Landslides are heterogeneous natural processes. Given the significant variability of the different landslide types and in particular of their dimensional characteristics, style of movement and triggering mechanisms, multiple models and approaches have been developed in the literature. At present, no single model or modelling approach is applicable to all the different landslide types. This also limits the prediction of the spatial occurrence of landslides achieved through susceptibility models which aims at estimating the probability of the spatial landslide occurrence. Such models divide and classify a territory on the basis of its propensity to specific landslide types, using relationships linking the occurrence of landslides with their conditioning factors. In this work, we identify and apply a methodology for the combined modelling of susceptibility posed by different landslide types. The methodology initially envisages the modelling of the susceptibility for the individual landslide types using differentiated approaches, calibration, evaluation and application phases and subsequently their combination. In the modelling, the pixel is used as the base mapping unit, while the slope unit is used as a mapping unit for a subsequent spatial susceptibility aggregation. The result maps, here defined as "composite susceptibility maps", subdivide a territory according to its propensity to failure of one or more landslide types. The proposed model was applied as part of the Project "Paesaggi Sicuri", funded by the Italian Ministry of Cultural Heritages and Activities (MIBACT), in a portion of the UNESCO site "Porto Venere, Cinque Terre e Isole" characterized by the occurrence of different landslides types, namely slides, falls and flows. The derived composite susceptibility map allowed a more realistic analysis of the geo-hydrological vulnerability being able to consider jointly the different landslides types occurring in the study area.

As prioritized by the Sendai Framework, enhancing disaster preparedness is fundamental for the effective response, for taking actions in anticipation of events, and to ensure that the appropriate capacities are in place for effective response and recovery at all levels. Under this view early warning systems can be seen as irreplaceable tools to supporting the Civil Protection authorities in the preparedness and response phases. This is particularly relevant for the case of rainfall-induced slope failures that occur worldwide every year, claiming lives and causing severe economic disruption. Implementing early warning systems to forecast the occurrence of such geo-hydrological phenomena is difficult and challenging both from the scientific and technological side. Here we present a framework developed in Italy (Rossi et al., 2012) for the operation forecasting of rainfall induce landslides over large areas, which includes (i) criteria, tools and technological supports for the collection of rainfall induced landslide occurrences; (ii) scientific methods and tools for the analysis of the relation between rainfall and landslides occurrences and for the landslide rainfall threshold definition; (iii) operational early warning system procedures and technological supports for the rainfall induced landslide forecasting; (iv) interfaces for the query and analysis of the early warning system outputs; (v) criteria, tools and technological supports for the validation of the early warning system outputs. The main lessons learned in the last decade and the most critical issues experienced implementing such framework for the entire Italian territory (SANF system) and for different regions both in Italy and India (SARF systems, LANDSLIP LEWS system) are highlighted and discussed.

Landslides cause every year worldwide severe damages to the population. A quantitative knowledge of the impact of landsliding phenomena on the society is fundamental for a proper and accurate assessment of the risk posed by such natural hazards. In this work, a novel approach is proposed to evaluate the spatial and the temporal distribution of societal landslide risk from historical, sparse, point information on fatal landslides and their direct human consequence.s (Rossi et al., Accepted). The approach was tested in Italy, using a detailed catalogue listing 5571 fatalities caused by 1017 landslides at 958 sites across Italy, in the 155-year period 1861 - 2015. The model adopting a Zipf distribution to evaluate societal landslide risk for the whole of Italy, and for seven physiographic and 20 administrative subdivisions of Italy. The model is able to provide estimates of the frequency (and the probability) of fatal landslides, based on the parameters, namely (i) the largest magnitude landslide F, (ii) the number of fatal events E, and (iii) the scaling exponent of the Zipf distribution s, which controls the relative proportion of low vs. large magnitude landslides. Different grid spacings, g and circular kernel sizes, r were tested finally adopting g = 10 km and r = 55 km. Using such geometrical model configuration, the values of the F, E and s parameters were derived for each grid cells revealing the complexity of landslide risk in Italy, which cannot be described properly with a single set of such parameters. Based on such modeling configuration. This model configuration allowed to estimate different risk scenarios for landslides of increasing magnitudes, which were validated checking the anticipated return period of the fatal events against information on 130 fatal landslides between 1000 and 1860, and eleven fatal landslides between January 2016 and August 2018. Despite incompleteness in the old part of the record for the low magnitude landslides, and the short length and limited number of events in the recent period 2016 - 2018, the anticipated return periods are in good agreement with the occurrence of fatal landslides in both validation periods. Despite the known difficulty in modelling sparse datasets, the proposed approach was able to provide a coherent and realistic representation and new insight on the spatial and temporal variations of societal landslide risk in Italy.

The Italian territory is affected by rainfall-induced landslides, which can result in loss of lives and widespread damage. Empirical rainfall thresholds are widely used for predicting the occurrence of failures triggered by intense or prolonged rainfall at national and regional scale, even if they have empirical limitations for small geographical areas. This limitations depend on the size of the landslide catalogue available for the definition of statistically robust rainfall threshold over small areas (Peruccacci et al. 2012). Martinotti et al. 2017 theorized, designed and tested the Ensemble-Non-Exceedance Probability (E-NEP) algorithm, which exploits standard rainfall records obtained from rain gauges and a given rainfall threshold to quantitatively assess the landslide occurrence probability over time. Using the rainfall threshold defined by Peruccacci et al. 2017 for the entire Italian territory, they applied the E-NEP algorithm to analyse the landslides triggered during a time period of torrential rain between 1 and 6 September 2014 in the Gargano Promontory (Puglia) and found that the E-NEP metrics provided better diagnostics than the single metrics often used for landslide forecasting.

Effective infiltration (EI) is the amount of precipitation infiltrating into the soil and recharging the aquifers. EI is estimated using direct or indirect methods or using water balance models. Direct and indirect methods lead to biased EI estimates, since based on simplified schemas of groundwater bodies and of their recharge mechanisms. Water balance models include different processes and variables, but they are seldom applied due to the limited availability of the input data, particularly at regional scales. We propose a method for EI estimation over large areas based on a monthly water balance model exploiting open source software and free/open data. The model integrates procedures to estimate EI and other water balance components, accounting for the uncertainty of input data. The model is calibrated in the Central Apennines (Italy), where EI reference values are available from the literature, and later applied in the Alps, where regional EI estimates are missing.

As prioritized by the Sendai Framework, enhancing disaster preparedness is fundamental for the effective response, for taking actions in anticipation of events, and to ensure that the appropriate capacities are in place for effective response and recovery at all levels. Under this view early warning systems can be seen as irreplaceable tools to supporting the Civil Protection authorities in the preparedness and response phases. This is particularly relevant for the case of rainfall-induced slope failures that occur worldwide every year, claiming lives and causing severe economic disruption. Implementing early warning systems to forecast the occurrence of such geo-hydrological phenomena is difficult and challenging both from the scientific and technological side. Here we present a framework developed in Italy for the operation forecasting of rainfall induce landslides over large areas, which includes (i) criteria, tools and technological supports for the collection of rainfall induced landslide occurrences; (ii) scientific methods and tools for the analysis of the relation between rainfall and landslides occurrences and for the landslide rainfall threshold definition; (iii) operational early warning system procedures and technological supports for the rainfall induced landslide forecasting; (iv) interfaces for the query and analysis of the early warning system outputs; (v) criteria, tools and technological supports for the validation of the early warning system outputs. The main lessons learned in the last decade and the most critical issues experienced implementing such framework for the entire Italian territory (SANF system) and for different regions both in Italy and India (SARF systems, LANDSLIP LEWS system) are highlighted and discussed.

Gully erosion is a significant geo-hydrological phenomenon occurring worldwide. Such phenomena contribute significantly to the soil erosion on a catchment and to its morphological shaping. In so doing, it impacts all the processes acting in a hillslope. Being one of the principal processes of soil erosion, gully erosion will play an important role in worsening the effects of climate and land use changes in the near future. Therefore, the prediction of the spatial and temporal occurrence of these phenomena is an interesting problem both for the scientific world and more in general for the society. In this work we model gully erosion on different study areas, using a distributed pixel-based model. The LANDPLANER model was used for the purpose, mainly due to its ability to deal with scenario-based analysis and due to the limited requirements of input data in its basic configuration, which include a DEM and a land cover map to derive the parameters of the runoff through the Curve Nuumber method. The twofold erosion modelling schema integrated in LANDPLANER, namely a quasi-static topographic threshold approach and a dynamic simplified erosion index, were tested in some study areas, considering the local morphological, climatological and Land Use/Land Cover conditions. We propose a framework to derive such dynamical model input data to better characterize the spatial and temporal occurrence of gully phenomena. Open source (SENTINEL-2) and commercial satellite (WorldView 3) data are used for the purpose and with the main objectives to perform long term, seasonal, event and scenario-based modelling analyses. Modelling results were validated using geomorphological and gully phenomena inventories, using different spatial criteria and different performance metrics. We maintain that the tested modelling and validation approaches can be easily replicated and applied in other different study areas to better characterize the spatial and temporal occurrence of gully erosion phenomena.

The prediction of the location of gully heads in various environments is an important step towards predicting slope and catchment dynamics and to properly estimate soil erosion rates. So far, data collection and modelling of topographic thresholds for gully head prediction has mainly focused on forested areas, rangelands, pastures and cropland. However, such data for badlands are very scarce, even if such environments are most interesting to study gully processes, resulting from the complex interaction between soil degradation and erosion, and soil building processes. In this study we extend the database on topographical thresholds for gully head formation through data collection in badland areas and to improve the prediction of gully head development in a given landscape. For this purpose, we selected different badland sites in the Mediterranean that are characterized by different badland morphologies that developed in differed geo-environmental conditions. The analysis of the conditions under which gully heads developed allowed to refine a recently reported gully head threshold equation, and to illustrate how to use the updated model. This model shows that the resistance to gully head formation depends on slope gradient and drainage area at gully heads, land use in the gully catchment at the moment of gully development (expressed numerically by parameters derived from the Runoff Curve Number method), surface rock fragment cover, presence of joints, pipes, and factors/processes affecting soil detachment rate. This study improves our understanding of environmental conditions that control the development of gully heads in various badland types through a combination of field data collection of gully heads and modelling.

The Mediterranean region has been identified as one of the main climate change hotspots_ its sensitivity to global change is high and its evolution remains uncertain. The region experiences many interactions and feedbacks at the oceanic, atmospheric, and hydrological levels, while facing high anthropogenic activities. Analysing the water cycle over the Mediterranean region is of major importance to environmental and socio-economic aspects. The satellite monitoring of the Mediterranean water cycle represents one of the key challenges for the hydrological community. The presentation will show recent results on using satellite soil moisture and precipitation products for hydrometeorological prediction in the Mediterranean region, and particularly for the prediction of floods and landslides. Specifically, we will show the comparison of multiple satellite precipitation products for predicting flood in 100+ basins over the Mediterranean Basin by also using different hydrological models. Moreover, the assessment of satellite precipitation products for predicting the occurrence of landslides in Italy is carried out. Among the investigated satellite products, we have firstly considered state-of-the-art products such as TMPA (TRMM Multisatellite Precipitation Analysis), GPM (Global Precipitation Measurement), and H SAF (EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management). Secondly, we have tested the innovative products using the SM2RAIN algorithm for rainfall retrieval from multiple satellite soil moisture products including ASCAT (Advanced SCATterometer), SMOS (Soil Moisture and Ocean Salinity mission) and SMAP (Soil Moisture Active and Passive mission).

The definition of empirical rainfall thresholds for the prediction of landslide occurrence is conditioned by several issues. The most debated ones are_ the definition of objective and automatic procedures for threshold calculation; the evaluation and quantification of diverse uncertainties resulting from data and methods; the definition of validation procedures; the implementation of thresholds into landslide early warning systems. However, threshold reliability strongly depends on the quality and quantity of input data, e.g. rainfall time series and information on landslide occurrence. In particular, the temporal resolution of rainfall data influences the equation, the shape and the validity range of the thresholds. Recent studies have proved that the use of rainfall data with coarse temporal resolution causes a systematic underestimation of thresholds, due to the overestimation of the duration of the rainfall events responsible for the failures. Moreover, thresholds calculated using daily rainfall data are always lower and steeper than those defined with hourly data. These issues have relevant implications when the thresholds are implemented in warning systems for the operative prediction of landslide occurrence. In this work, we analyse how the rainfall temporal resolution influences the definition of rainfall thresholds, their validation and the uncertainty associated with them. For the purpose, we use hourly rainfall measurements collected by a network of 172 rain gauges and geographical and temporal information on 561 rainfall-induced landslides occurred in Liguria region (northern Italy) between October 2004 and November 2014. We use a comprehensive tool, already published, that automatically reconstructs the rainfall conditions responsible for the failures and calculates frequentist cumulated event rainfall-rainfall duration (ED) thresholds. To evaluate the influence of different temporal resolutions we cluster the rainfall data in different, increasing bins of 1, 3, 6, 12, and 24 hours (representing decreasing temporal resolutions). We apply the automatic tool to reconstruct rainfall conditions responsible for failures and to define ED thresholds. We find that the rainfall temporal resolution influences considerably the threshold definition. In particular, decreasing the rainfall temporal resolution, we obtain thresholds with a smaller intercept, a higher slope, a shorter range of validity, and higher uncertainties. On the other hand, it seems that the rainfall temporal resolution does not influence the validation procedure and the threshold performance indicators.

The "Sentinelle del Territorio" (Sentinels of territory) project is part of the local Plan for the reduction of geo-hydrological risk in the La Spezia Municipality (Liguria region, northern Italy) and aims at (i) increasing the knowledge of the geo-hydrological hazards and (ii) monitoring, in detail, the building characteristics and vulnerability through the active participation of different actors. The project arises from the awareness that monitoring the territory and increasing knowledge of its critical aspects are preliminary to any following action, structural or not, aimed at risk mitigation. The activities are based on an ongoing collaboration of citizens, municipal technicians, civil protection volunteers, professional associations and IRPI researchers. For the purpose, tools for the collection and management of multiple data regarding the city buildings were designed and different forms, based on the type of geo-hydrological process to which buildings are subject, were structured. To support surveyors, volunteers and municipal technicians the forms were designed to be compiled on paper or through Apps specifically developed for Android and IOS based smartphones. For buildings placed in flood prone areas, different information on the ground and basement floors and on the water drainage system was prioritised. In the landslide susceptible areas, forms contained further fields dedicated to the presence, type and dimension of cracks and on the presence and maintenance of any existing landslide mitigation works. The forms were designed using ODK Aggregate for Android and GISCloud for IOS platforms that allowed the building geo-localization, depending to the smartphone GPS receiver system, and media file association to the building records. After the form filling, data were automatically sent to a dedicated server. Despite the initial efforts spent for the conceptualization of the forms, the use of these technologies resulted very effective and allowed the rapid collection and the quick update of a huge amount of data. Analysis of the collected data provides a general overview of the characteristics of the buildings and of their vulnerability to geo-hydrological processes. The project results reached two main goals_ an up-to-date comprehensive knowledge of the buildings condition and an increase of citizens' awareness on geo-hydrological hazards, involving people in the land management process.

The karst nature of large sectors of Apulia, combined with the high diffusion of different types of artificial cavities, make sinkholes among the most widespread geo-hydrological hazards in the region. They have caused several damage to infrastructures, building and population. Sinkholes represent a widespread problem in Apulia, and therefore they must necessarily be considered in studies concerning the regional geo-hydrological hazards and the related risks. With this aim we included sinkholes in a regional geodatabase concerning floods and landslides in Apulia, as a fundamental step for the susceptibility and hazard study of sinkhole occurrence on the specific territory. At these aims, it is necessary that the database is rigorously built, based on reliable information and data, including all those elements necessary for the subsequent analysis. Here we present a geodatabase about geo-hydrological hazards, developed by the geomorphology group at the Institute of Research for the Geo-Hydrological Protection of the National Research Council of Italy (IRPI-CNR), now modified to take into account the geomorphological characteristics of Apulia, namely the sinkhole phenomena. A sinkhole is considered as a "phenomenon", belongs to an "event" that represent the ensemble of the phenomena (landslides, floods, sinkholes) caused by a "trigger" (of meteorological, seismic, or anthropogenic origin). In the database are included all the sinkholes for which the connection with an underground cavity, either of natural or anthropogenic origin, is certain. In addition, the information on occurrence time of the sinkhole, and knowledge of its location, are fundamental. The geodatabase allows to collect information about different types of geo-hazard (landslide, flood, sinkhole), to record with different geometry (point, line, polygon) both the location of the phenomena and of the damaged objects/mitigation works, to report data in format compliant with the EU Flood Directive (2010), even in the specific format required by the Department of the Italian Civil Protection.

After major geo-hydrological disasters, the rapid detection of both location and extension of the areas struck by floods and landslides is essential to manage recovery operations. In these cases, one of the most important tools required by decision-makers is a georeferenced map showing the affected areas. Preliminary maps reporting the potential location of landslides, for example, may also represents a starting point for field Geologists engaged in the production of detailed event landslides inventories, allowing optimize time and efforts. Optical and radar satellite images are experiencing an increasing use in the emergency operations due to improved revisiting times and spatial resolution. However, optical scenes are often useless for long times because of a permanent cloud cover or shadow effects hiding the collapsed mountain slopes. For this reason, the landslide research community is dedicating more efforts to implement new approaches based on satellite radar data, which typically are not affected by these types of disturbance. Even if the development of landslide inventories from radar images is still a challenge, such data represent a valuable support to generate archives of information acquired systematically, forming therefore clusters of "Big data" that can be useful in the context of susceptibility, hazard, and landslide risk analysis. In the innovative approach presented in this contribution, we faced many of the issues related to the use of satellite radar data for supporting the production of event landslides inventories. The research activities have been carried out in the framework of the STRESS (Strategies, Tools and new data for REsilient Smart Societies) project, devoted to design, implement and test a prototype of a Spatial Data Infrastructure (SDI) to support decision makers in the geo-hydrological risk management. Specifically, our group have implemented an automatic processing chain that, starting from the downloading of Sentinel-1 satellite images, produces a georeferenced map highlighting the likely location of landslides. The procedure exploits multi-temporal variations of the radar backscattered signal induced by significant land cover changes, which can be associated to the occurrence of rapid-moving landslides. This map is sent to local scientists and citizens by means of a Smart App developed to collect, store and analyze Volunteered Geographic Information (VGI), to ease and improve results obtained from satellites. The STRESS project is also aimed at promoting and exploiting VGI freely provided by citizens involved as "human sensors" in the production of landslide inventories, providing direct information if no evidences are available from remote sensing. Outcomes resulting from both remote sensing and VGI activities should thereby support the updating of existing landslides susceptibility models and hazard assessment. The test site of the project is located in the Central Alps (Italy), where the steep slopes are very prone to landslides and debris flow processes. However, a preliminary application of the automatic processing chain has been successfully performed for a wide area of the Papua New Guinea affected by dozens of landslides in 2018, as well as the implementation of the VGI Smart App has been completed and verified.

Validating Natural Hazard (NH) early-warning system (EWS) requires the continuous monitoring of the occurrences of natural hazards, their collection in a data structure and their confrontation with the forecasts produced by the system. Social media streaming is an emerging technology to collect data on landslides occurrence. In particular, the use the Twitter API is consolidating among all the other social media APIs. Continuous data on the occurrence of landslide events can be collected and recorded in a database. Visualization tools can be really useful for EWS validation to display, at the same time, the temporal evolution of the landslide EWS forecasts and the occurrence of the slope failures. The collaboration project between Research Institute for Geo-Hydrological Protection (IRPI), a research institute active in the field of geo-hydrological hazards and the ITTS A. Volta a secondary schools aims to increase the perception and knowledge that students and teachers have on geo-hydrological risk. This is achieved through the development of tools and analysis which allow them to become aware of the phenomenological characteristics of landslides and floods, their impact on the population/environment and the rules of conducts to be followed before, during and after the disasters. The project allows students to work with IRPI data and tools and leads them to develop software applications that can be accessed from the communication devices (personal computers, tablets, smartphones) for the dissemination of content and for understanding the phenomena. The present contribution describes the recent achievements, carried out entirely by six high school student, on the development of_ (i) an automatic system for the detection, filtering, classification, storage and visualization on a web map of the tweets containing information about landslide occurrences, and (ii) a web service for the contemporary visualization of the time streaming of the EWS forecasts and of the landslides occurrences. The work was carried out independently by three group of students with the supervision of the researchers, and carried out according to the following steps_ (i) analysis of the state of the art, (ii) identification of the method for tracking the work done, (iii) identification of the points of contact between the activities of the different groups in order to promote the exchange of knowledge and transversal work. Finally, during a specific divulgation workshop organized at their school, the students presented their work to the colleagues and professors, while the IRPI researchers presented their research activities and disseminated information about geo-hydrological hazards.

Collecting, organizing and using historical information on natural hazards (NH) is crucial for developing methods, systems and procedures aimed at protecting citizens, structures and infrastructures, for planning mitigation actions, and for increasing risk awareness. Information on past events is essential e.g., to update the catalogue of flood events required by the EU Flood Directive, to develop and test empirical rainfall thresholds for landslide occurrence, and to identify areas subject to specific or multiple hazards. LAND-deFeND - LANDslides and Floods National Database, is a freely available database structure designed to collect information about past landslides and floods (geo-hydrological hazards, GHH). The structure is flexible, allowing to_ (i) collect, in a single platform, information on different phenomena (i.e. landslides, floods, sinkholes), (ii) store information on the location of the GHHs, on the damaged sites, and of the remedial / mitigation works, using different types go geometries (i.e. points, lines, polygons), and a to (iii) manage, separately and jointly, the uncertainty inherent to the temporal and the spatial information on the GHHs. In addition, LAND-deFeND is compliant with the EC INSPIRE and Flood Directives. Here we present a new version of the database structure - LAND-deFeND 1.1 - which was recently developed, and we discuss the rationale behind the implementation of new features, including the possibility to (i) collect and store information on sinkholes, (ii) collect and store information on the rainfall event responsible for landslide occurrence, (iii) to store the bounding box of individual meteorological triggers, (iv) to manage information about the warning level issued by civil protection authorities before and during a GHHs, and to (v) produce reports and output / exchange data in formats compliant to the EC Flood Directive, and to the Italian Department for Civil Protection (DPC). The new release of the LAND-deFeND database allows regional civil protection offices to maintain regional GHH databases potentially interoperable at national level.

Exploiting data acquired by different instruments with a 3D visualization is recently becoming a mandatory requirement for a great part of space missions (e.g., [1]). In this context, we adapted MATISSE [2] to the needs of the Moon Mapping project [3], by adding to its database observations and high-order outputs coming from Chang'e 1 and Chang'e 2 (in the following CE1 and CE2, respectively) Chinese missions to the Moon. This task required the development of ad hoc software, able to ingest and spatially (re)project the data, mostly which are mostly formatted compliant to the PDS (Planetary Data System) standard. The possibility of analyzing the data with an effective threedimensional perspective added value to their scientific content and at the same time gave also and easy and "smart" access to the data to non-professional users, which is one of the main target of the Moon Mapping project.

Lunar rilles are any of the long, narrow depressions on the surface of the Moon. These structures have different characteristics, which are related to their origin. Here, a classification of the lunar rilles in different groups with similar morphometric features and likely the same formation mechanisms is proposed. The detection, classification and mapping of lunar rilles has been achieved in two quadrants of the northern hemisphere, which are located between -90°E to 90°E longitude and 0°N to 60°N latitude. For the detection and mapping of rilles, we used images from the Lunar Reconnaissance Orbiter Camera (LROC) [1] which have a resolution of 100 m/pixel and the DEM from Lunar Orbiter Laser Altimeter (LOLA) with a resolution of 6 m/pixel. This work is part of an international cooperation between Italy and China called "Moon Mapping project" for the collaboration between Italian and Chinese college students.

Mass movements are almost ubiquitous in the Solar System, with rockfall, avalanches or landslides that are observed not only on Earth, but also on multiple other bodies. The characteristics of the observed landslides (i.e. type of failure, geometry, velocity, etc.) are strongly influenced by several factors such as the initial mass position, the material and its mechanical properties, the topographic relief and the volatile content. In this work, we identified 26 landslides located on the surface of the comet 67P using OSIRIS Rosetta images. We investigate the landslide shapes and aspect ratios through the use of the high-resolution shape model of 67P. Assuming the height to runout length as an approximation for the friction coefficient of the cometary material, we find that the mapped mass failures behaves thoroughly different from the one observed on other Solar System icy bodies. Indeed, being the 67P high friction coefficients comparable, or even higher, than those found on Earth landslide, they imply a mechanically rocky-type behavior for the cometary material. This makes 67P, and comets in general, very peculiar objects that are mainly composed of ice and organics, but that are characterized by rocky-type properties rather than icy-type characteristics.

Lunar rilles are any of the long, narrow depressions on the surface of the Moon. These structures have different characteristics, which are related to their origin. Here, a classification of the lunar rilles in different groups with similar morphometric features and likely the same formation mechanisms is proposed. The detection, classification and mapping of lunar rilles has been achieved in two quadrants of the northern hemisphere, which are located between -90°E to 90°E longitude and 0°N to 60°N latitude. For the detection and mapping of rilles, we used images from the Lunar Reconnaissance Orbiter Camera (LROC) [1] which have a resolution of 100 m/pixel and the DEM from Lunar Orbiter Laser Altimeter (LOLA) [2] with a resolution of 6 m/pixel. Lunar rilles include generic sinuous rilles (SR), cracks on lava deposits (CL), surface lava flows (LF), subsurface lava tubes or catena (crater chains, CC) and tectonic structures (TS). For each type of the classified structures, morphologic parameters, i.e. length, width, perimeter, area, depth, longitude and latitude have been measured in order to allow a better understanding of how these features formed [3]. For those sinuous rilles classified as remnants of shallow lava channels or subsurface collapsed lava tubes, morphometric analysis included the extraction of the sinuosity index and of the regional slope and azimuth. This work is born inside an international cooperation between Italy and China called "Moon Mapping project" for the cooperation between Italian and Chinese college students [4].

On Earth, landslides occur in various morphological and climatic settings and can strongly affect the evolution of a landscape. On Mars, slope failures have been also observed since decades (e.g., [1], [2]), especially in the large canyons of Valles Marineris. In the perspective of a novel interest in the human settlement on the red planet it is important to explore the local environmental conditions and the possible hazards. For the purpose, we analyzed the geometrical features of landslides on Earth and Mars and compared the relationships between their geometrical parameters (i.e. landslide volumes, areas, drop heights and runout distances). Data for this study were collected using landslide catalogues available from several authors [3, 4, 5, 6, 7]. In particular, we selected rock and debris slides, rock avalanches on Earth and Mars and terrestrial submarine landslides. Having insights on the geometrical properties of the landslides on the two planets might provide tools for the understanding of the sliding mechanisms in different environments.

The Italian territory is highly prone to shallow rainfall-induced landslides. Moreover, a large physiographic, geological and climatic variability characterizes the national landscape. For these reasons - and for the abundance of available rainfall measurements - Italy is an ideal test site to investigate how rainfall conditions that induced shallow landslides may vary in different environmental settings. Since 2007, we have been building a catalogue of rainfall events responsible for the triggering of landslides in Italy. Using accurate landslide information and hourly rainfall data recorded by a network of 2228 rain gauges, we reconstructed 2309 rainfall events that induced 2819 (mostly) shallow landslides in Italy in the period January 1996 - February 2014. We calculated the rainfall duration D (in hours) and the cumulated event rainfall E (in mm) presumably responsible for each failure. Using a well-established frequentist method, we calculated empirical cumulated event rainfall-rainfall duration (ED) thresholds at different non-exceedance probabilities and the uncertainties associated with their parameters. Using the entire dataset, we determined a national threshold representing the rainfall conditions that can likely result in landslides in Italy. By considering six environmental subdivisions based on topography, lithology, soil regions, land cover, climate, and precipitation regime, we defined 26 regional thresholds identifying the rainfall conditions responsible for landslide triggering in different environmental settings in Italy. Overall, the resulting national and environmental thresholds are similar, and cover a small part of the possible DE domain. Nevertheless, thresholds for meteorological domains, which are classified according to the mean annual precipitation (MAP) become higher at increasing values of the MAP. This confirms the idea that the landscape adjusts to the regional meteorological conditions. We also observed that the national threshold at 20% non-exceedance probability was capable of predicting all the rainfall-induced landslides that caused casualties between 1996 and 2014. We suggest that this threshold can be used as lower limit to forecast fatal rainfall-induced landslides in Italy. The findings encourage the use of empirical rainfall thresholds for landslide forecasting in Italy, but poses an empirical limitation to the possibility of defining accurate thresholds for small geographical areas, with insufficient datasets.

The Amatrice Basin is an intermountain morphostructural depression of the central Apennines (Italy) that hosted large amount of the epicentral distribution activated during the 2016-2017 seismic sequence. The basin rests on the hanging wall of the Gorzano-Laga Fault, a major NW-SE-striking extensional fault that is part of the complex seismogenic fault array. While structures and kinematics have been previously documented for the Gorzano-Laga Fault, no details on kinematics, styles of deformation, and time of activity have been yet provided for the fault systems resting within the Amatrice Basin. This work deals with the mechanisms of nucleation and development of the Amatrice Fault System (AFS), a ~10 km-long fault system located in the depocentre of the Amatrice Basin. Our multidisciplinary approach combines geological-structural investigations with geochronological (230Th/234U, Uranium-series disequilibrium) and geochemical (?13C and ?18O stable isotope) analyses on selected carbonate structures (calcite-filled veins and calcite fibres on fault surfaces). Our results are used to address the spatial-temporal evolution of the AFS in a complex mechanism of growth and link of isolated segments, likely assisted by fluid migration and calcite mineralisation. The stale isotope compositions and the geochronological dating attest for a meteoric water ingress through and along the AFS extensional faults in the Early-Middle Pleistocene. The AFS constrains the long-term history of the extensional tectonics regime in the Amatrice Basin, providing useful correlation with the activity of the basin-bounding Gorzano-Laga Fault.