Search

Cultural heritage is one of the most exceptional resources characterizing the Italian territory. Archaeological heritage, i.e., the archaeological sites with different types of archaeological artifacts, strongly contributes to enriching the national and international cultural heritage. Nevertheless, it is constantly exposed to external factors, such as natural deterioration, anthropic impact, and climate-related hazards, which may compromise its conservation. In Italy, many archaeological areas are affected by significant soil settlements that involve a large part of monuments. This paper focuses on the landslide hazard assessment of the archaeological site of Pietrabbondante (Molise region, Italy). The impact of the expected rainfall regimes, according to the EURO-CORDEX projections, on slope stability conditions were evaluated through the application of a physically based model that couples a hydraulic and a mechanical model to evaluate slope stability evolution due to pore pressure changes. Given the unavoidable lack of knowledge of the geotechnical soil properties in an archaeological heritage area, the proposed method considered the random uncertainty of soil parameters by means of a probabilistic approach in order to assess the stability conditions in terms of probability of occurrence of a landslide. The results of this study provide a reference for the safety assessment and preventive conservation of archaeological areas characterized by high cultural value. [ABSTRACT FROM AUTHOR]

Transferability of knowledge from well-investigated areas to a new study region is gaining importance in landslide hazard research. Considering the time-consuming compilation of landslide inventories as a prerequisite for landslide susceptibility mapping, model transferability can be key to making hazard-related information available to stakeholders in a timely manner. In this paper, we compare and combine two important transfer-learning strategies for landslide susceptibility modeling: case-based reasoning (CBR) and domain adaptation (DA). Care-based reasoning gathers knowledge from previous similar situations (source areas) and applies it to solve a new problem (target area). Domain adaptation, which is widely used in computer vision, selects data from a source area that has a similar distribution to the target area. We assess the performances of single- and multiple-source CBR, DA, and CBR–DA strategies to train and combine landslide susceptibility models using generalized additive models (GAMs) for 10 study areas with various resolutions (1, 10, and 25 m) located in Austria, Ecuador, and Italy. The performance evaluation shows that CBR and combined CBR–DA based on our proposed similarity criterion were able to achieve performances comparable to benchmark models trained in the target area itself. Particularly the CBR strategies yielded favorable results in both single- and multi-source strategies. Although DA tended to have overall lower performances than CBR, it had promising results in scenarios where the source–target similarity was low. We recommend that future transfer-learning research for landslide susceptibility modeling can build on the similarity criterion we used, as it successfully helped to transfer landslide susceptibility models by identifying suitable source regions for model training. [ABSTRACT FROM AUTHOR]

Transferability of knowledge from well-investigated areas to a new study region is gaining importance in landslide hazard research. Considering the time-consuming compilation of landslide inventories as a prerequisite for landslide susceptibility mapping, model transferability can be key to making hazard-related information available to stakeholders in a timely manner. In this paper, we compare and combine two important transfer-learning strategies for landslide susceptibility modelling: case-based reasoning (CBR) and domain adaptation (DA). CBR gathers knowledge from previous similar situations (source areas) and applies it to solve a new problem (target area). DA, which is widely used in computer vision, selects data from a source area that has a similar distribution to the target area. We assess the performances of single- and multiple-source CBR, DA and CBR-DA strategies to train and combine landslide susceptibility models using generalized additive models (GAMs) for 10 study areas with various resolutions (1 m, 10 m and 25 m) located in Austria, Ecuador, and Italy. The performance evaluation shows that CBR and combined CBR-DA based on our proposed similarity criterion was able to achieve performances comparable to benchmark models trained in the target area itself. Particularly the CBR strategies yielded favourable results in both single- and multi-source strategies. DA tended to have overall lower performances than CBR; yet, it had promising results in scenarios when the source-target similarity was low. We recommend that future transfer learning research for landslide susceptibility modelling can build on the similarity criterion we used, as it successfully helped to achieve landslide susceptibility model transfers by discovering suitable training datasets from various regions. [ABSTRACT FROM AUTHOR]

Recent events, including the floods in central Europe in May 2021, have highlighted how climate change is giving rise to scenarios that were neither foreseen nor predictable. One problem this poses is the need to rethink the logic of various environmental constraints that are often based on return times of 20-50 years or 100-200. A single event does not change the statistical expectations for the recurrence of the event itself, but the recurrence of several extraordinary events in a few years is a clear indication of a changing trend. The prevention of the effects of such events is based on the definition of the areas at greater or lesser risk specifically based on the return times of the exceptional events, so it is foreseeable that a series of territorial plans, mostly carried out a few decades ago, will have to be updated or re-executed from scratch. These reworkings will be able to take advantage of the opensource software and open spatial data that have become available in the meantime, facilitating the entire process, and making it more open and shareable. In this paper we tested on a real case (the May 1999 pyroclastic flows in Campania, southern Italy) the actual possibility of implementing a model for forecasting such events using only open-source software and open data. It has been demonstrated that the entire process can be carried out using only open-source resources and it has been verified that the predictions of the hazard and risk model obtained with only input data prior to the event, give an output prediction that is significantly coincident with the events that actually occurred as documented by the authorities. [ABSTRACT FROM AUTHOR]

Starting on 24th August 2016, Central Italy was struck by a six-month earthquake sequence that caused 303 victims and extensive major damages to urban areas and infrastructures, in some cases entire villages needed complete rebuilding. In this paper we present a map that portrays the overall susceptibility to multiple landslide types and the exposure to landslides of the rural-urban areas of the Castelsantangelo sul Nera Municipality, a typical village of the central Italian Apennine. The map is based on a procedure that ingests geomorphological data and models and groups the individual landslide susceptibility maps in a joint susceptibility and exposure map based on expert-defined criteria. The procedure has been applied to built-up and to undeveloped areas to highlight their exposure and was used as a tool for planning post-seismic reconstruction. We advise that such maps are used also as basic tool for ordinary urban planning. [ABSTRACT FROM AUTHOR]

Starting on 24th August 2016, Central Italy was struck by a six-month earthquake sequence that caused 303 victims and extensive major damages to urban areas and infrastructures, in some cases entire villages needed complete rebuilding. In this paper we present a map that portrays the overall susceptibility to multiple landslide types and the exposure to landslides of the rural-urban areas of the Castelsantangelo sul Nera Municipality, a typical village of the central Italian Apennine. The map is based on a procedure that ingests geomorphological data and models and groups the individual landslide susceptibility maps in a joint susceptibility and exposure map based on expert-defined criteria. The procedure has been applied to built-up and to undeveloped areas to highlight their exposure and was used as a tool for planning post-seismic reconstruction. We advise that such maps are used also as basic tool for ordinary urban planning. [ABSTRACT FROM AUTHOR]

Abstract: In this paper all the phases for the realization of the early warning system for the rockslide of Torgiovannetto in Central Italy are described. The landslide consists in a 182,000m3 rock wedge threatening two roads which are important for local transportation. The present work encompasses all the components of an early warning system, including the geological knowledge, the risk scenarios, the kinematic characterization of the landslide, the choice and installation of the monitoring system, the setting of appropriate alarm levels and the definition of plans of civil protection. The focus is on practical and logistical issues met in all these phases and the counter-measures adopted. At present the system consists in 13 wire extensometers, 1 thermometer, 1 rain gauge and 3 cameras. Should a velocity threshold be exceeded by two or more sensors, the attention level would be entered, causing improved monitoring and surveillance. In case the behavior of the landslide changes and, by using expert judgment and forecasting methods, an imminent failure is hinted, then an alarm is issued and the upper road is closed. This paper can provide ideas and solutions for a landslide early warning system that aims to be simple, flexible, versatile and with a low probability of giving false alarms. [Copyright &y& Elsevier]

Landslide geodatabases, including inventories and thematic data, today are fundamental tools for national and/or local authorities in susceptibility, hazard and risk management. A well organized landslide geo-database contains different kinds of data such as past information (landslide inventory maps), ancillary data and updated remote sensing (space-borne and ground based) data, which can be integrated in order to produce landslide susceptibility maps, updated landslide inventory maps and hazard and risk assessment maps. Italy is strongly affected by landslide phenomena which cause victims and significant economic damage to buildings and infrastructure, loss of productive soils and pasture lands. In particular, the Messina Province (southern Italy) represents an area where landslides are recurrent and characterized by high magnitude, due to several predisposing factors (e.g. morphology, land use, lithologies) and different triggering mechanisms (meteorological conditions, seismicity, active tectonics and volcanic activity). For this area, a geodatabase was created by using different monitoring techniques, including remote sensing (e.g. SAR satellite ERS1/2, ENVISAT, RADARSAT-1, TerraSAR-X, COSMO-SkyMed) data, and in situ measurements (e.g. GBInSAR, damage assessment). In this paper a complete landslide geodatabase of the Messina Province, designed following the requirements of the local and national Civil Protection authorities, is presented. This geo-database was used to produce maps (e.g. susceptibility, ground deformation velocities, damage assessment, risk zonation) which today are constantly used by the Civil Protection authorities to manage the landslide hazard of the Messina Province. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this paper is to analyze the reactivation mechanism of ancient earth flows, with a view to gleaning information that can subsequently be utilized to formulate a risk-reduction strategy. All considerations made herein are the result of direct experience and observation of actual events which have occurred over the past few decades in the Northern Apennines. Particular attention has been paid to the analysis of the evolution of landslides during actual reactivation, acknowledging a typical, recurring succession of events that precede the failure of the slope. The hazard assessment of these large landslide bodies, which are of slope scale, constitutes a thorny problem, especially in view of the inapplicability of traditional deterministic models such as limit equilibrium stability analysis. Nevertheless, a site-specific assessment of probability of reactivation of these large and ancient earth flows is fundamental to effective land-use planning. [Copyright &y& Elsevier]

Recent research in Umbria, Italy, has shown that landslide susceptibility is controlled by a process called path-dependency, which describes how past landslides control the locations of future landslides. To date, landslide path-dependency has only been characterised in Italy. This raises the question of whether this process occurs in other geomorphic settings, and thus whether path-dependency should be more universally included in landslide susceptibility assessments. Therefore, the main aim of this paper is to investigate and quantify landslide path dependency in the Nepal Himalaya. This is achieved by applying several path dependent metrics to three monsoon-triggered landslide inventories for the central-eastern Nepal Himalaya. These inventories were developed at two different spatial and temporal resolutions. As such, we aim not just to quantify landslide path-dependency, but also to assess whether path dependency characteristics are resolution-dependent. We find strong evidence that landslide path dependency is occurring in Nepal, with all three inventories having more overlap between past and new landslides than expected from a random distribution, and a tentative observation that the expected degree of overlap between landslides decreases with time. Finally, whilst path-dependency is observable across both of the investigated inventory resolutions, we find that the rates and magnitudes of the quantified path dependent metrics are sensitive to inventory length, study region size and the size/type of landslides mapped. Overall, our results corroborate the path-dependency observations from Italy, confirming that this process does occur in other geomorphic settings, and thus suggesting that path-dependency should be explicitly and universally considered in landslide susceptibility approaches. [ABSTRACT FROM AUTHOR]

The growing volume of synthetic aperture radar (SAR) imagery acquired by satellite constellations creates novel opportunities and opens new challenges for interferometric SAR (InSAR) applications to observe Earth's surface processes and geohazards. In this paper, the Parallel Small BAseline Subset (P-SBAS) advanced InSAR processing chain running on the Geohazards Exploitation Platform (GEP) is trialed to process two unprecedentedly big stacks of Copernicus Sentinel-1 C-band SAR images acquired in 2014–2020 over a coastal study area in southern Italy, including 296 and 283 scenes in ascending and descending mode, respectively. Each stack was processed in the GEP in less than 3 days, from input SAR data retrieval via repositories, up to generation of the output P-SBAS datasets of coherent targets and their displacement histories. Use-cases of long-term monitoring of land subsidence at the Capo Colonna promontory (up −2.3 cm/year vertical and −1.0 cm/year east–west rate), slow-moving landslides and erosion landforms, and deformation at modern coastal protection infrastructure in the city of Crotone are used to: (i) showcase the type and precision of deformation products outputting from P-SBAS processing of big data, and the derivable key information to support value-adding and geological interpretation; and (ii) discuss potential and challenges of big data processing using cloud/grid infrastructure. [ABSTRACT FROM AUTHOR]

Pyroclastic soils are widespread in the world. In particular, they cover a great part of Campania, a densely populated country of Southern Italy, where some distinct volcanic centers are present. In these soils, precipitations can trigger fast flow-like landslides causing destruction and loss of human lives. The movement style, the high velocity and the long run-out of these landslides are an indication of the occurrence, in the saturated soil mass, of mechanisms of undrained instability due to the inability of soil to sustain the deviator stress related to the slope condition. This paper reports the results of a wide experimental laboratory program carried out on a volcanic ash, which recently has been the seat of a killer landslide, stressing the factors that govern the undrained response of these materials. [ABSTRACT FROM AUTHOR]

In this paper, the preliminary results of an integrated geomorphological study carried out in a 1.6 ha catchment area located on the eastern side of the Crati River valley (northern Calabria, South Italy) have been presented. An orthophoto and shaded relief map of the study catchment, obtained by 288 unmanned aerial vehicle (UAV) images, integrated with field geomorphological surveys have been used to produce a detailed map of landslides and water erosion phenomena. The study area is characterized by active morphodynamic processes that result in the occurrence of water erosion phenomena and several landslides. In particular, 29 slides and 37 earth slides that evolve into earth flows have been recognized. Spatial and temporal development of geomorphic processes (erosion/depletion and sedimentation/accumulation) have affected the catchment area in the last seven years. Indeed, the comparison between light detection and ranging digital terrain models (LiDAR-DTM) of 2012 and UAV-DTM of 2019 showed depletion values between −0.01 and −5.76 m, with a mean value of −0.96 m; whereas for the accumulation the mean value is 0.94 m, with a maximum thickness of the deposited material of about 2.98 m. The results obtained highlight the usefulness of the methodology to provide detailed information on geomorphic processes and related short-term landscape development in a small drainage basin. [ABSTRACT FROM AUTHOR]

Shallow flowslides, debris flows and debris avalanches are rainfall-induced landslides consisting in the shear failure of few metres of soils (or in some cases even less than a metre), which greatly increase downslope in volume and flow velocity. The southern Italian region of Campania has been historically affected by such events involving pyroclastic soils mainly resting on steep carbonate slopes. This paper deals with the analysis of factors influencing the occurrence of flow-like landslides, adopting the Lattari Mts. in Campania as a case study. The results of two investigation campaigns carried out in the area allowed effective large-scale geological and geotechnical characterization to be set up. Stratigraphic profiles, mean physical properties and typical friction angles at the critical state for each soil layer were investigated. The effect of suction on peak and critical shear strength, whose drop is responsible for soil failure, was analysed. Using detailed information on both the stratigraphic and geotechnical features of the soils involved in past flow-like landslides, typical triggering models were selected, representing locally recurrent geomorphologic conditions at the basin scale. The identified models were adopted for slope stability analyses carried out on four cross-sections of flowslides occurring prior to the event, to back-analyse the triggering conditions. From the evidence on the triggering mechanisms and the results of analyses, the infinite slope approach is not always suitable to model slope stability conditions properly, because the onset of landslides is also affected by local topographic and stratigraphic factors. • Flow-like landslides can be triggered due to local features. • Local topographic irregularities can be represented by roads, tracks, scarps and terraces. • Infinite slope model can be suitable to model only slopes characterized by angles higher than 39–40°. • Local natural and anthropic factors can affect the results of slope stability analysis. • The triggered landslides occurred when the 3-months precedent rainfall exceeded the 40 years average value. [ABSTRACT FROM AUTHOR]