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The following work focuses on the surveys that were carried out using optical sensors (photogrammetry) and LiDAR mounted on UAS platforms. The processing of the acquired images provided the necessary information for the development of high-precision digital terrain models that can be used as a basis for the subsequent modeling of the stability analysis of collapse phenomena with STONE, a three-dimensional rockfall simulation model. These surveys allowed us to localize the possible detachment sources and the inclusion of scenario-based seismic shaking as a trigger for rockfalls.The areas filmed fall almost exclusively along the north-western slope of Mt. Epomeo and more precisely in the areas identified as locality Falanga (32 ha) and locality Frassitelli (123 ha) in the territory of the Municipality of Forio (Napoli) and only marginally in the Municipality of Serrara Fontana (Napoli). The slope surveyed has two distinct morphologies: 1) the north-west oriented sector (Falanga) delimited by extremely steep walls and by cliffs with variable vertical development, at the base of which there is a large sub-flat area delimited to the north by a new sudden jump in slope; 2) in the west sector (Frassitelli) the slope is instead more rounded, even if in various points there are areas with steep slopes and strongly fractured cliffs; this side is characterized by the presence of numerous tuff blocks, even of large dimensions, which have stopped at various altitudes after having detached themselves from the overlying sub-vertical walls.We also used data from the Geoportale Nazionale Italiano managed by the Ministry of Environment and provided different kinds of spatial data. In particular, the archive contains an extensive LiDAR survey covering a substantial portion of Italy, with data stored at the intermediate processing level. For this research, we selected point clouds covering the Ischia island and we interpolated separately the two point clouds, using the module specifically designed to perform surface interpolation from vector points mapped by splines, within the GIS platform.In conclusion, we interpreted the point-to-point difference between DSM and DTM as due to vegetation and exploited this information to infer modifications of ground parameters relevant to the simulations with Stone. We partially took into account disturbances due to the presence of anthropic structures and buildings using additional land cover data, which we correlated with point-to-point DSM – DTM differences.

Over the last 2 decades, the topic of earthquake-triggered landslides (EQTLs) has shown increasing relevance in the scientific community. This interest is confirmed by the numerous articles published in international, peer-reviewed journals. In this work we present a database containing a selection of articles published on this topic from 1984 to 2021. The articles were selected through a systematic search on the Clarivate™ Web of Science™ Core Collection online platform and were catalogued into a web-based GIS (web-GIS), which was specifically designed to show different types of information. After a general analysis of the database, for each article the following aspects were identified: the bibliometric information (e.g. author(s), title, publication year), the relevant topic and sub-topic category (or categories), and the earthquake(s) addressed. The analysis allowed us to infer general information and statistics on EQTLs (e.g. relevant methodological approaches over time and in relation to the scale of investigation, most studied events), which can be useful to obtain a spatial distribution of the articles and a general overview of the topic.

Indicators and indexes are quantifiable parameters used in scientific disciplines to summarize and communicate complex data in a simple and explanatory manner. In the field of natural hazards, indicators and indexes have been used to characterize natural processes, and the associated risk conditions in terms of impact, vulnerability, exposure, and resilience. In this paper, we formalize indicators at the municipal level to differentiate the Italian territory based on the spatial distribution of landslides. The indicators were combined with other information to define indexes able to better characterize the stability conditions of the municipalities and quantify the possible impact of slope movements on the road network. Indexes were defined only for the Umbria Region (Central Italy), which was chosen as an example. The proposed indicators and indexes show, in a simple way, the severity of the instability on the territory and can be used to support decision-makers to assess, evaluate, and manage landslide mitigation activities and civil protection actions.

Over the last two decades, the topic of earthquake-triggered landslides (EQTLs) has shown an increasing relevance in the scientific community. This interest is confirmed by the numerous articles published in the international, peer-reviewed journals. In this work we present a database containing a selection of articles published on this topic from 1984 to 2021. The articles were selected through a systematic search on the Clarivate analytics’ Web of Science-Core Collection™ online platform and were catalogued into a web-GIS, which was specifically designed to show different types of information. After a general analysis of the database, for each article were identified the bibliometric information (e.g., author(s), title, publication year), the relevant topic/sub-topic category(s) and the addressed earthquake(s). The analysis allowed to infer general information and statistics on EQTLs (e.g., relevant methodological approaches over time and in relation to the scale of investigation, most-studied events), which can be useful to get a spatial distribution of the articles and a general overview of the topic.

In the past 50 years, a large variety of statisti- cally based models and methods for landslide susceptibility mapping and zonation have been proposed in the literature. The methods, which are applicable to a large range of spa- tial scales, use a large variety of input thematic data, differ- ent model combinations, and several approaches to evaluate the models’ performance. Despite the numerous applications available in the literature, a standard approach for suscepti- bility modeling and zonation is still missing. The literature search revealed that several software pro- gram and tools are available to evaluate regional slope stability using physically based analysis, but only a few use statistically based approaches. Among them, LAND-SE (LANDslide Susceptibility Evaluation) provides the possi- bility to perform and combine different statistical suscepti- bility models and to evaluate their performances and asso- ciated uncertainties. This paper describes the structure and the functionalities of LAND-SUITE, a suite of tools for sta- tistically based landslide susceptibility modeling which in- tegrates LAND-SE. LAND-SUITE completes and extends LAND-SE, adding functionalities to (i) facilitate input data preparation, (ii) perform preliminary and exploratory analy- sis of the available data, and (iii) test different combinations of variables and select the optimal thematic/explanatory set. LAND-SUITE provides a tool to assist the user during the data preparatory phase and to perform diversified statistically based landslide susceptibility applications. The implementation and improvement of LAND-SUITE with respect to the version published by Rossi and Reichenbach (2016) were funded mainly using internal funds. Txomin Bornaetxea was financially supported by the postdoctoral fellowship program of the Basque Government (grant numbers POS_2020_2_0010) and hosted by the University of the Basque Country (UPV/EHU, group IT1678) in the framework of a scien- tific collaboration with the Geological Survey of Canada as well as during scientific collaborations with the Geomorphological Group of the Research Institute for the Geo-Hydrological Protection in Perugia, Italian National Research Council (CNR-IRPI)

Earthquake-induced landslides (EQILs) are severe secondary effects of a seismic event. These phenomena can produce direct and indirect damages to structure, infrastructures and to the society. EQILs can also trigger secondary hazard cascading effects and impact civil protection activities. For this reason, the scientific community over the past decades has dedicated an increasing attention to EQILs, with the publication of numerous scientific papers. In this work we describe a preliminary outcome of a comprehensive review of the main articles published on this topic from 1984 to 2021 in peer reviewed international journals. The selected articles, which have been identified after a systematic search on the Clarivate analytics’ Web of Science-Core Collection™ online platform, have been catalogued in a database, whose structure was designed to include the information preparatory for the analysis. Specifically, for each of the 798 articles we reported: a) the bibliometric information (i.e., article title, author(s), publication year, journal name and number of citations); b) the specific topic addressed by the article, which can be distinguished with respect to the scale of the analysis (i.e., regional or single slope) and the type of research (e.g., mapping, characterization/description, modelling); and c) the information related to the earthquake(s) considered in the article. In the database, we have identified 139 earthquakes whose main characteristics (e.g., date of occurrence, location, magnitude, focal mechanism) have been organized in a sub-section of the database. The analyses pointed out different commonalities between articles which allowed us to infer general aspects related to EQILs and, at the same time, to describe a comprehensive state of art on the topic.

Fra. Si. a national research project supported by the Ministry of the Environment and Land and Sea Protection, develops a coherent set of multiscale methodologies for the assessment and zoning of earthquake-induced landslide hazards. To achieve the goal, the project operates at different geographical, temporal, and organizational scales, and in different geological, geomorphological, and seismic-tectonic contexts. Given the complexity, variability, and extent of earthquake-induced landslides in Italy, operating at multiple scales allows you to (a) maximize the use of available data and information; (b) propose methodologies and experiment with models that operate at different scales and in different contexts, exploiting their peculiarities at the most congenial scales and coherently exporting the results at different scales; and (c) obtain results at scales of interest for different users.The project defines a univocal and coherent methodological framework for the assessment and zoning of earthquake-induced landslide hazard, integrating existing information and data on earthquake-induced landslide in Italy, available to proponents, available in technical literature and from "open" sources - in favor of the cost-effectiveness of the proposal. The integration exploits a coherent set of modeling tools, expert (heuristic) and numerical (statistical and probabilistic, physically-based, FEM, optimization models). The methodology considers the problem at multiple scales, including: (a) three geographic scales - the national synoptic scale, the regional mesoscale and the local scale; (b) two time scales - the pre-event scale typical of territorial planning and the deferred time of civil protection, and the post-event scale, characteristic of real civil protection time; and (c) different organizational and management scales - from spatial planning and soil defense, including post-seismic reconstruction, to civil protection rapid response. Furthermore, the methodology considers the characteristics of the seismic-induced landslide and the associated hazard in the main geological, geomorphological and seismic-tectonic contexts in Italy.The project develops methodologies and products for different users and/or users. The former concern methodologies for (i) the synoptic zoning of the hazard caused by earthquake-induced landslides in Italy; (ii) the zoning and quantification of the danger from earthquake-induced landslides on a regional scale; (iii) the quantification of the danger of single deep landslides in the seismic phase; and for (iv) the identification and geological-technical modeling of deep co-seismic landslides starting from advanced DInSAR analyzes from post-seismic satellites.

Rockfalls pose a substantial threat to ground transportation, due to their rapidity, destructive potential and high probability of occurrence on steep topographies, found along roads and railways. Approaches for assessment of rockfall susceptibility range from purely phenomenological methods and statistical methods, suitable for modeling large areas, to purely deterministic ones, usually easier to use in local analyses. A common requirement is the need to locate potential detachment points, often found uphill on cliffs, and the subsequent assessment of the runout areas of rockfalls stemming from such points. Here, we apply a physically based model to calculate rockfall trajectories along the whole Italian railway network, within a corridor of total length of about 17,000 km and varying width. We propose a data-driven method for the location of rockfall source points based on expert mapping of potential source areas on sample representative locations. Using empirical distributions of gridded slope values in source areas mapped by experts, we derived probabilistic maps of rockfall sources in the proximity of the railway network, regardless of a particular trigger. Source areas act as starting points of simulated trajectories in the three-dimensional model STONE. The program provides a pixel-by-pixel trajectory count, covering 24,500 km2, the largest homogeneous application of the model to date. We classified the map into a vector susceptibility map of the segments of the railway, for which we provide segment-wise rockfall susceptibility. Eventually, we considered a graph representation of the network to classify the segments both on the basis of rockfall susceptibility and the role of each segment in the network, resulting in a network-ranked susceptibility. Both maps are useful for subsequent hazard assessment, and to prioritize safety improvements along the railway, at national scale., 22 pages, 9 figures, 6 tables. Published version

Rockfalls are one harmful kind of landslide, due to their rapidity, destructive potential and high probability of occurrence on steep topographies, often found along transportation corridors. Various factors can trigger rockfalls, including intense rainfall and seismic activity, and diverse phenomena affect their occurrence, like rock weathering and fracturing. Existing approaches for the assessment of rockfall susceptibility range from purely phenomenological to purely deterministic, physically based methods. A common requirement for many approaches is the need to locate the potential point locations of source areas, often located uphill on cliffs. Application of a physically based model, in particular, allows the calculation of material runout stemming from rockfalls originating from such point locations. In this work, we propose a method for the location of rockfall source points, on a digital elevation model, suitable for large areas. We deem the method as data-driven, because it relies on expert delineation of potential source areas from Google Earth images in few sample locations, representative of the study area at large. We measure the slope distribution of grid cells encompassed by expert-mapped source areas, and generalize the distribution of sources to the whole of the study area. We apply the method to a corridor of about 17,000 km in length and varying width, containing the entire Italian railway network. The map of source areas represents the main input for a physically based simulation of rockfall trajectories with the model STONE, and likely of other similar physically based or phenomenological models for rockfall runout assessment.

“From mapping to hazard and risk zonation” is Volume 2 of the book “Understanding and Reducing Landslide Disaster Risk”. The volume collects 54 articles covering five main general topics, including (i) landslide detection, recognition and mapping, (ii) landslide susceptibility assessment and spatial landslide modelling, (iii) landslide size statistics and landslide temporal modelling, (iv) data and information for landslide disaster mitigation, and (v) vulnerability to landslides of people, communities and the built environment. More than 180 authors contributed to the volume, and presented the results of their research conducted in 23 Nations in all continents, except Antarctica. Overall, the 54 articles illustrate a variety of consolidated and innovative methods and techniques, and together represent a contribution of the international landslide community to the long-term effort towards landslide disaster risk reduction.

Rockfalls are the most frequent and dangerous instability phenomena in mountainous areas, causing high economic and social damages. Rockfalls are triggered by complex instability mechanisms and the source areas are controlled by environmental factors like geology, the presence of discontinuities and slope angle. Modeling rockfall phenomena is complex and requires diversified input including parameters controlling the boulders trajectories and the source areas identification.In the Canary Islands, the steep topography and the geological complexity influence the activation of slope dynamics and the occurrence of slope failures. In particular, rockfalls are very common and they represent a major threat to society, costing lives, disrupting infrastructures and destroying livelihoods. In 2011 the volcanic crisis in El Hierro Island triggered numerous rockfalls that affected the road network causing a great social alarm.After the recent event, we have attempted to identify rockfall source areas using different approaches including probabilistic modeling. The probabilistic approach applies a combination of multiple statistical models and requires a map of the observed source areas as dependent variable and a set of thematic information as independent variables (e.g., morphometric parameters derived from DTM, lithological information that considers the mechanical behavior of the rocks). For the purpose, we have identified various scenarios selecting different training and validation zones and evaluating for each scenario the associated errors. The maps resulting from the models, provide for the whole El Hierro Island, the probability of a pixel being a source area and can be used as input for the rockfall modeling.

The increasing availability of free-access satellite data represents a relevant opportunity for the analysis and assessment of natural hazards. The systematic acquisition of spaceborne imagery allows monitoring areas prone to geo-hydrological disasters, providing relevant information for risk evaluation and management. In case of major landslide events, for example, spaceborne radar data can provide an innovative solution for the detection of slope failures, even in case of persistent cloud cover. The information about extension and location of the landslide-affected areas may support decision-making processes during the emergency responses. In this paper, we present a semi-automatic procedure, based on Sentinel-1 Synthetic Aperture Radar (SAR) images, aimed to facilitate the detection of rapid-moving landslides. The procedure evaluates changes of radar backscattered signals associated to land cover modifications, that may be also caused by mass movements. The procedure requires an initial manual selection of some parameters, and is able to execute automatically the download and pre-processing of images, the detection of SAR amplitude changes, and the identification of areas potentially affected by landslides, which are then displayed in a geo-referenced map. This map should help decision-makers and emergency managers to organize field investigations. The processes automatization is implemented with specific scripts running on a GNU/Linux operating system and exploiting modules of Open Source software. We tested the processing chain, in back analysis, on an area of about 3000 km2 in central Papua New Guinea that in February/March 2018 was struck by a severe seismic sequence that triggered numerous widespread landslides. In the area, we simulated a periodic survey of about seven months, from 12 November 2017 to 6 June 2018, downloading 36 Sentinel-1 images and performing 17 change detection analyses automatically. The procedure resulted in statistical and graphical evidences of widespread land cover changes occurred just after the most severe seismic events. Most of them can be interpreted as mass movements triggered by the main seismic shocks.

The variability of landslide phenomena in terms of types, velocity and size, makes it difficult to establish a unique methodology for the definition of landslide susceptibility, with different approaches proposed in the literature for the prediction of landslide occurrence. In addition, the extent of the study area and the characteristics of the available data may influence the selection of the susceptibility models. For these reasons, landslide susceptibility studies described in the literature use different modelling approaches adopting a variety of mapping units and thematic information. In this chapter, we first use a database of 565 articles from a recent systematic review of the literature to illustrate and describe a synthesis of relevant information on landslide susceptibility modelling and terrain zonation. We then present examples of susceptibility zonations prepared at four different scales: (i) continental (Europe), (ii) national (Italy), (iii) sub-national (Umbria Region, Italy), and (iv) catchment scale (Collazzone area, Italy), using different data types and resolutions, different mapping units, and various statistically-based modelling approaches. We use these four examples to provide our reflections on the proprieties of the geo-environmental data, and the main characteristics of the modelling approaches at different scales. We conclude with a few steps that could become a starting point for the discussion and definition of a standard for statistically-based landslide susceptibility methods and zonation.

From Mapping to Hazard and Risk Zonation is Volume 2 of the book "Understanding and Reducing Landslide Disaster Risk", prepared to collect selected contributions presented to the Fifth World Landslide Forum (WLF5), to be held in Tokyo, Japan, 2-6 November 2021. A contribution of the International Consortium of Landslides (ICL) to landslide disaster risk reduction, the volume is divided in six parts, and comprises an editorial introduction, two keynote articles, and 52 articles covering five main topics related to (i) landslide detection, recognition and mapping techniques and methods tested at various geographical scales and in different morphological, geological and climatic settings, (ii) landslide susceptibility assessment and spatial landslide modelling at different geographical scales, using consolidated and innovative techniques, (iii) landslide size statistics and landslide temporal modelling, which are key, yet inadequately investigated to landslide hazard assessment, (iv) landslide data and information collection, organization, and sharing for improved disaster mitigation, and (v) vulnerability to landslides of people, communities and the built environment, key but poorly understood components of landslide risk assessment.

Modelling rockfall phenomena is complex and requires various inputs, including an accurate location of the source areas. Source areas are controlled by geomorphological, geological, or other geo-environmental factors and may largely influence the results of the modelling. In the Canary Islands, rockfalls are extremely common and pose a major threat to society, costing lives, disrupting infrastructure, and destroying livelihoods. In 2011, the volcanic event on the island of El Hierro triggered numerous rockfalls that affected strategic infrastructures, with a substantial impact on the local population. During the emergency, the efforts performed to map the source areas and to model the rockfalls in the considerably steep landscape characterising the island were not trivial. To better identify the rockfall source areas, we propose a probabilistic modelling framework that applies a combination of multiple statistical models using the source area locations mapped in the field as the dependent variable and a set of thematic data as independent variables. The models use as input morphometric parameters derived from the Digital Elevation Model and lithological data as an expression of the mechanical behaviour of the rocks. The analysis of different training and validation scenarios allowed us to test the model sensitivity to the input data, select the optimal model training configuration, and evaluate the model applicability outside the training areas. The final map obtained from the model for the entire island of El Hierro provides the probability of a given location being a potential source area and can be used as the input for rockfall runout simulation modelling.

Regional landslide inventories are often prepared by several different experts, using a variety of data sources. This can result in a combination of polygon and point landslide data, characterized by different meanings, uncertainties and levels of reliability. The propagation of uncertainties due to such heterogeneous data is a relevant issue in statistical landslide susceptibility zonation at supra-local scale. In the inhabited highlands of the Rwenzori Mountains, we compare different approaches and mapping units to provide a robust methodology for susceptibility mapping using a combination of landslide point and polygon data. First, the effect of the uncertainty related to a point representation of landslides is assessed comparing slope unit-based and pixel-based analyses, using digital elevation models with different resolutions. Secondly, with regard to landslide polygon inventories, we compare the use of thresholds versus a presence/absence of the depletion centroid or a randomly selected point in the landslide polygon in order to identify slope units with landslides. Based on these results, we prepare regional slope unit-based susceptibility maps using a logistic regression model calibrated with the landslide polygon inventory and validated with the point inventory. Although pixel-based mapping remains the most common approach for statistical landslide susceptibility zonation, our analysis clearly favours the use of slope units as a powerful tool to prepare regional susceptibility maps and, in particular, to exploit heterogeneous information in a consistent way.

Il lavoro descrive le carte inventario delle frane, di tipo geomorfologico e multi-temporale, preparate per una parte del territorio comunale di Motta Montecorvino, che ricade nel settore collinare e montuoso del Sub-Appennino Dauno (Provincia di Foggia, Puglia). Il lavoro è realizzato nell'ambito del progetto "Valutazione integrata dei fenomeni di instabilità geo-idrologica in Puglia, modelli interpretativi e definizione delle soglie di pioggia per l'innesco di frane" ed ha lo scopo di produrre una carta inventario delle frane di tipo geomorfologico per tutto il territorio Dauno e carte inventario di tipo multi-temporali per dieci centri abitati. La mappatura delle frane è realizzata attraverso l'interpretazione di più serie di fotografie aeree stereoscopiche in bianco e nero a diverse scale, per il periodo dal 1954 al 2003. La carta inventario geomorfologica di Motta Montecorvino, evidenzia un'elevata presenza di frane con dimensioni che vanno da centinaia di metri quadrati a qualche decina di ettari, mentre la carta inventario multi-temporale mostra un elevato numero di frane recenti di piccole-medie dimensioni, all'interno o in prossimità dei corpi di frane preesistenti e di maggiori dimensioni.

In this paper, we do a critical review of statistical methods for landslide susceptibility assessment and associated terrain zonations. Landslide susceptibility is the likelihood of a landslide occurring in an area depending on local terrain conditions, estimating "where" landslides are likely to occur. Since the first attempts to assess landslide susceptibility in the mid-1970s, hundreds of papers have been published using a variety of approaches and methods in different geological and climatic settings. Here, we critically review the statistically-based landslide susceptibility assessment literature by systematically searching for and then compiling an extensive database of 565 peer-review articles from 1983 to 2016. For each article in the literature database, we noted 31 categories/sub-categories of information including study region/extent, landslide type/number, inventory type and period covered, statistical model used, including variable types, model fit/prediction performance evaluation method, and strategy used to assess the model uncertainty. We present graphical visualisations and discussions of commonalities and differences found as a function of region and time, revealing a significant heterogeneity of thematic data types and scales, modelling approaches, and model evaluation criteria. We found that the range of thematic data types used for susceptibility assessment has not changed significantly with time, and that for a number of studies the geomorphological significance of the thematic data used is poorly justified. We also found that the most common statistical methods for landslide susceptibility assessment include logistic regression, neural network analysis, data-overlay, index-based and weight of evidence analyses, with an increasing preference towards machine learning methods in the recent years. Although an increasing number of studies in recent years have assessed the model performance, in terms of model fit and prediction performance, only a handful of studies have evaluated the model uncertainty. Adopting a Susceptibility Quality Level index, we found that the quality of published models has improved over the years, but top-quality assessments remain rare. We identified a clear geographical bias in susceptibility study locations, with many studies in China, India, Italy, South Korea and Turkey, and only a few in Africa, South America and Oceania. Based on previous literature reviews, the analysis of the information collected in the literature database, and our own experience on the subject, we provide recommendations for the preparation, evaluation, and use of landslide susceptibility models and associated terrain zonations.

The use of remotely piloted aircraft systems (RPASs) in geosciences is often aimed at the acquisition of an image sequence to produce digital models and orthophotographs of the topographic surface. The technology can be applied for rockfall hazard and risk assessment. To study rockfalls, an approach consists in the application of numerical models for the computation of rockfall trajectories. Data required for such simulations include digital terrain models, location of the instability source areas, and the mechanical properties of the terrain. In this article, we present an analysis of the earthquake-triggered rockfall that occurred along the SP18 in Villanova di Accumoli (Lazio, central Italy) during the seismic sequence that started on 24 August 2016. A survey with a multicopter was carried out to obtain a surface model of the terrain and identify and characterize the source areas and other instable blocks in areas not accessible in the field. The investigated area extends for 6500 m2 and was covered by 161 photographs that were used to obtain an orthophoto with a ground resolution of 2.5 cm and a digital surface model with a ground resolution of 20 cm × 20 cm, which was processed and fused with GNSS real-time kinematic data. To obtain a map of potential rockfall trajectories, we run the numerical model STONE, using as origin of the boulders both source areas mapped in the field and pixels with a slope angle above a selected threshold. Results showed that only the part of the road SP18 already affected by the rockfall was exposed to further rockfall impacts. In particular, it was observed that 29.2 % (i.e. 12 123) of the 41 500 simulated trajectories may potentially reach or cross this tract of the road. Based on these data, limited protection measures were suggested. The combined use of RPAS data, fused with ground GPS points, an accurate geomorphological survey, and terrain static and dynamic parameters from the literature allows fast, low-cost, and replicable rockfall numerical modelling useful for emergency response and adoption of proper protection measures.

The document, which represents the fourth deliverable of WP4 "Tools and methods to support Early Warning System for Rock falls", describes the actions performed in the Activity 4.5 "Rainfall thresholds for the possible initiation of rock falls". The main goal of this activity is the definition of empirical rainfall thresholds for the possible initiation of rock falls in the Canary Islands. The report describes the empirical cumulated event rainfall - rainfall duration (ED) thresholds for the Gran Canaria and Tenerife test sites. For the purpose, a tool for the objective and reproducible reconstruction of rainfall events and of rainfall conditions responsible for rock falls is used. A frequentist statistical method is adopted to define ED thresholds for different non-exceedance probabilities.

Lo scopo del documento è aggiornare i requisiti utente del sistema SANF-RFI, le cui funzionalità e caratteristiche sono definite nella Proposta Tecnica. L'individuazione dei requisiti utente di SANF-RFI è basata: (i) su quanto emerso nell'ambito di incontri con RFI, utente del sistema SANF-RFI e dei suoi prodotti, e (ii) sulle conoscenze e competenze del CC CNR IRPI. Nel documento è riportato l'elenco aggiornato dei requisiti utente di SANF-RFI, suddivisi in requisiti di capacità (CAP), di interfaccia (INT), hardware e software (RHS), e di servizio (SER). I requisiti sono numerati e codificati.

The document is an update of the deliverable "Map and report on rockfall source areas modelling" (D4.6) released in December 2018, and introduces new data and inforation on observed source areas. The document describes an application of LAND-SUITE (LANDslide - SUsceptibility Inferential Tool Evaluator) to evaluate the spatial probability of rockfall source areas in El Hierro island.

A 1:5,000 scale geological map and 31 geological cross-sections are presented for the surroundings of Amatrice village (central Apennines, Italy), epicentral area of the first damaging earthquake of the 2016–2017 seismic sequence. This detailed geological dataset focuses on: (i) the extent, the thickness, and the internal stratigraphic architecture of the Quaternary continental deposits; (ii) the bedding and the thickness of the Miocene substratum; and (iii) the spatial distribution of the main fault systems. The provided dataset would update the available regional geological maps in deciphering the syn-to-post-orogenic history of the Amatrice Basin. Eventually, the accuracy of the geological mapping would represent a basic tool for interpreting and integrating the multidisciplinary dataset deriving from post-seismic activities.

Il documento illustra i risultati della modellazione della suscettibilità da frana (i.e. probabilità spaziale di occorrenza o propensione al dissesto) per frane di crollo, colata detritica e scivolamento, e per la loro combinazione lungo la rete ferroviaria gestita da Rete Ferroviaria Italiana S.p.A. (RFI).

Urbanization of mountainous areas characterized by rough morphology implies the construction of road networks intersecting the drainage streams by means of bridges, culverts, or low water crossings. Historical data on the occurrence of damage caused by floods or sediment-laden flows are a key element for the identification of critical road sections prone to future impacts with geo-hydrological processes. In this contribution, we present a database of historical information on geo-hydrological damaging events affecting road and railway networks in correspondence of watercourse crossings in the Calabria region, southern Italy. This region is characterized by a rugged orography, steep slopes, and few plains, resulting in a large number of small drainage basins, high relief energy, and remarkable river bed load. Here, during extreme weather periods, the road network is the most frequently and intensely damaged element. Direct damage consists in breakage of road sectors and bridges, often affecting people travelling. Indirect damage involves the effects on society, which result in a loss of revenue and tourism, and increased times and costs from longer driving distances due to road blockages. The database has been built using the typical historical data sources as chronicles, diaries, historical books, local and regional agencies, press archives, scientific papers, and documents of Civil Protection offices. It includes spatial and temporal information on more than six hundred events of breakage or damage to watercourse crossings on several types of road and railway, occurred in the region from 1902 to 2016. We analyzed the historical records identifying the affected municipalities and basins, and generating descriptive statistics on data. Furthermore, we analyzed the geomorphometric properties of the basins subtended by the points representing the locations of the damaging events, in order to search for relationships between the basins features and damage, and to characterize all the other basins subtended by each road crossing in the region. Such analysis and related results can be useful for regional infrastructural planning and emergency response, or as a framework of those critical points that either must be monitored during floods or needing reinforcement works.

Automatic subdivision of landscapes into terrain units remains a challenge. Slope units are terrain units bounded by drainage and divide lines, but their use in hydrological and geomorphological studies is limited because of the lack of reliable software for their automatic delineation. We present the r.slopeunits software for the automatic delineation of slope units, given a digital elevation model and a few input parameters. We further propose an approach for the selection of optimal parameters controlling the terrain subdivision for landslide susceptibility modeling. We tested the software and the optimization approach in central Italy, where terrain, landslide, and geo-environmental information was available. The software was capable of capturing the variability of the landscape and partitioning the study area into slope units suited for landslide susceptibility modeling and zonation. We expect r.slopeunits to be used in different physiographical settings for the production of reliable and reproducible landslide susceptibility zonations.

Landslide susceptibility (LS) assessment provides a relative estimate of landslide spatial occurrence based on local terrain conditions. A literature review revealed that LS evaluation has been performed in many study areas worldwide using different methods, model types, different partition of the territory (mapping units) and a large variety of geo-environmental data. Among the different methods, statistical models have been largely used to evaluate LS, but the minority of articles presents a complete and comprehensive LS assessment that includes model performance analysis, prediction skills evaluation, and estimation of the errors and uncertainty. The aim of this paper is to describe LAND-SE (LANDslide Susceptibility Evaluation) software that performs susceptibility modelling and zonation using statistical models, quantifies the model performances, and the associated uncertainty. The software is implemented in R, a free software environment for statistical computing and graphics. This provides users with the possibility to implement and improve the code with additional models, evaluation tools, or output types. The paper describes the software structure, explains input and output, and illustrates specific applications with maps and graphs. The LAND-SE script is delivered with a basic user guide and three example data sets.

We present an updated version of the European landslide susceptibility map ELSUS 1000 that was released through the European Soil Data Centre in 2013. The ELSUS V2 map shows the landslide susceptibility zonation for individual climate-physiographic zones across Europe. ELSUS V2 covers a larger area of Europe than ELSUS 1000 as it includes Iceland, Cyprus, the Faroes, and the Shetlands, at a higher spatial resolution (200 x 200 m). The updated map was prepared using the same semi-quantitative method as for ELSUS 1000, combining landslide frequency ratios information with a spatial multi-criteria evaluation model of three thematic predictors: slope angle, shallow subsurface lithology and land cover. However, the new map was prepared using also: i) an extended landslide inventory, containing 30% of additional locations for model calibration, map validation and classification, and ii) a new lithological data set, based on harmonized shallow subsurface information derived from the International Hydrogeological Map of Europe (IHME). The new version of the map increases the overall predictive performance of ELSUS by 8%.

SAFETY is a two-years European project started the 1st January 2016 and ended the 1st January 2018. The general aim of the project was to develop a methodology and tools in order to exploit Sentinel-1 data for detecting and monitoring the activity state of geohazards (e.g. landslides, volcanic and subsidence) and evaluating their impact on built-up areas and infrastructure networks, at a regional scale. The products of the methodology must support Civil Protection Authorities (CPA) in the risk management activities at a regional scale. In this contest, a strong effort has been spent to generate products that must be operative: reliable and easily to read by users who are not familiar with radar data. The developed procedure is fast, periodically repeatable, and case-adaptable. The methodology, allows the full exploitation of Sentinel-1 constellation data (wide area coverage, high temporal repeatability, freely available data) making feasible long term monitoring plannings. Moreover a free software tool for the Sentinel-1 SAR data processing has been developed. This work presents the developed methodology, through some images of the most significant results obtained over the two test sites of the project (the Canary Island, in Spain, and the Volterra municipality, in Italy), and explains both the strengths and the main lessons learnt for the future steps.

A rapid assessment of the areal extent of landslide disasters is one of the main challenges facing by the scientific community. Satellite radar data represent a powerful tool for the rapid detection of landslides over large spatial scales, even in case of persistent cloud cover. To define landslide locations, radar data need to be firstly pre-processed and then elaborated for the extraction of the required information. Segmentation represents one of the most useful procedures for identifying land cover changes induced by landslides. In this study, we present an application of the i.segment module of GRASS GIS software for segmenting radar-derived data. As study area, we selected the Tagari River valley in Papua New Guinea, where massive landslides were triggered by a M7.5 earthquake on February 25, 2018. A comparison with ground truth data revealed a suitable performance of i.segment. Particular segmentation patterns, in fact, resulted in the areas affected by landslides with respect to the external ones, or to the same areas before the earthquake. These patterns highlighted a relevant contrast of radar backscattering values recorded before and after the landslides. With our procedure, we were able to define the extension of the mass movements that occurred in the study area, just three days after the M7.5 earthquake.

Deliverable D4.6: Map and report on rockfall source areas modelling. This deliverable describes a new approach for a probabilistic identification of rockfalls source areas, using a combination of multiple statistical models able to reduce the subjectivity. The proposed model requires a map of the observed source areas and thematic information (e.g., morphometric indicators derived from DTM, lithological information that explicitly consider the mechanical behaviour of the rocks, vegetation information). The map of the probabilistic source areas will be the input for rockfall modelling that will be performed using STONE, a GIS-based rockfall simulation software that provided, among other information (energy and speed of block), the distance travelled by the blocks from different source areas.

Lo scopo del documento è descrivere i requisiti utente del sistema SANF-RFI. L'individuazione dei requisiti utente di SANF-RFI è basata: (i) su quanto emerso nell'ambito di incontri con RFI, utente del sistema SANF-RFI e dei suoi prodotti, e (ii) sulle conoscenze e competenze del CC CNR IRPI. Nel documento è riportato l'elenco dei requisiti utente di SANF-RFI, suddivisi in requisiti di capacità (CAP), di interfaccia (INT), hardware e software (RHS), e di servizio (SER). I requisiti sono numerati e codificati.

Il documento illustra le attività svolte per la definizione dei livelli di esposizione al danno da frana per il tracciato dell'acquedotto che rifornisce la città di Messina. I risultati riportati rientrano nelle attività di ricerca svolte dall'Istituto di Ricerca per la Protezione Idrogeologica (IRPI), Centro di Competenza (CC) del Dipartimento della Protezione Civile (DPC), nell'ambito dell'emergenza idrica nella città di Messina per conto del Commissario Delegato per fronteggiare l'Emergenza idrica nella Città di Messina (CDEM).

In Italy rainfall-induced slope failures occur every year, claiming lives and causing severe economic disruptions. We have designed and implemented a warning system, named SANF (an acronym for national early warning system for rainfall-induced landslides), to forecast the possible occurrence of rainfall-induced landslides. The system is based on: (i) rainfall thresholds for possible landslide occurrence, (ii) sub-hourly rainfall measurements obtained by a nationwide network of 1950 rain gauges, and (iii) quantitative rainfall forecasts. All system components exploit Open Source software. Twice a day the system compares the measured and the forecasted rainfall amounts against pre-defined thresholds, and assigns to each rain gauge a probability of landslide occurrence. This information is used to prepare synoptic-scale maps showing where rainfall-induced landslides are expected. The system outputs are delivered to the National Civil Protection Authorities in different formats. Spatial outputs are published as standard OGC (Open Geospatial Consortium) web services (WMS, WFS, WCS) by the IRPI Spatial Data Infrastructure (IRPI SDI). A password protected WebGIS interface facilitates the use of the system by the Civil Protection personnel and gives access to current and past forecasts. In addition, bulletins containing the system information can be generated automatically and sent via e-mail to the Civil Protection personnel. In a more recent implementation, the system calculate hourly-based forecast using new regional rainfall thresholds and combine landslide forecasts with landslide susceptibility information available at synoptic scale in the national territory. Improvements of the validation procedures and of the landslide susceptibility layer are currently underway.

The Tramuntana range, in the northwestern sector of the island of Mallorca (Balearic Islands, Spain), is frequently affected by rockfalls which have caused significant damage, mainly along the road network. In this work, we present the procedure we have applied to calibrate and validate rockfall modelling in this region, using 103 cases of the available detailed rockfall inventory (630 rockfall events collected since the eighteenth century). We have exploited STONE (Guzzetti et al. 2002), a GIS-based rockfall simulation software which computes 2D and 3D rockfall trajectories starting from a DTM and maps of the dynamic rolling friction coefficient and of the normal and tangential energy restitution coefficients. The appropriate identification of these parameters determines the accuracy of the simulation. To calibrate them, we have selected 40 rockfalls along the range which include a wide variety of outcropping lithologies. Coefficients values have been changed in numerous attempts in order to select those where the extent and shape of the simulation matched the field mapping. Best results were summarized with the average statistical values for each parameter and for each geotechnical unit, determining that mode values represent more precisely the data. Initially, for the validation stage, 10 well-known rockfalls exploited in the calibration phase have been selected. Confidence tests have been applied to their modelling results taking into account not only the success but also the mistakes. The best accuracy is obtained when the rockfall has a preferential trajectory and worse results when the rockfall follows two or more trajectories. Additionally, the greater the rockfall runout length, the less precise the simulation is. We have further validated the calibrated parameters along the Ma-road (111 km), the main transportation corridor in the range, using 63 rockfall events that occurred during the past 18 years along the road. Of the rockfalls where source areas were properly identified, 81.5 % are well represented by STONE modelling, as the travel paths and the depositional areas are successfully ascertained. Results of the analysis have been used by the Road Maintenance Service of Mallorca to assess hazard and risk posed by rockfall at regional scale to design the road management plan.

Diplomazia2 is framed within the program "Science for Diplomacy: Multi-disciplinary Training Program", and it is the result of closer and more mature collaboration between the Directorate General for Cooperation on Development of the Ministry for Foreign Affairs and International Cooperation (MAECI), the Italian Agency for Cooperation on Development (AICS) and the National Research Council (CNR). The implementation of joint projects such as DIPLOMAzia2 highlights the effectiveness of the diplomacy-science partnership as the driving force behind the achievement of relevant goals jointly pursued by the international community.