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.