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The recent spread of low-cost and high-quality RGB-D and infrared sensors has supported the development of Natural User Interfaces (NUIs) in which the interaction is carried without the use of physical devices such as keyboards and mouse. In this paper, we propose a NUI based on dynamic hand gestures, acquired with RGB, depth and infrared sensors. The system is developed for the challenging automotive context, aiming at reducing the driver&rsquo, s distraction during the driving activity. Specifically, the proposed framework is based on a multimodal combination of Convolutional Neural Networks whose input is represented by depth and infrared images, achieving a good level of light invariance, a key element in vision-based in-car systems. We test our system on a recent multimodal dataset collected in a realistic automotive setting, placing the sensors in an innovative point of view, i.e., in the tunnel console looking upwards. The dataset consists of a great amount of labelled frames containing 12 dynamic gestures performed by multiple subjects, making it suitable for deep learning-based approaches. In addition, we test the system on a different well-known public dataset, created for the interaction between the driver and the car. Experimental results on both datasets reveal the efficacy and the real-time performance of the proposed method.

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.

Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety of application scenarios like Mixed Reality environments, touchless public kiosks, entertainment systems, and more. Recognition of hand gestures can be nowadays performed directly from the stream of hand skeletons estimated by software provided by low-cost trackers (Ultraleap) and MR headsets (Hololens, Oculus Quest) or by video processing software modules (e.g. Google Mediapipe). Despite the recent advancements in gesture and action recognition from skeletons, it is unclear how well the current state-of-the-art techniques can perform in a real-world scenario for the recognition of a wide set of heterogeneous gestures, as many benchmarks do not test online recognition and use limited dictionaries. This motivated the proposal of the SHREC 2021: Track on Skeleton-based Hand Gesture Recognition in the Wild. For this contest, we created a novel dataset with heterogeneous gestures featuring different types and duration. These gestures have to be found inside sequences in an online recognition scenario. This paper presents the result of the contest, showing the performances of the techniques proposed by four research groups on the challenging task compared with a simple baseline method.

Visual observation of uncontrolled real-world behavior leads to noisy observations, complicated by occlusions, ambiguity, variable motion rates, detection and tracking errors, slow transitions between behaviors, etc. We show in this paper that reliable estimates of long-term trends can be extracted given enough data, even though estimates from individual frames may be noisy. We validate this concept using a new public dataset of approximately 20+ million daytime pig observations over 6 weeks of their main growth stage, and we provide annotations for various tasks including 5 individual behaviors. Our pipeline chains detection, tracking and behavior classification combining deep and shallow computer vision techniques. While individual detections may be noisy, we show that long-term behavior changes can still be extracted reliably, and we validate these results qualitatively on the full dataset. Eventually, starting from raw RGB video data we are able to both tell what pigs main daily activities are, and how these change through time.

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

Rainfall thresholds for the occurrence of debris flows are commonly defined by Intensity-Duration curves (ID thresholds). Interestingly, many empirical ID thresholds show up as straight lines in a log-log plot and therefore can be expressed by power-law functions of the form I=α⋅Dβ, where α is the scaling coefficient and β is the exponent of the power function. The different values of α and β reflect the variability of geological and hydrological conditions in the different areas. In most cases, however, field conditions are so complex that a quantitative interpretation of the empirical rainfall threshold is impossible and the physical meaning of α and β remains obscure. In this work, we provide a physical interpretation of the rainfall thresholds that characterize an active debris flow catchment in the Eastern Italian Alps (the Dimai Basin, Belluno Province). The catchment is affected by frequent debris flows generated by surface-water runoff and has been monitored since 2010 to investigate the initiation process. Monitoring data allowed for the detection of two rainfall thresholds: a lower one that identifies the arrival of water in the initiation area (Catchment Outflow Threshold) and an upper one that identifies the initiation of debris flows by channel runoff (Debris Flow Threshold). We demonstrate that these two thresholds can be satisfactorily reproduced by a simple physically based model in which the excess rainfall is routed over the catchment using a kinematic-wave scheme. This simple analysis provides a sound explanation of the observed thresholds and can be used to develop physically based thresholds for runoff-generated debris flows.

In the Dolomitic region, abundant coarse hillslope sediment is commonly found at the toe of rocky cliffs. Ephemeral channels originate where lower permeability bedrock surfaces concentrate surface runoff. Debris flows initiate along such channels following intense rainfall and determine the progressive erosion and deepening of the channels. Sediment recharge mechanisms include rock fall, dry ravel processes and channel-bank failures. Here we document debris flow activity that took place in an active debris flow basin during the year 2015. The Cancia basin is located on the southwestern slope of Mount Antelao (3264 m a.s.l.) in the dolomitic region of the eastern Italian Alps. The 2.5 km2 basin is incised in dolomitic limestone rocks. The data consist of repeated topographic surveys, distributed rainfall measurements, time-lapse (2 s) videos of two events and pore pressure measurements in the channel bed. During July and August 2015, two debris flow events occurred, following similarly intense rainstorms. We compared rainfall data to existing rainfall triggering thresholds and simulated the hydrological response of the headwater catchment with a distributed model in order to estimate the total and peak water discharge. Our data clearly illustrate how debris entrainment along the channel is the main contributor to the overall mobilized volume and that erosion is dominant when the channel slope exceeds 16°. Further downstream, sediment accumulation and depletion occurred alternately for the two successive events, indicating that sediment availability along the channel also influences the flow behaviour along the prevailing-transport reach. The comparison between monitoring data, topographical analysis and hydrological simulation allows the estimation of the average solid concentration of the two events and suggests that debris availability has a significant influence on the debris flow volume. © 2020 John Wiley & Sons, Ltd.

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.

The Piees de ra Mognes fan at the base of the Punta Nera cliffs, in the Venetian Dolomites (Italy), has been subject to debris flow activity for decades. Until recently, these debris flows never reached the National Road 51 on the valley bottom. Debris flows usually initiated at the base of an incised rocky channel in the Punta Nera cliffs where runoff is delivered to loose scree deposits of the fan. The main debris flow channel is strongly incised at the apex of the fan and splits into several minor channels at lower elevations. During the autumn 2014 and May 2016, two cliff collapses produced large debris deposits. Since then, the frequency of debris flows increased considerably because of the availability of debris deposits at very steep slope that lowered the runoff discharge needed for the debris flow initiation. In a few cases, debris flows that initiated in the rocky channel reached and interrupted the National Road 51, about 2 km downstream the well-known touristic village of Cortina d���Ampezzo. On July 2016, a monitoring station was placed at the beginning of the debris flow channel just downstream the base of the rocky channel. In the period between July and -September, the monitoring station recorded six debris flow events. Analysis of these data is used to describe the characteristics of debris flow initial routing. Moreover, we use video image analysis to investigate the velocity and depth of the surge from the 5 August 2016 event.

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.

A total of 87 direct shear tests in a large direct shear-box apparatus have been used to investigate the strength and dilatancy of sand–gravel mixtures. This paper focuses on the differences in behaviour between a silica sand (yellow Leighton Buzzard sand) and sand–gravel mixtures obtained by adding fractions of two kinds of gravel to the sand. The purpose is to find a relation between the grain-size characteristics of the materials and the shearing resistance. Experimental results are analysed in terms of the frictional and dilatant contributions to the strength of mixtures as a function of their relative density, and are compared with dilatancy theories and empirical equations. The addition of gravel to the mixtures, even at low fractions (less than 0.1 by volume), causes an increase in peak friction angle (Φ ′peak) which results both from higher dilatancy at failure (ψ max) and higher constant volume friction angle (Φ ′cv). Use of the minimum voids ratio (e min) of the materials allows the data for the two families of mixtures to be normalized and interpreted in terms of Φ ′cv and the ratio (Φ ′peak − Φ ′cv)/ψ max. The relationships between relative density (D r ), ψ max and Φ ′peak − Φ ′cv are only partly explained on a physical basis, so we develop empirical equations to predict the peak shear resistance of sand–gravel mixtures (up to gravel contents of 0.5) on the basis of easily measurable quantities. Such equations constitute a practical tool to overcome the problems arising from the impracticality of testing coarse material in the standard shear-box apparatus.

The importance of pore water pressure regime for landslide activity is generally accepted. In the case of earthflows, generalized failures (reactivations) are rare and sustained slow movements can proceed for decades. The relationship between precipitation, pore water pressure responses and movement is not straightforward. We document rainfall, pore pressure regime and displacements in the source area of an active earthflow. Pressure heads at shallow depth are clearly related to infiltration from the surface and can be satisfactorily reproduced by a diffusive model while the hypothesis of gravity-dominated flow can be rejected based on the short delay between rainfall and pressure response. Displacement rates are very small to zero during the summer and increase a couple of months later than the onset of the precipitation of the wet season. Only late in the wet season, velocities attain peak values (up to 4 mm/day) and show a remarkable correlation to rainfall episodes. Higher displacement rates correspond to unexceptional pressure head values, we therefore believe that alternative mechanisms of water pressure build-up may exist. Fractures likely act as a preferential flow system and influence both the hydrological responses to rainfall and the deformation behavior of the landslide.

In Northern Apennines, landslides involving weak rocks such as clay shales are widespread and often cause damage to public infrastructure and private properties. These landslides, mostly classifiable as earthflows, generally exhibit continuous slow movements, with temporary increases of velocity controlled both by groundwater and rainfall regime. Although the relationship between precipitation, groundwater flow and displacement rate is evident, its quantitative description remains problematic. We use piezometric and slope movement continuous monitoring to investigate the groundwater flow system in the vicinity of the contact between clay shales and overlying more permeable units, where the village of Lizzano in Belvedere is located. Our aim is to describe the groundwater flow and its relation to slope deformation in order to simulate the effect of possible drainage measures both on piezometric levels and expected displacement rates. Timing and magnitude of piezometric responses at different depths are related to observed deformations and used to calibrate a transient 3D groundwater flow model. Groundwater modeling validates the conceptual hydrogeological scheme and allows simulation of the impact of surface and deep drainages on piezometric levels. Results indicate that horizontal drains are more effective than infiltration reduction measures, both in terms of drawdown and time effectiveness of action. Simulated hydraulic heads are then used to produce a probabilistic prediction of the expected displacement rates by means of an empirical method. In the case of Lizzano in Belvedere, according to our results, the lowering of hydraulic heads operated by horizontal drains can reduce the velocity of slope movements from centimeters per year to millimeters per year.

Clay-shales largely outcrop in the Northern Apennines of Italy, where they are associated with frequent and widespread landslide activity. The paper presents the results of monitoring activities carried out in two field-sites and focused on the hydrology of clay-shales prone to landsliding. In the monitored slopes, the water table is close to the ground surface throughout the year, with seasonal fluctuations of tens of centimetres to a couple of metres. Shallow weathered soils, or clay cover, and unaltered material exhibit a much different behaviour. Although responses to single rainfalls are clearly identifiable as pressure pulses in the clay cover, they are never observed in the underlying parental clay-shales where downward gradients indicate recharge and only long-term seasonal fluctuations are recorded. Short-term variations of pressure head in the clay cover are ruled by downward propagation of a pressure wave in saturated conditions. More than 400 pore-pressure responses collected in the two sites are analysed in terms of lag time, rate and amount of pressure increase and timing of pressure peaking. It emerges that the linear diffusion theory can satisfactorily explain the observed behaviour. In deeper unaltered material, the barometric effect influences the measures similarly to what is observed in confined aquifers. After its removal, the corrected data exhibit regular seasonal fluctuations which are used to estimate the diffusivity of the material based on phase-lag and attenuation of the downward propagating long-term periodic pulse. Copyright © 2011 John Wiley & Sons, Ltd.

Debris flow is an efficient process of sediment transfer from slope base to piedmont depositional fans in mountain drainage basins. To advance understanding of debris-flow sediment dynamics at the regional scale, we analyze a historical (1998–2009) database of debris flows from 77 basins of Alto Adige Province, northeastern Italy. By combining information on event volumetric deposition, high-resolution digital topography, and Quaternary sediment mapping we are able to link debris-flow sediment flux to morphometry, lithologic variability, and sediment availability. We show that basin-wide specific sediment yield (SSY) scales as an inverse power function of basin area. This function is strongly controlled by the way rock type and abundance of Quaternary deposits affect the rate of downstream sediment recruitment. When sediment flux associated with each debris-flow event is subsumed across discrete spatial increments of the entire region, a complex sedimentary signature in the area-SSY space is apparent. That is, SSY increases downstream up to areas as large as 1 km2, and starts to decline beyond this scale, regardless of sediment availability. We propose that this area-SSY relation is characteristic of debris flow–dominated settings.

Empirical mobility relationships can be used for delineating debris flow inundated areas. A database of documented events in alpine mountain catchments of northeastern Italy is used to test the model DFlowz ( Berti and Simoni, 2007 ). We back-analyzed 25 DF events, ranging in volume from 3000 to 350,000 m 3 , with the support of high resolution topographic information derived from LiDAR. The analysis makes use of an objective methodology for evaluating the accuracy of the predictions and involves the calibration of the model based on factors describing the uncertainty associated with the empirical relationships. Results indicate that the model is capable of reproducing the observed behavior with a maximum uncertainty of a factor of 3. The most relevant source of error lies in the estimation of the deposited volumes which affects the results of back-calculation and is mainly responsible also for the scatter associated with the empirical mobility relationships. On the contrary, the influence of different flow properties on the depositional process appears to play a minor role as the mutual relations between the three main scaling parameters (volume, inundated area, and cross-sectional area) are respected in the vast majority of cases and calibrated mobility coefficients show no significant relationship with the angle of reach of the deposit.

Debris flow initiation by channel bed mobilization is a common process in high mountainous areas. Initiation is more likely to occur at the outlet of small, steeply sloping basins where concentrated overland flow feeds an ephemeral channel incised in slope deposits. Such geological conditions are typical of the Dolomite region (Italian Alps), which is characterized by widespread debris flow activity triggered by severe summer thunderstorms. Real-time data and field observations for one of these catchments (Acquabona catchment, Belluno, Italian Alps) were used to characterize the hydrological response of the initiation area to rainfalls of varying intensity and duration. The observed behaviour was then reproduced by means of a simple hydrological model, based on the kinematic wave assumption, to simulate the generation of channel runoff. The model is capable of predicting the observed hydrological response for a wide range of rainfall impulses, thus providing a physical basis for the understanding of the debris flow triggering threshold.

We monitored positive pore water pressure in a clay slope in the Apennines to investigate how rainfall influences the pore pressure distribution along the soil profile and, consequently, affects slope stability conditions. Data refers to the first season of monitoring activities (August 2001–June 2002). The study site is located at the head of a complex landslide, where incipient shallow failures are visible along the slope. The preliminary analysis of pressure data allowed to point out consistent trends, which manifested throughout 11 months. During the cold and wet season, saturation always extends close to the ground surface ( < 1 m) and pore water pressure measurements indicate a strong downward component of the flow, which is largely dominant over the downslope component, in any condition. Response to rainfalls at shallow depth (1 to 3 m) generally consists in a pressure pulse whose delay is relatively short if compared to low permeability of the soil and whose nature appears clearly transient. Although no failure occurred along the slope during the observation period, it is very likely such transient response would mimic the pore water pressure pattern capable to cause sliding. The presence of prefertial flow path in the sub-surface can only explain anomalous response of some sensors or substantial differences between buried at similar depths.

During intense rainstorms, runoff plays a major role in triggering debris flows in the Dolomite region of Italy. Here the landscape is dominated by steep dolomite massifs where rainfall rapidly concentrates in steep headwater catchments. Debris flow channels originate at the outlet of headwater catchments and erode thick talus deposits delivering sediments to the fan. Headwater catchments are typically very steep (45°-60° on the average) and mostly consist of exposed bedrock with no vegetation and sparse to none soil cover. Debris flows occur in the summer season during short and intense thunderstorms. In order to gain a better understanding of debris flow initiation by surface water runoff, we monitored rainfalls and pore pressures in the source area of a small catchment. We also obtained video footage of surface runoff and debris flow initiation from two cameras. Observations show that incoming water infiltrates in highly porous channel bed debris flowing downstream as subsurface stormflow. Only when increasing discharge exceeds the capacity of the channel bed, surface flow appears and debris flows are triggered by progressive erosion. Although we don’t have a measure of water discharge, we can distinguish three types of hydrologic response in the initiation area: subsurface runoff; surface runoff and debris flow occurrence. Data are sufficient to empirically define the debris flow rainfall triggering threshold in the duration-intensity space. By analyzing type and timing of the response in relation to rainfall forcing, we can calibrate a simple hydrologic model based on SCS method to reproduce our observations. The model is well suited to describe the empirical rainfall triggering threshold. Even more simple estimates of concentration time and initial loss would be sufficient to explain the fundamental processes ruling the shape and slope of the rainfall threshold. The relative simplicity of the mechanisms at the base of the hydrologic response of debris flow catchments in the Dolomites suggests that a regionalization of debris flow rainfall threshold should be possible.

We present an InSAR analysis of slow moving landslide in the Northern Appennines, Italy, and assess the dependencies on the choice of DEM. In recent years, advanced processing techniques for synthetic aperture radar interferometry (InSAR) have been applied to measure slope movements. The persistent scatterers (PS-InSAR) approach is probably the most widely used and some codes are now available in the public domain. The Stanford method of Persistent Scatterers (StamPS) has been successfully used to analyze landslide areas. One problematic step in the processing chain is the choice of an external DEM that is used to model and remove the topographic phase in a series of interferograms in order to obtain the phase contribution caused by surface deformation. The choice is not trivial, because the PS InSAR results differ significantly in terms of PS identification, positioning, and the resulting deformation signal. We use four different DEMs to process a set of 18 ASAR (Envisat) scenes over a mountain area (~350 km2) of the Northern Appennines of Italy, using StamPS. Slow-moving landslides control the evolution of the landscape and cover approximately 30% of the territory. Our focus in this presentation is to evaluate the influence of DEM resolution and accuracy by comparing PS-InSAR results. On an areal basis, we perform a statistical analysis of displacement time-series to make the comparison. We also consider two case studies to illustrate the differences in terms of PS identification, number and estimated displacements. It is clearly shown that DEM accuracy positively influences the number of PS, while line-of-sight rates differ from case to case and can result in deformation signals that are difficult to interpret. We also take advantage of statistical tools to analyze the obtained time-series datasets for the whole study area. Results indicate differences in the style and amount of displacement that can be related to the accuracy of the employed DEM.