass, approximately 225.000 m3 in volume, detached from the lowermost sector of the Mt. Rotolon landslide cover (located in the Vicentine Pre-Alps, upper Agno River Valley), channelizing within the Rotolon Creek riverbed and evolving into a highly mobile debris flow. The latter phenomena, characterized by a 3 km travel distance, damaged many hydraulic works, putting at high risk bridges and local roads located along the creek banks, together with the population of both the town of Recoaro Terme and the villages of Maltaure, Turcati and Parlati. Starting from the beginning of the emergency phase, the Civil Protection system was activated, involving the National Civil Protection Department, Veneto Region and local administrations personnel and technicians, as well as research centers. On December 8th 2010 a local scale monitoring system, based on a ground based interferometric radar (GB-InSAR), was implemented in order to evaluate the slope deformation pattern evolution in correspondence of the debris flow detachment sector, with the final aim of assessing the landslide residual risk and manage the emergency phase. Accurate geomorphological field surveys were also carried out, in order to study the landslide morphological features as to improve the radar data interpretation. The radar system acquired in continuous GB-InSAR data, such as displacement maps and time series of 10 selected monitoring points, which were uploaded via LAN network on a dedicated Web-based interface, shared with the technical stakeholders and decision makers involved in the emergency management and allowing for a near real time data routine visualization. This paper describes the outcomes of a 2 years GB-InSAR monitoring campaign (December 2010-November 2012), reporting the various applications of GB-InSAR data for monitoring, mapping and emergency management activities, in order to provide a rapid and easy communication of the results to the involved technicians and civil protection personnel, for a better understanding of the landslide phenomena and decision making process in a critical landslide scenario
Deep convolutional neural network for microseismic signal detection and classification
No full textReliable automatic microseismic waveform detection with high efficiency, precision, and adaptability is the basis of stability analysis of the surrounding rock mass. In this paper, a convolutional neural network (CNN)-based microseismic detection network (CNN-MDN) model was established and well trained to a high degree of accuracy using a dataset with 16,000 preprocessed waveforms. By comparison with other methods, 4000 waveforms were tested to evaluate the precision, recall, and F1-score. The results revealed that the CNN-MDN demonstrated the highest performance in microseismic detection. Moreover, the low sensitivity of the CNN-MDN to noise of different intensities was proved by testing on semi-synthetic data. The model also possesses good generalization ability and superior performance capability for microseismic detection under different geological structure backgrounds, and it can correctly detect the microseismic events with Mw ≥ 0.5. These preliminary results show that the CNN-MDN can be directly applied to unprocessed microseismic data and has great potential in real-time microseismic monitoring applications
Diffondere la conoscenza e la consapevolezza dei rischi geologici nelle scuole tramite l’informazione, l’innovazione e l’educazione
No full textIl progetto promosso da Inail Direzione regionale per la Toscana e condiviso e sottoscritto da Regione Toscana, dall’Ufficio scolastico regionale del Miur e dal Dipartimento di scien- ze della terra dell’Università degli studi di Firenze è attivo dal 2013 ed ha visto il coinvol- gimento di 52 plessi scolastici di ogni ordine e grado distribuiti in tutto il territorio della Toscana. L’obiettivo è quello di valutare il grado di sicurezza geologica dell’edificio scola- stico, valutare le conoscenze e quindi la resilienza degli occupanti (docenti, personale ata e alunni) e creare i presupposti affinché siano integrati i documenti di valutazione dei rischi e i piani di emergenza con una valutazione dei rischi di natura geologica e le adeguate rispo- ste alle emergenze. La resilienza è considerata come la capacità che ogni comunità consape- vole di convivere con rischi ha di reagire in modo attivo alla presenza di un pericolo, predi- sponendo strategie di prevenzione integrate con le Autorità locali. In caso di rischi poten- zialmente molto lesivi e che possono coinvolgere la totalità delle persone presenti in un luogo di lavoro è di estrema importanza che la risposta alle emergenze sia pronta, adeguata e ben organizzata
Analysis of LiDAR derived DEM geomorphometric parameters to assess the kinematic behaviour of a DSGSD
No full textSlope instability processes in mountainous areas are characterized by a complex interaction between different lithological, geomorphological, structural features, and processes. Deep-seated gravitational slope deformations (DSGSDs) are largest non-catastrophic slow rock-slope deformation, that until recently, under the present climatic condition, were considered inactive and not hazardous phenomena. Generally, the entire slope affected by DSGSD can be differently deformed with millimetric-displacements, that often cannot be observed by means of field surveys. This can generate in the risk management of these phenomena non-exhaustive safety awareness strategies, which on the contrary often focus only on the more short-period localized hazardous effects. DSGSD, in fact, evolve at different time scales and could present sudden and rapid secondary minor landslides. Therefore, a complete risk assessment strategy must comprise also the analysis of deep-seated impulsive phenomena. This type of behaviour can be observed effectively only using high-resolution data obtained by means of advanced remote sensing techniques. Among all these technologies applied in landslide analysis the more effective in the DSGSD studies are: ground-based interferometric radar (GB-InSAR) and Light detection and ranging (LiDAR). On 4th November 2010, after the October-November 2010 rainfalls, the Rotolon deep-seated gravitational slope deformation (Vicentine Pre-Alps, NE Italy) reactivated with a sudden ground movement. A 450,000 m2 mountainous area moved some meter downslope, but the undeniable signs were only connected to the triggering of a debris flow from the bulging area detrital cover, and the presence of a continuous perimeter fracture near the crown area. Therefore, the 2010 event apparently was limited to secondary and localized phenomena, so that an early-warning system (a GB-InSAR and an automatic monitoring network composed by extensometers and a robotic total station) were installed to monitor the residual risk. Moreover, a 3D landslide runout numerical model was performed to identify the source and impact areas of further debris flow, the flow velocity, and the deposit distribution within the Rotolon creek valley. Nevertheless, the analysis of the DEMs parameters, derived from two detailed LiDAR surveys (2x2 m), performed just few days before and after the event, allowed to highlight some morphological changes occurred after the 2010 reactivation, and associable not only to shallow movements but also to deeper ones. The kinematic behavior reconstruction and the geomorphometric parameters analysis were performed in a GIS environment, integrating morphometric terrain parameters (slope, aspect, surface roughness, topographic wetness index, hillshade, and curvature) with the results of an accurate geomorphological field survey. This analysis pointed out not only shallower movements in the bulging area, but also regular morphological changes occurred in six main areas of the whole DSGSD, and connected to deeper continuous displacements along the maximum slope gradient, confirming the DSGSD reactivation. Moreover, the displacements connected to the DSGSD reactivation did not cease immediately, in particular far from the break/crown zone (as shown by the integration of the morphometric terrain parameters and the GB-InSAR data), but continued with very slow deformations until the new equilibrium was reached, testifying the impulsive behavior of the landslide
Geomorphology of the Rotolon landslide (Veneto Region, Italy)
No full textIn this paper a geomorphological map of the Rotolon landslide is presented. This cartographic product was obtained using a combination of accurate field surveys together with airborne Lidar analysis, aerial photo interpretation and thermographic field surveys within a GIS. The map was prepared in order to analyze the morphological features of the landslide and therefore improve interpretation of the GB-InSAR data. This monitoring device was installed on the site after the detachment of a debris mass of 225,000 m3 on 4 November 2010. The main purpose of the post-event activities, including the geomorphological characterization, was to detect the processes acting on the landslide, evaluate the hazard related to each phenomenon, understand the landslide kinematics and define the residual risk for the area.The geomorphological map suggests that debris production and detachment are hazardous phenomena that involve the surficial detrital cover of a bigger and more complex landslide. The latter has the typical characteristics of a deep-seated gravitational slope deformation. The distinction between secondary processes, which appear to be the most hazardous in the short-term, and deep seated ones, demonstrates that accurate mapping provides important information for local administrations and decision makers, allowing them to prepare landslide susceptibility and hazard models
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