Landslide 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.

In this work, we apply a physically based model, namely the HIRESSS (HIgh REsolution Slope Stability Simulator) model, to forecast the occurrence of shallow landslides at the regional scale. HIRESSS is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions during a rainfall event. The modeling software is made up of two parts: hydrological and geotechnical. The hydrological model is based on an analytical solution from an approximated form of the Richards equation, while the geotechnical stability model is based on an infinite slope model that takes the unsaturated soil condition into account. The test area is a portion of the Aosta Valley region, located in the northwest of the Alpine mountain chain. The geomorphology of the region is characterized by steep slopes with elevations ranging from 400 m a.s.l. on the Dora Baltea River's floodplain to 4810 m a.s.l. at Mont Blanc. In the study area, the mean annual precipitation is about 800–900 mm. These features make the territory very prone to landslides, mainly shallow rapid landslides and rockfalls. In order to apply the model and to increase its reliability, an in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslide formation was conducted. In particular, two campaigns of on site measurements and laboratory experiments were performed using 12 survey points. The data collected contributed to the generation of an input map of parameters for the HIRESSS model. In order to consider the effect of vegetation on slope stability, the soil reinforcement due to the presence of roots was also taken into account; this was done based on vegetation maps and literature values of root cohesion. The model was applied using back analysis for two past events that affected the Aosta Valley region between 2008 and 2009, triggering several fast shallow landslides. The validation of the results, carried out using a database of past landslides, provided good results and a good prediction accuracy for the HIRESSS model from both a temporal and spatial point of view.

A variety of methods (detailed geomorphological surveys, geotechnical investigations, local instrumentation, satellite data, and radar interferometry) along with geophysical techniques may be used to investigate slope instabilities and to detect the inhomogeneities of materials as well as their properties, boundaries, and sliding surfaces. Of these techniques, the method based on seismic noise measurements allows abrupt changes in seismic impedance at landslide boundaries resulting from varying levels of seismic velocity and material density to be detected. Peaks of the Horizontal to Vertical Spectral Ratio have proven to serve as effective indicators of the resonance frequency of low-impedance surface layers. In this work, horizontal to vertical spectral ratio surveys of the Castagnola (La Spezia, Italy) and Roccalbegna (Grosseto, Italy) landslides were carried out. From roughly 100 single-station measurements made inside and outside the landslides at each site, we define a threshold number of single-station seismic noise measures beyond which information is redundant because the variation in reconstructed impedance contrast surfaces is not significant. This approach allows one to reliably retrieve the geometry of a landslide body, ultimately generating useful information for determining whether further measurements are needed to improve landslide body reconstruction

In this study, the main focus is the application and improvement of four empirical models, which account for the pyroclastic cover deposit thickness (PCDT) spatial distribution with respect to the bedrock surrounding the Somma‐Vesuvius volcano (Campania, southern Italy). Three models, which are already known in the literature, link the depth to bedrock to the morphological features of a slope. An original model called SEPT (slope exponential pyroclastic thickness) is presented in this manuscript and combines the initial total thickness of ash‐fall pyroclastic cover with the slope gradient. All models were applied and validated using field measurements derived from this and preceding studies in the study area.The main finding is that the spatial distribution of the depth to bedrock in mountainous peri‐volcanic areas mainly depends on the initial thickness of air‐fallen material at a given position and slope angle. These findings allowed for the recognition of an ash‐fall pyroclastic depositional environment that is characterized by different processes from those existing in other geomorphological frameworks and in which the soil thickness along the slopes is controlled by the weathering of bedrock and the formation of soil in situ. Finally, in this research, a reliable approach is proposed that is also applicable to other peri‐volcanic areas of the world to assess the spatial distribution of the depth to bedrock, which is a fundamentally important parameter in distributed geomorphologic and hydrologic modeling. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

Three-quarters of the world population suffered natural disasters at least once between 1980 and 2000. Furthermore, last years' chronicles showed us several geological events that repededly affected urban landscapes. As a consequence beside the loss of human lives and environmental degradation, lots of students were excluded from school, many of whom never to return. Natural hazards have physical, educational, economic and psychosocial impacts. Nowadays it is well ascertained that to decrease this impact by means of structural interventions requires considerable economic resources. Nevertheless, the comparision consequences of similar events in different contexts, it emerges that risk awareness of the population and education to emergency procedures have a positive impact on the occurrence of victims. It follows that the ability of school occupants exposed to hazards to resist and recover from the effects of a hazard in a timely and efficient manner plays a key role to reduce risk, moreover resulting in a cheaper and faster strategy of intervention.This paper presents a new cost-effective methodology and procedure to rapidly assess the geohazard safety classification (GSC) of schools and provides useful information to local decision makers. The GSC, based on the concepts of hazard, vulnerability and resilience, can be calculated integrating ancillary data by means of rapid and not invasive field surveys and questionnaires distributed to the schools employees. Moreover, it can be easily read and understand since it uses the same type of scale as energy efficiency, to indicate the occupants' safety in case of adverse events related to geo-hydrologic hazards.This new rapid assessment methodology have been tested on 10 schools in Tuscany (Italy) and the present paper shows how the GSC can be strongly affected by the lack of ancillary information or the incompleteness of the Risk Assessment Document as well as the school occupants poor perception of geo-hydrologic risk. However, this limitation is at the same time one of the strengths of the GSC: investing in education is a cost-effective way to increase substantially the GSC