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Da molti anni la Commissione - nell'ambito delle azioni dedicate a rafforzare il legame tra scienza e società - invita i ricercatori a promuovere la cooperazione con soggetti esterni, dagli stakeholder ai cittadini, a comunicare di più e meglio, a valorizzare i risultati della propria ricerca dimostrando che essa può avere un impatto (sociale ed economico) sulla società. Ma ancora oggi queste attività sono considerate come non strettamente attinenti allo sviluppo della ricerca, se non proprio estranee, dalla maggior parte dei ricercatori, che spesso le delegano a figure esterne, ritenendosi poco adeguati (o non tenuti) a svolgerle. Con il risultato di acuire la separazione invece di rafforzare il legame tra scienza e società. 1 Questo atteggiamento, con il nuovo approccio della RRI, richiesto in tutti i progetti finanziati nell'ambito del programma Horizon2020 (H2020), non è più possibile, almeno in via teorica. Nella RRI si chiede infatti ai ricercatori di attuare un cambio del proprio modo di operare, "anticipando" i possibili impatti delle attività, "riflettendo" sulle azioni intraprese o da programmare durante le fasi, da quelle svolte quotidianamente fino alle interazioni personali con tutti gli attori dell'innovazione. Nella nuova configurazione del rapporto tra scienza e società auspicato da H2020 ci si aspetta dunque qualcosa di diverso e di più di una semplice adesione formale a delle norme o strumentale per accedere a un finanziamento comunitario. Per parafrasare il titolo di un report europeo (Felt 2007), la RRI chiede a tutti gli attori di "prendere sul serio" la responsabilità nella società della conoscenza, a cominciare dalla riflessione su come sta cambiando il proprio specifico ambito di ricerca e sulle implicazioni che il cambiamento e l'innovazione proposta possono avere per le responsabilità di tutti gli attori. E' quanto abbiamo provato a fare con il progetto "Strategies and Tools for REsilient Smart Societies" (dall'acronimo STRESS) che descriviamo brevemente in questo capitolo.

Recent decades in Italy have seen a very rapid expansion of urbanisation in terms of physical assets, while demographics have remained stable. Both the characteristics of Italian soil and anthropic development, along with repeated global climatic stress, have made the country vulnerable to floods, the intensity of which is increasingly alarming. The combination of these trends will contribute to large financial losses due to property damage in the absence of specific mitigation strategies. The present study focuses on the province of Sondrio in Northern Italy (area of about 3,200 km²), which is home to more than 180,000 inhabitants and the population is growing slightly. It is clearly a hot spot for flood exposure, as it is primarily a mountainous area where floods and flash floods hit frequently. The model we use for assessing potential flood damage determines risk scenarios by overlaying flood hazard maps and economic asset data. In Italy, hazard maps are provided by Regional Authorities through the Hydrogeological System Management Plan (PAI) based on EU Flood Directive guidelines. The PAI in the study area includes both the large plain and the secondary river system and considers three hazard scenarios of Low, Medium and High Frequency associated with return periods of 20, 200 and 500 years and related water levels. By an overlay of PAI maps and residential areas, visualized on a GIS, we determine which existing built-up areas are at risk for flood according to each scenario. Then we investigate the value of physical assets potentially affected by floods in terms of market values, using the database of the Italian Property Market Observatory (OMI), and in terms of reconstruction costs, by considering synthetic cost indexes of predominant building types (from census information) and PAI water height. This study illustrates a methodology to assess flood damage in urban settlements and aims to determine general guidelines that can be extended throughout Italy. The final objective will be to analyse how the loss prospective can change when mitigation measures, including actions to reduce the flood hazard and strategies to prevent potential consequences, are implemented. Flood impacts and the corresponding value of mitigation measures will be assessed by means of a cost-benefit analysis in accordance with the EU Floods Directive.

Modern approaches for emergency management promote exchange of information between local authorities and community aiming at more appropriate and effective ways to manage hydro-meteorological risks1. In this framework, risk communication should not only start during the build-up of the hazard, but also in pre-warning and 'peace' time and it contribute to better emergency preparedness. Lately, a rapid growth of interest emerges to enable citizens to inspect hazard-related processes on their territory2. From the risk managers perspective, substantial advantages of taking this citizen-based approach include (1) the opportunity to identify on a quick and 'relatively' low cost basis one or more risk components at different geographical locations and (2) the ability to provide a practical application for citizens interested in creating and communicating useful information toward establishing a better understanding of their territory. From the citizens perspectives, it provides the opportunity to generate benefit through increasing and encouraging interest for self-awareness as well as self-preparedness. However, the use of citizen-based information also bring forth the need to train and establish standardized forms, guidelines and tools, particularly if the data collected seek to be useful information for decision-making activities and emergency management3. In this research work, we address the question on the quality of data collected by volunteers for decision-making activities. This in the framework of the civil protection organization of the Friuli-Venezia-Giulia (CP-FVG) and the Italian study area of the CHANGES project, Municipality of Pontebba4. An experiment is carried out by analyzing the results of a questionnaire form dealing with the inspection of the functional status of check dams and bridges across streams. This form is filled by volunteers (in this case, citizens and university students), that register to a web-portal with access by browser after a standardized training given by practitioners and scientists. During the latter, the guidelines to fill the questionnaire, i.e. various conditions of hydraulic structures and the proposed criteria for quality evaluation5, will be disseminated to the volunteers. The quality of the data are analyzed on the basis of these guidelines in order to determine if the citizens-based data collection approach can be used to prioritize the structures to be inspected by the risk managers.

La tecnica WofE, utilizzata anche nel Progetto Permanet, prevede l’acquisizione di una serie di informazioni spazializzate e standardizzate. Il modello si basa su metodologia quantitativa per combinare “evidenza“ a supporto dell’ipotesi (ossia la distribuzione dell’evento) e si fonda su una serie di temi (es. uso del suolo, litologia) a cui viene dato un peso rispetto alla probabilità di accadimento. I parametri su cui si basa il modello consistono in una serie di dati d’ingresso e un set di fenomeni avvenuti presenti in un database storico (training points). I parametri gestiti sono vincolati alla loro disponibilità e ricampionati per ottenere una risoluzione standard The WofE technique, also used by the PermaNET Project, is based on the acquisition of spatial and standardised information. This model is aimed at collecting evidence supporting the hypothesis (the event distribution) through a quantitative method and is based on a number of elements (such as land use, lithology) that acquire a certain weight in relation to their likeliness of occurrence. The model parameters are a series of input data and of occurred events inserted into a historical database (training points). The use of these pa- rameters depends on their availability; they are then re-sampled in order to obtain a standard resolution.

In the framework of the European project Mountain Risks (http://mountain-risks.eu/), one of the projects currently developed is a methodology to integrate risk management and evacuation emergency plans, focused on prevention as a key element for disaster risk reduction, applied in the Mountain Community Valtellina of Tirano, an area recurrently affected by several mountain hazards. Taking into account the actual state of disaster risk reduction initiatives in the study area, including the existence of a real time emergency plan based on GIS (Geographical Information Systems), DSS (Decision Support Systems), and ICT (Information & Communication Technology), but knowing the lack involvement of the general community in any of the preparation activities developed until the present and the lack of divulgation of the current emergency plan, it was decided that the methodology that could better adapt to the actual conditions of the study area would be a non structural Community Based Early Warning System (CBEWS). A CBEWS has been recognized by institutions as the UN and the INSDR, as an effective and important strategy for disaster risk reduction. This strategy is broadly used especially in developing countries and has proved its effectiveness in many disasters crisis all over the world. In spite of that, possibly for political and social reasons, there are really few applications of CBEWS in developed countries which has made the elaboration of this research project a particularly difficult process due to the lack of previous references with similar conditions to the one in the study area. Difficulties related to any multidisciplinary work which also involves the general community have been faced during the development of the project such as the differences in language (both the technical jargon of the different disciplines and the native language), time restrictions, the process of learning and adapting to different social structures, the process of contacting several institutions and persons looking to co-involve them in the project. The development of the CBEWS involves several phases: hazard and risk assessment including the analysis of the legal framework and the application of an extensive social survey to evaluate the levels of risk perception, awareness, preparation and information desires of the community; the development of prevention and monitoring strategies and preparedness activities, including the development of a communication campaign developed by an interdisciplinary group to inform and educate the community and practitioner stakeholders. Preliminary results of the survey show, among others, low levels of risk perception and preparedness, and lack of knowledge and information related to natural hazards. All the results confirm the necessity of develop the communication and education campaign. The aim of the CBEWS is not only to increase the level of preparedness of the community and decrease its vulnerability, but also to strengthen institutional collaboration, in particular local institutions, in order to assure acontinuity of the efforts

In the Environmental risk evaluation, the most important problem are: to attempt to anticipate the risks, to assess the relationships between causes and effects and to balance the benefits with the costs associated to the control of risks. Risk assessment is mixed with risk management, which is in effect a different area of human behavior. According to mainstream economics refer risk to individual behavior, the Expected utility function (EUF) incorporates risk: risk aversion is strictly individual, it’s necessary a good knowledge of probability occurrence and risk is managed through decision. But, when we use multidimensional data to describe the risk, EUF seems inadequate: environmental risks are complex, and so individual can not manage them. The main consequence is that environmental risk is to be considered exogenous with respect to individual behavior. Environmental economics assesses risks on the basis of the relationship: causes lead to effects. Effects have to be evaluated as physical/technical ones, afterwards it is possible to assess their economic value., Aestimum, Aestimum 42 (2003)

The objective of this work was to draw up a Municipality Emergency Plan, implemented in a information support, in order to manage a Hydro- geological Emergency. The landslide occurrence probability needs the drafting of a Civil Protection Plan able to reliably tackle the management of emergencies. The study of the hazard area together with its vulnerability, enables to analyze and to make a zonation of the risk within the same area. This information is necessary to develop the Emergency Procedures to be applied on the occasion of a Landslide event. The use of Geographic Information Systems makes more efficient the contemporary management both of the cartography of the area and of useful databases concerning for example Civil Protection resources and structures required to overtake the emergence. This approach leads up to computerize and speed up the reply of the structures involved in an emergency situation, leading to a significant reduction of the response time by the staff that manage the emergency operations, and leading to an increase of the qualitative efficiency response.

The Civil Protection purpose is to better protect people, their environment, property and cultural heritage in case of major natural events or manmade disasters (Foster, 1980, Alexander, 1998, Alexander, 2000). The management of a critical event has precise goals: people safeguard, taking care of the injured, coordination of first aid activities, recovery of primary public services, management of personnel, organization of resources and communication with public and private institutions, government agencies, authorities and citizens (Cate, 1994; Daines, 1991; Drabek et al., 1991). In a broader view, the role of Civil Protection is carried out through three key modes of action: prevention, preparedness and response. These actions encompass: a) the prevention of risks and damage to people, properties, infrastructure and in so doing environment, in the event of disasters, detecting and studying causes of disasters, improving means and methods of forecasting, analysing the characteristics of the damaging event together with the vulnerability of the territory, respectively; b) the increase of the degree of preparedness of people involved in Civil Protection, in order to raise their ability to quickly and effectively respond to an emergency; the cooperation requires a rapid mobilisation of intervention teams, experts and other resources in the event of major emergencies in order to alleviate the effects of a disaster during the first days. The Civil Protection is entrusted to facilitate these actions as well to offer technical or technological support, if required; c) the improvement of the techniques and methods of response and taking care emergencies; d) the enhance of the public information, education and awareness, helping citizens to protect themselves more effectively. Information is the key to successful cooperation in Civil Protection matters. The dissemination of information can be carried out in advance or during the emergency; e) the granting of financial assistance to the affected areas via the Solidarity Fund.

The main aim of this work is developing new technologies for managing emergencies in the field of Civil Protection. In Italy and in Lombardy there are many lows that govern the management of emergencies and give directives to guide the implementation of municipal emergency plans for the Civil Defence. The innovative aspect of this research is to combine the potential of Geographic Information Systems (GIS), of Decisions Support Systems (DSS) and of the most modern mobile technologies (for communication) for the emergency management in a real-time. For this work is used a software called PETer (developed by Globo Srl), a geographic information system that is able to integrate different kind of information. This software allows us to manage all the information that are necessary to the implementation of an emergency plan and is able to give guidelines for overcoming it. In this way all the involved people are able to know what they have to do in all the phases of the emergency. The potential of the software is being consultable, easy usable and upgradeable.

Landslides are one of the most common hazards in the Romanian Curvature Carpathians and Subcarpathians, covering a wide range of geomorphic mass wasting forms and processes. The purpose of this paper is to present a susceptibility analysis at regional scale for the Buzau County (Romania), focusing on shallow and medium-seated (sensu B?lteanu 1983) landslides. The susceptibility map was obtained using the weights-ofevidence modeling technique that allows understanding the significance of predisposing factors of shallow and medium-seated failures. The model was run considering eight environmental factors: slope, altitude, internal relief, planar and profile curvature, aspect, soil, land-use. A landslide inventory derived from archive data, literature review, field mapping and aerial imagery interpretation was divided into a training and a prediction set and was used to prepare and validate the model. The model performance was evaluated using the area under the ROC and the success rate curve. The susceptibility map represents an important step for landslide hazard and risk assessment, crucial components for the definition of adequate risk management strategies.

Agriculture is a global issue nowadays. At the European level, it is a sector, in which we are investing many resources. In particular, the Agri-Food sector plays a central role in the policies of the European Commission and the Horizon 2020 research and innovation program, as well as being the main theme of Expo 2015 that will be held in Milan, Lombardy. In the Lombardy region, the farmers represent 2% of the entire population, cultivating about 80% of the agricultural land. Increasing needs to develop a common body of knowledge shared at the regional and national level so as to make it possible to effectively monitor cropping systems, water stress and impacts of climate changes affecting more frequently the territory, are becoming more and more urgent. In this context, the project Space4Agri (S4A) intends to support the regional and local needs in terms of management of the agriculture sector, by designing and developing an information and knowledge based platform for managing geospatial and mainstream information by making it accessible over the Internet by standard communication technologies (Geo&Mainstream ICT). This platform has been designed to allow data workflows integrating i) spatial data and observations, ii) non-spatial information available from existing agronomic databases, iii) data collected in the field by farmers, agronomists and volunteers using mobile applications, iv) data collected by unmanned aerial sensors, and/or data produced by researchers as a result of applying scientific analysis on high quality remote sensing data. Foreseen results of the Space4Agri project and from other similar ongoing research activities may significantly spur the socio-economic development of Europe and create new growth opportunities for companies, public administrations, students and citizens.

Agriculture is a global issue nowadays. At the European level, it is a sector, in which we are investing many resources. In particular, the Agri-Food sector plays a central role in the policies of the European Commission and the Horizon 2020 research and innovation program, as well as being the main theme of Expo 2015 that will be held in Milan, Lombardy. In the Lombardy region, the farmers represent 2% of the entire population, cultivating about 80% of the agricultural land. Increasing needs to develop a common body of knowledge shared at the regional and national level so as to make it possible to effectively monitor cropping systems, water stress and impacts of climate changes affecting more frequently the territory, are becoming more and more urgent. In this context, the project Space4Agri (S4A) intends to support the regional and local needs in terms of management of the agriculture sector, by designing and developing an information and knowledge based platform for managing geospatial and mainstream information by making it accessible over the Internet by standard communication technologies (Geo&Mainstream ICT). This platform has been designed to allow data workflows integrating i) spatial data and observations, ii) non-spatial information available from existing agronomic databases, iii) data collected in the field by farmers, agronomists and volunteers using mobile applications, iv) data collected by unmanned aerial sensors, and/or data produced by researchers as a result of applying scientific analysis on high quality remote sensing data. Foreseen results of the Space4Agri project and from other similar ongoing research activities may significantly spur the socio-economic development of Europe and create new growth opportunities for companies, public administrations, students and citizens.

Statistical based landslide susceptibility models are widely used in medium to regional scale assessments. The two main inputs in these models are the landslide inventory of past events and the landslide caustative factor maps. In this study we assessed how the performance and prediction capability of the Weights-of-Evidence (WofE) susceptibility model is affected by the way we represent landslides in the pixel format, considering the entire polygon or only the landslide centroid. Influence of pixel density representing the landslide polygon was also taken into account. The second part of the research concidered the effect of the landslide model training and prediction sample sizes on the performance and prediction rates of the WofE model. Two case study areas were chosen to apply the representation and sampling tests: (1) the Fella River Basin (Eastern Italian Alps) containing debris flows and (2) the four times larger Buzau County (Romanian Carpathians) containing shallow landslides. Both areas are very different in terms of size, landslide types and geo-environmental factors, and were chosen in order to determine the applicability and flexibility of our analysis. Our results indicate that there is only a minor increase in performance and prediction when increasing the number of pixels to represent the entire landslide polygon. As the number of pixels increased from a single centroid to all pixels within the polygon, we found that the relative increase in pixels was similar within all classes (e.g. grass-land, forest, bare rock) of each thematic factor map like land-use or litholo gy. This indicated that the landslides have a similar size across the entire study area and is one of the causes of the lack of significant increase in model performance. The similari ty in performance and prediction rates for different landslide representation tests was in contrast to their respective susceptibility maps, which did show significant differences among each-other. This requires further analysis in future studies to determine which susceptibility map should be chosen for decision making. As for the sample size analysis, we have found that using 10 to 20% of all landslides to train the WofE model in both case studies is sufficient to predict the remaining 80 to 90% of the landslides. Modeling with more than 20% of the landslides causes a "plateau effect" in the performance and prediction rates. This indicate s that only a small percentage of all the landslides in an inventory are needed for good prediction results, making it also unnecessary to map every landslide in the area for a suffici ent performing landslide susceptibility analysis.

This contribution discusses how spatial prediction models of landslide susceptibility can be applied to datasets with combination of categorical and continuous data layers maintaining the variability of values: i.e., avoiding binary transformations that impoverish their significance. The data layers represent conditional factors, such as geology, land use, distance from thrusts, internal relief, slope, attitude and permeability, which are used to associate the distribution of mapping units with that of landslides, possibly of specific dynamic types and time intervals of occurrence. The landslide trigger areas, used as training sites, maintain in the modeling their spatial extension as polygonal patches. Predictions are made by mathematical models, e.g., empirical likelihood ratio, also using several occurrence subsets to obtain blind testing for empirical cross-validation of the spatial prediction results. Prediction maps are interpreted in relation with the corresponding prediction-rate curves expressing the goodness of the prediction. Datasets from two study areas in northern Italy, come from the Apennines and from the Alps. Different analytical strategies are followed in the two study areas due to the difference in density of landslide occurrence. The prediction-rate curves obtained provide continuous class values distributions that preserve variability thus avoiding prediction class grouping before interpretation. The analysis of the prediction-rate curves, tables and histograms leads to more articulate criteria for decisions aiming at hazard mitigation or avoidance. Maps of predicted susceptibility/hazard levels are generated that consist of relative values that need careful quantitative scrutiny to be interpreted: the only meaning of such relative values is their rank.

Natural and anthropogenic factors are identified as critical in characterizing aquifer vulnerability in the Milan Province study area, in which the impact of elevated concentrations of NO3 is being assessed. In this contribution, map versions of such continuous and categorical data layers are used to establish relationships between their map units and the location of over 300 water wells with nitrate levels either clearly above a threshold of 20 mg/l (impacted wells), or with wells clearly below that (non-impacted wells). The natural and anthropogenic data layers that are assumed to reflect (a) potential sources of nitrate, and (b) relative ease with which nitrate may migrate in groundwater, are: population density, nitrogen fertilizer loading, precipitation and irrigation, protective capacity of soils, land use, vadose zone permeability, groundwater depth, and groundwater velocity. Two versions of the data layers database are used in the study: one in which the data layers maintain their original value ranges and one in which they are reclassified into simplified classes. The water wells are separated first into the two groups to locate and recognize sites to be used to map high and low vulnerabilities using an empirical likelihood ratio prediction model, ELR. Further partition of the two sub-groups into prediction and validation wells allows setting up blind tests to cross-validate the predictions of relative vulnerability classes (ranks). Prediction-rate curves and tables are obtained and visualized as cumulative proportions of study area in decreasing order of predicted vulnerability class versus the corresponding relative proportion of impacted validation wells (i.e., not used to predict). A similar procedure is followed with the non-impacted well locations. Predictions are thus compared and interpreted and repeated predictions are obtained using randomized sub-sets of prediction and validation wells. Target of the strategy used is not only to assess the goodness of predictions but also to estimate their reliability levels.

Nell'ambito della Convenzione tra la Comunità Montana Valtellina di Tirano (Sondrio, Italia) e l'Istituto per la Dinamica dei Processi Ambientali (IDPA, sezione di Milano) del Consiglio Nazionale delle Ricerche (CNR, 2004), ha preso l'avvio uno studio finalizzato allo sviluppo di metodologie informatiche atte alla gestione di rischi idrogeologici (a livello degli effetti fisici attesi, conseguenti a fenomeni potenzialmente pericolosi) e finalizzate, in ultima analisi, alla definizione di un Piano di Protezione Civile. Tale piano è stato inizialmente definito, in via del tutto sperimentale, in una porzione del comune di Grosotto (Sondrio), identificata come possibile scenario di rischio, sulla base delle informazioni a disposizione; si è inoltre tenuta in considerazione la reale struttura organizzativa delle squadre di Protezione Civile, attualmente operanti a livello comunale.

A 3D geological modelling methodology is briefly presented in this work. This procedure allows to reconstruct complex geological bodies using topographic and structural-geological data. The main constraints considered for the geological surfaces reconstruction are the geological cross-sections. GIS (Geographic Information System) tools and functions have been exploited for 2D data management, while gOcad® software for 3D modelling. The proposed methodology consists in three main steps: i) data acquisition; ii) data storage in a GIS; iii) 3D surface and volume reconstruction. This methodology has been applied for the 3D reconstruction of the Monte Misma anticline (Bergamo), localized in the thrust and fold systems of the frontal part of the Central Southern Alps. This 3D geological reconstruction allows to check and improve the geological interpretation of the buried surfaces. Moreover the geological surfaces and volumes definitions can be very useful in the different environment of the Earth Sciences (eg. oil exploration; numerical modelling; geophysical data processing, etc.).

A geological map can be considered one of the best tool to display the geometrical relationships among different geological bodies. Moreover their extent can be appreciated in three dimensions, applying geometrical techniques, when topographic and structural data are available. The aim of this work is to show how geological cartographic field data stored in a Geographic Information System (GIS) can be used for 3D modeling of complex geological bodies, using a procedure which has been established for this purpose. 3D reconstruction has been performed in gOcad. This software is based on the discrete smooth interpolator, which makes possible the construction of 3D surfaces, volumes and grids starting from simple elements with an atomic structure, as points and lines. These techniques, chiefly based on the use of cartographic data, have been applied to the reconstruction of a deep seated slope gravitational deformation developed within the sedimentary cover of the Southern Alps, Bergamo, Italy. The DSSGD occurs within a complex thrust stack, later affected by strike-slip and normal faults. These structures have been modelled basing on detailed structural, morpho-structural and geological field data (1:5,000-1:2,000). Photointerpretation techniques have been used for morphological analyses. All these data were firstly stored and integrated within a GIS, to be later generalized and imported into gOcad. The 3D model was reconstructed through several steps which will be described in detail. 3D modelling offers several advantages. First of all, a rigorous check of the consistency of the surface geology and of 2D interpretative sections was possible, taking to a general improvement of the geometrical interpretation of the Zuccone DSSGD and to 3D retrodeformation of the slided rock masses. Moreover the geometric features of the reconstructed geological bodies can be used to design preliminary monitoring plans or subsurface investigations through seismic surveys and drilling. In addition, the construction of 3D grids, where properties are added, can represent a starting point for geomechanical numerical modeling.