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Debris flow events, generated by surface runoff, occur with great frequency in the Dolomites (Northeastern Italian Alps) during the summer season. Summer thunderstorms, which are common in the region, can quickly generate runoff at the base of rocky cliffs, which then entrains and propagates downstream the underlying unconsolidated material. In the past, the main atmospheric feature considered in evaluating the initiation of debris flow events was rainfall. Observations led to the development of rainfall intensity–duration thresholds for sediment mobilization, which compared incoming severe rainfalls with the potential for triggering debris flows. This study works toward the examination of another characteristic of the atmosphere, the atmospheric electric field. In particular, the behavior of the electric field prior to convective rainfall is investigated as an indicator of rainfall intensities capable of triggering debris flows, in a basin near Cortina d’Ampezzo (Italy). Results suggest that prior to bursts of intense rainfall, the electric field derivative frequency distribution exhibits a recurrent pattern roughly half the time. When it occurs, the amplitude of derivative frequency distribution intersects the zero axis twice before rainfall reaches maximum intensity. A regression model is designed which considers the amplitude maximum and the difference in time between the crossings of the zero axis. The validation of this model suggests a mild relationship between electric field and rainfall intensity in an alpine environment.

Transformer-based neural networks represent a successful self-attention mechanism that achieves state-of-the-art results in language understanding and sequence modeling. However, their application to visual data and, in particular, to the dynamic hand gesture recognition task has not yet been deeply investigated. In this paper, we propose a transformer-based architecture for the dynamic hand gesture recognition task. We show that the employment of a single active depth sensor, specifically the usage of depth maps and the surface normals estimated from them, achieves state-of-the-art results, overcoming all the methods available in the literature on two automotive datasets, namely NVidia Dynamic Hand Gesture and Briareo. Moreover, we test the method with other data types available with common RGB-D devices, such as infrared and color data. We also assess the performance in terms of inference time and number of parameters, showing that the proposed framework is suitable for an online in-car infotainment system.

Landslides are widespread geological features in Italy’s Northern Apennines, with slow-moving earthflows among the most common types. They develop in fine-grained rocks and are subject to periodic rainfall-induced reactivations alternating to phases of dormancy. In this paper, we use radar interferometry (InSAR) and information about landslide activity to investigate deformation signals on an areal basis and to assess the dynamics of recently reactivated earthflows. We use traditional two-pass interferometry by taking advantage of the short revisit time of the Sentinel 1 satellite to characterize 4 years of slope deformations over the 60 km2 study area, where 186 landslides are mapped. Our results show that most intense and sustained deformation signals are associated with phenomena on the verge of reactivation, indicating that radar interferometry may have a potential for early warning purposes. By focusing on three specific earthflow reactivations, we analyze their dynamics through the years that preceded their failure. Despite inherent uncertainties, it was possible to retrieve the deformation signal’s temporal evolution, which displayed seasonally recurring accelerations, peaking during the major precipitation episodes in the area.

In this work we propose a deep learning pipeline to predict the visual future appearance of an urban scene. Despite recent advances, generating the entire scene in an end-to-end fashion is still far from being achieved. Instead, here we follow a two stages approach, where interpretable information is included in the loop and each actor is modelled independently. We leverage a per-object novel view synthesis paradigm; i.e. generating a synthetic representation of an object undergoing a geometrical roto-translation in the 3D space. Our model can be easily conditioned with constraints (e.g. input trajectories) provided by state-of-the-art tracking methods or by the user itself. This allows us to generate a set of diverse realistic futures starting from the same input in a multi-modal fashion. We visually and quantitatively show the superiority of this approach over traditional end-to-end scene-generation methods on CityFlow, a challenging real world dataset., Accepted at ICPR2020

Slow moving landslides are widespread geomorphological features in the Northern Apennines of Italy where they represent one of the main landscape forming processes. The lithology of the Northern Apennines fold and thrust belt is characterized by alternations of sandstone, siltstone and clayshales, also known as flysch, and clay shales with a chaotic block in matrix fabric, which are often interpreted as tectonic or sedimentary melanges. While flysch rocks with a high pelitic fraction host earthslides that occasionally evolve into flow like movements, earthflows are the dominant landslide type in chaotic clay shales. In the present work, we document the kinematic response to rainfall of landslides in these different lithologies using radar interferometry. The study area includes three river catchments in the Northern Apennines. Here, the Mediterranean climate is characterized by two wet seasons during autumn and spring respectively, separated by dry summers and winters with moderate precipitation. We use SAR imagery from the X-band satellite COSMO SkyMed and from the C-band satellite Sentinel 1 to retrieve spatial displacement measurements between 2009 and 2016 for 25 landslides in our area of interest. We also document detailed temporal and spatial deformation signals for eight representative landslides, although the InSAR derived deformation signal is only well constrained by our dataset during the years 2013 and 2015. In spring 2013, long enduring rainfalls struck the study area and numerous landslide reactivations were documented by the regional authorities. During 2013, we measured higher displacement rates on the landslides in pelitic flysch formations compared to the earthflows in the clay shales. Slower mean velocities were measured on most landslides during 2015. We analyse the temporal deformation signal of our eight representative landslides and compare the temporal response to precipitation. We show that earthslides in pelitic flysch formations accelerate faster than earthflows in chaotic clay shales and reach higher velocities, while the kinematic behaviour of the earthflows can be described as rather steady with only minor accelerations. Although we have no detailed pore pressure measurements for the period of interest, the observed behaviour can be explained in our view by the morphological and hydrological characteristics of the different landslide types. On the one hand landslide material and bedrock in the pelitic flysch rocks are more resistant, which is why slope angles are higher in this lithology. On the other hand, landslides in the pelitic flysch formations have often deeper slip surfaces and landslide material is more permeable. This is why long persistent rainfall is necessary to saturate the landslide material and induce pore pressures that are high enough to trigger displacement.

Landslide is one of the repeated geological hazards during rainy season, which causes fatalities, damage to property and economic losses in Korea. Landslides are responsible for at least 17% of all fatalities from natural hazards worldwide, and nearly 25% of annual casualties caused by natural hazards in Korea. Due to global climate change, the frequency of landslide occurrence has been increased and subsequently, the losses and damages associated with landslides also have been increased. Therefore, accurate prediction of landslide occurrence, and monitoring and early warning for ground movements are very important tasks to reduce the damages and losses caused by landslides. Various studies on landslide prediction and reduction in landslide damage have been performed and consequently, much of the recent progress has been in these areas. In particular, the application of information and geospatial technologies such as remote sensing and geographic information systems (GIS) has greatly contributed to landslide hazard assessment studies over recent years. In this paper, the recent advances and the state-of-the-art in the essential components of the landslide hazard assessment, such as landslide susceptibility analysis, runout modeling, landslide monitoring and early warning, were reviewed. Especially, this paper focused on the evaluation of the landslide susceptibility using probabilistic approach and physically based method, runout evaluation using volume based model and dynamic model, in situ ground based monitoring techniques, remote sensing techniques for landslide monitoring, and landslide early warning using rainfall and physical thresholds.

Landslides are common landscape features in the Northern Apennine mountain chain and cause frequent damages to human structures and infrastructure. Most landslides in the area can be classified as earthflows, where the clay-shales form the substrate, whereas complex landslides with flow and sliding components are common on the slopes where fine-grained turbidites form the substrate. Most of these landslides move periodically with contained velocities and, only after particular rainfall events, some of them accelerate abruptly. Space-borne synthetic aperture radar interferometry (InSAR) provides a particularly convenient way for studying the periods before and after failures. In this paper, we present InSAR-results derived from the Sentinel 1 satellite constellation for two landslide cases in the Northern Apennines. The first case is a complex landslide that is hosted on a pelitic flysch formation, whereas the second case is an earthflow located in chaotic clay shales. Both cases failed catastrophically and threatened or damaged important infrastructures. In the case of the complex landslide, we report spatially variations of the deformation field between repeated periods of acceleration. The data illustrate that the deformation initiated in the upper part of the slope and expanded over the whole landslide body afterward. In the case of the earthflow, we describe spatial and temporal kinematics during the period before a catastrophic failure in March 2018. We discuss the temporal deformation signal together with rainfall and snowmelt data from a nearby meteorological station. Deformation and precipitation data highlight that high total precipitation can be considered the trigger of the failure.

Slow moving earth-flows are a common geomorphological feature in the Northern Apennines and one of the main landscape forming agents. Often houses and small villages were built on these phenomena which are as consequence affected by damages that are caused by small displacements. In this short note, we present the InSAR results obtained from the Stanford Method of Persistent Scatterers (StaMPS) for Cosmo SkyMed and Envisat imagery together with a geologicalgeomorphological survey. We focus on the village of Gaggio Montano located in the Apennines south of Bologna. Here the tectonically sheared Flysch of the Monghidoro Formation structurally overlies the mélange of the Palombini shales and different complex landslides were mapped on the slope. We show that several landslide bodies are moving with steady deformation rates at least since 2003 and that the results obtained from Envisat and Cosmo SkyMed compare well to each other. Moreover the displacements measured by InSAR are in the same order of magnitude as displacements that have been measured in the past with inclinometers. Because the higher deformation rates are closely related to young houses and industrial complexes, it is possible that anthropogenic factors, like leakage from the water supply/discharge system, influence the displacements. A steady infiltration of water from the Flysch slabs into the clay shales might however represent a possible explanation.

In dolomitic headwater catchments, intense rainstorms of short duration produce runoff discharges that often trigger debris flows on the scree slopes at the base of rock cliffs. In order to measure these discharges, we placed a measuring facility at the outlet (elevation 1770 m a.s.l.) of a small, rocky headwater catchment (area ∼ 0.032 km2, average slope ∼ 320%) located in the Venetian Dolomites (North Eastern Italian Alps). The facility consists of an approximately rectangular basin, ending with a sharp-crested weir. Six runoff events were recorded in the period 2011-2014, providing a unique opportunity for characterizing the hydrological response of the catchment. The measured hydrographs display impulsive shapes, with an abrupt raise up to the peak, followed by a rapidly decreasing tail, until a nearly constant plateau is eventually reached. This behavior can be simulated by means of a distributed hydrological model if the excess rainfall is determined accurately. We show that using the Soil Conservation Service Curve-Number (SCS-CN) method and assuming a constant routing velocity invariably results in an underestimated peak flow and a delayed peak time. A satisfactory prediction of the impulsive hydrograph shape including peak value and timing is obtained only by combining the SCS-CN procedure with a simplified version of the Horton equation, and simulating runoff routing along the channel network through a matched diffusivity kinematic wave model. The robustness of the proposed methodology is tested through a comparison between simulated and observed timings of runoff or debris flow occurrence in two neighboring alpine basins. This article is protected by copyright. All rights reserved.

The Dolomite Alps of northeastern Italy experience debris flows with great frequency during the summer months. An ample supply of unconsolidated material on steep slopes and a summer season climate regime characterized by recurrent thunderstorms combine to produce an abundance of these destructive hydrogeologic events. In the past debris flow events have been studied primarily in the context of their geologic and geomorphic characteristics. The atmospheric contribution to these mass wasting events has been limited to recording rainfall and developing intensity thresholds for debris mobilization. This study aims to expand the examination of atmospheric processes that preceded both locally intense convective rainfall (LICR) and debris flows in the Dolomite region. 500 hPa pressure level plots of geopotential heights were constructed for a period of three days prior to debris flow events to gain insight into the synoptic scale processes which provide an environment conducive to LICR in the Dolomites. Cloud-to-ground (CG) lightning flash data recorded at the meso-scale were incorporated to assess the convective environment proximal to debris flow source regions. Twelve events were analyzed and from this analysis three common synoptic scale circulation patterns were identified. Evaluation of CG flashes at smaller spatial and temporal scales illustrated that convective processes vary in their production of CG flashes (total number) and the spatial distribution of flashes can also be quite different between events over longer periods. During the 60 min interval immediately preceding debris flow a majority of cases exhibited spatial and temporal collocation of LICR and CG flashes. Also a number of CG flash parameters were found to be significantly correlated to rainfall intensity prior to debris flow initiation.

none 3 si Advanced interferometric synthetic aperture radar (InSAR) postprocessing, like persistent scatterer InSAR (PSInSAR), offers the possibility to investigate slow moving landslides, where standard interferometry is problematic. These advanced algorithms involve the analysis of a series of SAR acquisitions in both time and space. One input that requires particular attention for landslide applications is the external digital elevation model (DEM) that is used to correct the interferograms for the topographic phase term. When multiple elevation data sets are available for a given study area, it is difficult to decide which one should be used. In this paper, we test the sensitivity of PS-InSAR/Small Baseline Subset (SBAS) results to different DEMs. The study area is located in the Northern Apennines of Italy, where chaotic clay shales and finegrained flysch host slow-moving earth flows and ancient rock slides. C-band (Envisat) and X-band (Cosmo-SkyMed) data are processed with different DEMs. We describe a simple framework to statistically analyze the influence of these models on the final PS-InSAR/SBAS results. We find that individual interferograms do not vary much depending on the DEM, while the results from PS-InSAR and SBAS analysis do vary. This is likely caused by the way the DEM error is estimated. We find also that the quality of the DEM is more important than the resolution and that Xband InSAR data are more sensitive to the choice of the DEM than C-band. The significance of the results is discussed with reference to two landslide areas. Bayer, B.; Schmidt, D.; Simoni A. Bayer, B.; Schmidt, D.; Simoni A.

Synthetic Aperture Radar (SAR) interferometry (InSAR) is used to make measurements of small surface displacements in different situations including ground-settlement, landslides and excavations. We document the deformation history of four dormant deep-seated landslides in the Northern Apennines of Italy that were reactivated by the excavation of a double road tunnel. The tunnel is part of a larger infrastructure project that involves the improvement of the A1 highway which connects Bologna and Florence. The excavation of the tunnel under the landslides’ basal shear surfaces started in 2011, and with the advance of the tunnel front, deformation began to occur, causing damages to homes and infrastructures. The tunnel passes under the small villages of Ripoli and Santa Maria Maddalena. The deformation slowed down after the tunnel was completed in November 2014, and low surface displacement rates were registered for the period between October 2014 and June 2016. We show the results of an InSAR analysis designed to measure surface movements between 2003 and 2016. The InSAR displacements are derived from the Envisat, COSMO SkyMed, and Sentinel 1 datasets and cover the main construction phase of the tunnel (2011-2015). A detailed geological and geomorphological mapping of the slope is developed based on the field evidence and on the spatial pattern of surface deformation provided by our InSAR analysis. Together with the map, a new conceptual geological model of the slope in tectonically sheared and weathered flysch is presented. The satellite InSAR data show good agreement with available ground based monitoring data that include inclinometer and GPS-measurements, while small differences occur with respect to deformation time series obtained from a ground-based InSAR instrument. In particular, the InSAR results for the X-Band data of COSMO SkyMed demonstrate the close relationship between the position of the excavation front and the displacement rates of previously dormant landslide deposits. Conversely, the concurrent rainfall does not appear to significantly influence the observed behaviour and, if any, had only a minor influence on the displacement history of the investigated landslides.