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Sinkholes are widespread phenomena on the Earth. Consisting of vertical depressions with chiefly circular shape and a three-dimensional funnel shape (Waltham et al., 2005), their triggering is often associated to dissolution or erosion of geological materials, which leads to underground instability and subsequent formation of the depression. When a sinkhole is generated in an urban area, it can be defined as “anthropogenic” sinkhole (Guarino &amp; Nisio, 2012). Because of the presence of a widespread network of artificial cavities, the city of Naples is one of the urban areas most affected by sinkholes in Italy (Basso et al., 2013). To emphasize and recognize the most prone areas, a sinkhole susceptibility analysis has been carried out. The sinkholes susceptibility map has been produced by using a Machine Learning technique, namely Maximum Entropy (MaxEnt). MaxEnt is a presence-only method that relies on the assumption that the best model to represent the true distribution of an event is the one maximizing the entropy. Maximizing the system entropy means that the best model I 965ew32s the one with the maximum uncertainty about event’s probability of occurrence. This, in turn, implies that the best model has no starting hypothesis and all the combinations of predictor variables can trigger the investigated event (Phillips &amp; Dudik, 2008). To apply such algorithm, a sinkhole inventory is required, and twelve environmental variables have been employed to obtain a more realistic susceptibility map. The results highlight that the most susceptible zones coincide with the historical city center due to the higher presence of cavities and secondary aqueduct and sewer networks. In addition, the highest susceptibility class presents a relatively important extension (4.93%) which consolidates the necessity of studying these phenomena in metropolitan cities like Naples in an effort to help the local administration in finding eventual susceptible areas. The produced map is a first attempt to evaluate the sinkhole susceptibility in the study area by using a Machine Learning technique that takes in consideration the whole Naples municipality.

SGI 2021

Evaluation of anthropogenic sinkhole susceptibility in the city of Naples (Italy) through a presence-only algorithm

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L'Istituto Nazionale di Oceanografia e Geofisica Sperimentale - OGS e il Dipartimento di Matematica e Geoscienze dell'Università di Trieste sono orgogliosi di ospitare il 90° Congresso della Società Geologica Italiana a Trieste dal 14 al 16 settembre 2021. La modalità del congresso è interamente online.

Con il motto "Geologia senza frontiere" questo evento mira a promuovere le Scienze della Terra come disciplina scientifica proiettata nel futuro, oltre i confini geografici, politici e disciplinari, per comprendere meglio l'interno del Pianeta Terra e la struttura del sottosuolo, difendere la società da pericolosi eventi geologici, comprendere meglio la variabilità climatica, pianificare l'utilizzo delle georisorse in modo etico e nel rispetto dell'ambiente.


**Please note, times listed in the SCHEDULE tab (calendar icon) reflect YOUR LOCAL TIME ZONE. The main timezone for this conference will be Central European Summer Time.**

The National Institute of Oceanography and Experimental Geophysics - OGS and the Department of Mathematics and Geosciences of the University of Trieste are proud to host the 90th Congress of the Italian Geological Society in Trieste on 14-16 September 2021.  The Congress will be held entirely online.

With the motto "Geology Without Borders" this event aims to promote Earth Sciences as a scientific discipline projected into the future, beyond geographical, political and disciplinary boundaries, to better understand the interior of Planet Earth and the structure of the subsurface, defend society from dangerous geological events, better understand climatic variability, plan the use of geo-resources in an ethical way and respecting the environment.


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Earth Sciences should be understood not only as necessary for a better understanding of the interior of the planet Earth, but also as a defense of society from dangerous geological events, for the understanding of climatic variations, for the planning and use of georesources in a ethical and respecting and protecting the environment.

Sinkholes are widespread phenomena on the Earth. Consisting of vertical depressions with chiefly circular shape and a three-dimensional funnel shape (Waltham et al., 2005), their triggering is often associated to dissolution or erosion of geological materials, which leads to underground instability and subsequent formation of the depression. When a sinkhole is generated in an urban area, it can be defined as “anthropogenic” sinkhole (Guarino & Nisio, 2012). Because of the presence of a widespread network of artificial cavities, the city of Naples is one of the urban areas most affected by sinkholes in Italy (Basso et al., 2013). To emphasize and recognize the most prone areas, a sinkhole susceptibility analysis has been carried out. The sinkholes susceptibility map has been produced by using a Machine Learning technique, namely Maximum Entropy (MaxEnt). MaxEnt is a presence-only method that relies on the assumption that the best model to represent the true distribution of an event is the one maximizing the entropy. Maximizing the system entropy means that the best model I 965ew32s the one with the maximum uncertainty about event’s probability of occurrence. This, in turn, implies that the best model has no starting hypothesis and all the combinations of predictor variables can trigger the investigated event (Phillips & Dudik, 2008). To apply such algorithm, a sinkhole inventory is required, and twelve environmental variables have been employed to obtain a more realistic susceptibility map. The results highlight that the most susceptible zones coincide with the historical city center due to the higher presence of cavities and secondary aqueduct and sewer networks. In addition, the highest susceptibility class presents a relatively important extension (4.93%) which consolidates the necessity of studying these phenomena in metropolitan cities like Naples in an effort to help the local administration in finding eventual susceptible areas. The produced map is a first attempt to evaluate the sinkhole susceptibility in the study area by using a Machine Learning technique that takes in consideration the whole Naples municipality.

poster

The “Ceppo Lombardo Formation” (Riva, 1957) is a collection of Quaternary clastic conglomeratic units outcropping and sub-outcropping in an area of the Po Plain, North to the city of Milan (Italy). Due to the shallow depth and the areal extension of this formation, the geophysical characterization assume a great importance for geotechnical engineering, territory use and local seismic hazard studies. The geophysical characterization of such clastic units shows several and not negligible issues, starting from its great areal extension to the great variability in the cementation and alteration parameters. The main geological, geophysical and geotechnical information about this formation, derive from a great amount of data and studies available from local administration and professional studies, these datasets were not ever integrated to have a more robust geotechnical knowledge. With the aim of a more consistent characterization, we gathered and analysed all available geophysical and geological datasets, resulting from well stratigraphies and geophysical soundings. Additional geophysical surveys were conducted, using the single station passive seismic (HVSR) technique; one single site investigation and two 10-km-long perpendicular transects. New and old geophysical data was integrated with the information from geognostic tests (e.g. core drilling and cutting from well drilling) for an efficient validation, then a statistics study was performed. We present the geophysical methods, the statistical analysis results of vs parameter and several depth maps of its distribution in all study area. The main final results show that Ceppo Lombardo Formation show a well detectable impedance contrast where it overlies units with poor geotechnical characteristics. This formation has also been classified as overconsolidated soil (Vs < 500 m s-1) with the exception of the Brembo unit that show Vs values of a seismic bedrock (Vs > 800 m s-1). Additionally, the great variability output of the HVSR tests, indicate that the top surface has irregular geometry with variable impedance contrasts up to about 30 m depth.

Geophysical characterization of Ceppo Lombardo Formation (Po Plain NE of Milan, Italy): new data from passive seismic surveys

Research in urban geomorphology is a relatively recent topic and its theory and practice require continuous updates. Few studies have focussed on issues specifically connected with the cartographic representation of geomorphological processes and landforms in urban environments, with the aim of tentatively reconstruct and clarify the original physical landscape. Among these, recent urban geomorphological surveys conducted in Italian cities proposed new strategies for detecting and mapping human induced modifications to the topography, and anthropogenic landform classification has been recently deepened in the revised Italian national guidelines for geomorphological mapping (Campobasso et al., 2018), proposed by the Working Groups of the Italian Association of Physical Geography and Geomorphology (AIGeo) and the Italian Institute for the Environmental Protection and Research (ISPRA). In this work, natural landforms modified by man and artificial landforms are explored and compared in three Italian cities: Rome, Genoa and Perugia. The comparison is interesting because of the different morphogenetic environment characterizing the 3 cities and also for the differences in the geomorphological survey and mapping. At the same time, in these urban areas, human activities have similarly remodelled the topographic surface and become the most important modelling agent of relief. Many reliefs have been erased, whereas thick layers of anthropogenic deposits covered most of the natural landforms, with the result, for example, of hiding or greatly modifying the natural valley incisions. Geomorphological studies in urban environments allow the reconstruction of the physical landscape before human modifications and the implementation of innovative methodological tools, and an effective legend to represent the urban landforms and their evolution over time.

Geomorphological classification of the landscape in urban areas: anthropogenic landforms in Genoa, Rome and Perugia

Since early 1990s, the advent of satellite-based techniques, such as the Differential Interferometry Synthetic Aperture (DInSAR) (e.g. Curlander & McDonough, 1991) and Global Navigation Satellite System (GNSS), has revolutionized the monitoring of ground level displacements thanks to satellite-based techniques. These observation systems enabled us to control with unprecedented accuracy and resolution deformation phenomena caused by transient events, such as earthquakes, volcanic eruptions and sinkholes, or long-term processes, like subsidence and landslides, thus revealing useful applications in the geological, geotechnical and structural analysis fields (e.g. Lanari et al., 1998; Herrera et al., 2009). Today, the Advanced DInSAR (A-DInSAR) technique is based on high resolution sensors, which monitor the evolution of instability phenomena in any atmospheric and lighting condition, and in both historical centers and archaeological sites. Within this framework, we propose the application of an exhaustive approach for studying both permanent and periodic components of vertical land deformation in the urban area of Naples (southern Italy). Such methodology, successfully applied in the Po Delta area (Vitagliano et al., 2020), is proposed to study the geological risks in urban areas and to evaluate the effects of the anthropic context on the periodic processes related to climate variability. Firstly, a spatial analysis has been carried out to calculate the interferometric velocities of Sentinel-1 and COSMO-SkyMed data in the time intervals January 2016 – December 2019 and March 2017 – December 2020, respectively. The obtained ground displacement and velocity have been used for mapping the stable and unstable urban areas and for evaluating the dependencies between the distribution of the velocity zones and some geological features (e.g. ancient alluvial deposits and paleo-coast lines). Afterwards, a spatial-temporal analysis of continuous GPS data available for a site located in the city center has been performed, which provided a reliable identification of the seasonal trends of the ground displacement. Finally, an automatic cross-correlation procedure developed in Matlab environment was applied to systematically correlate the interferometric trends of each reflection point with the rainfall and sea level oscillations, measured in the same time interval. The correlation process allowed the identification of the most significant dependencies and the triggering mechanisms of the slow soil oscillations, and gave also interesting insights into urban instability processes, such as sinkholes.

Study of periodic dependencies among ground deformation, rainfall and sea level in the city of Naples (Italy)

Landslides represent a serious threat in hilly and mountainous areas of the world. Usually, shallow landslides are triggered by intense or prolonged rainfalls and frequently may evolve into potentially catastrophic flow-like movements. Because of the capacity of these phenomena to travel long distances, buildings and infrastructures located in areas improperly deemed safe can be affected. Landslides can be destructive events when mobilize large volumes of soil and/or rock and undergo long distances. It is impossible to stop such events and the best way to prevent disasters is to reduce or avoid the related risk (Carrara et al., 1999). Landslide risk assessment is a research topic of growing interest across the scientific community. Such interest stems from the awareness of the still dramatic impact of landslides on the socio-economic development of vast areas and the concurrent boosting request for urbanization across landslide-prone areas (Petley, 2012). Risk mitigation measures must necessarily focus on the vulnerability of the exposed elements and, in particular, of buildings potentially impacted by landslides. The destruction of these structures can provoke enormous economic losses and endanger the people inside them. On this basis, a study concerning landslide impacting settlements in the Cuenca area (Ecuador) has been carried out thanks to the availability of two fundamental datasets: landslide inventory map (LIM) and information on building's presence. A LIM represents a fundamental tool to display information on landslides activity and their multi-temporal evolution (Corominas et al., 2014). In most cases, inventories are discontinuous over time and so-called event-based landslide inventories are available, which are landslide inventories based on a singular severe event (rainfall- or earthquake-induced). In this case, LIM was derived from interferometric data and the visual interpretation of aerial photos integrated and validated by field investigation. The surveyed slope failures were classified according to Cruden & Varnes (1996). As concerns buildings information, it was possible to obtain multi-temporal data on the evolution of buildings constructed from 2010 to 2020. From this knowledge, it was possible to note that over time, due to the steady population increase, most of the buildings were built in correspondence of the mountainous areas surrounding the Cuenca center. Thanks to the availability of these data, it can be stated that the buildings, over time, have been built in areas that can potentially be affected by landslides.

Landslides affecting buildings in rapidly growing areas of Cuenca (Ecuador)

Consequences of climate change are often more obvious on global scale, but downsizing at regional scale implies a good knowledge of territory, its intrinsic fragility and the urban characteristics. Underlining and predicting trends of climate variables within regional and especially municipal scales to promote adaptation and mitigation strategies is the purpose of the SECAP (Supporting Energy and Climate Adaption Policies). A practical approach to analysing the impact of climate change aimed at driving specific policies and actions on an urban scale is the SECAP template, the official report of the Covenant of Mayors initiative. Using different methodologies, we have examined various extreme climatic events and climate projections at the regional scale, downscaling to the city of Trieste and other rural areas: the heat waves, the drought, the wildfires, the heavy precipitations, and all the consequences linked, for instance, to the river floods or episodic storm surges combined with the sea level rise. All projections seem to indicate potential significant variations in intensity of extreme events or frequency during the different seasons from a mid-term/long-term timeframe (2050-2100). The intensification of such extreme events amplifies the effects of sea level rise and the temperature increase on the territory, causing important consequences in terms of geological hazard, such as river flood, coastal flood and landslide, especially in a highly urbanized contexts like the city of Trieste. In order to quantify the cause-effect relationships requested by the SECAP template, we propose a methodology based on the intrinsic geological characteristics and vulnerabilities of the territory. In the template, the current hazards are considered in term of probability and impact, whereas for the future hazards the definition of the expected change of intensity and frequency, as well as the timeframes are requested. The quantitative approach permits to scale the qualitative “low, medium, high” attributes, too generic as indicators. For the river flood, the Regional Hydrogeological Planning Plan (PAI) and the risk maps of the Floods Directive have been analysed, parameterizing the hazard in a quali-quantitative way and highlighting the vulnerable areas. For the coastal flood we have superimposed predictive models of inundation of the city to the digital terrain model, quantifying the coastal length involved in the phenomenon. For landslide, we analysed and revised the regional landslides database in terms of the number of landslides compared to the extent of the municipal area and the type of land use. Finally, for each geological hazard, the effects of the foreseen intensification in extreme events were assessed. The analyses obtained show an increasing trend in these geological phenomena, and in general in risk. These considerations form the basis for the drafting of SECAP and local planning.

A quantitative approach for the urban adaptation policy to climate change (SECAP): an application to some geological hazards

The town of Naples is located in the eastern sector of the Campi Flegrei, a volcanic field placed along the Tyrrhenian flank of the southern Apennines. The geological evolution of Naples is strictly related with the volcanic history of the Campi Flegrei (Ascione et al., 2020, and reference therein). The present-day topography results from the interaction between volcanism, bradyseism and sea-level variations and is prone to the development of a dense network of ephemeral rivers, some of which develop along faults and fractures affecting the volcanic units (Ruello, 2008). According to the features of river networks, the town of Naples may be sub-divided in three sectors. To the west of Naples (e.g., near Agnano, Pianura, Soccavo, Fuorigrotta, Bagnoli, Posillipo and Chiaia), river network consists of small, often isolated, valleys (length around 1 km), dissecting both the inner and outer flanks of the Campi Flegrei caldera (whose  slope also exceeds 30°). In the central sector of Naples (e.g., near Vomero, Camaldoli, Capodimonte and the historical centre), river network is more organised, with “small” valleys converging towards “large” valleys. Consequently, large drainage basins may be recognised, which collect water from the hilly areas towards the low topography, very densely urbanised, historical centre. To the east of Naples (e.g., near Poggioreale, Ponticelli, San Giovanni a Teduccio), river network consists of a main trunk, the Sebeto River, flowing in the related alluvial plain. Most of the river network is very hard to be recognised, being overwhelmed by the growth of the town. A typical example is the Sebeto River, which actually flows below ground level and whose mouth has been included in the harbour area. The lack of river valleys is apparently in contrast with the alluvial events that struck Naples since historical times, as testified by alluvial deposits found in the subsurface (Cinque et al., 2011; Romano et al., 2013). Some of these events are pretty “famous”, such as those one that often hit the quarter named Sanità, which are known as the “Lava dei Vergini” due to volcanic clasts transported during the alluvial event. Noteworthy, the memory of “hidden” rivers remains in the name of many streets, as testified by the terms “Cupa”, “Cavone”, “Vallone” and “Arena” that identified sectors of the urban areas developed on river valleys. These features make Naples an interesting study area to analyse the interaction between natural processes and anthropic loading, and to make people aware of landscape dynamics.

The hidden rivers of Naples (southern Italy)

Gubbio (Umbria, central Italy) was built on the slope of Mt. Ingino (908 m asl), on the left bank of Torrente Camignano, where the vast flat area known as the "Gubbio Plain" begins. The debris at the base of the slope of Mt. Ingino is delimited by two alluvial fans, one of the Torrente Camignano at NW (almost flat) and the other of the Fosso Cavarello at SE (more steep). The slope debris shows an evident morphological step (H max. about 20 meters) oriented parallel to the slope itself. This produces a marked discontinuity in the slope profile and affects the whole width of the detrital body. This kind of escarpments is frequent on the slope debris at the base of the mountains of the Gubbio chain. This ridge constitutes the NE flank of an anticline, formed during the Apennine orogeny. It is broken at the core by a normal fault with considerable upthrow (over 1500 meters) and with direction parallel to the axis of the fold itself. These escarpments are likely to be interpreted as the surface morphological expression of recent phases of tectonic activity linked to the Gubbio fault (which, therefore, has to be considered an active and capable fault). A bull of Pope Clement III in 20 October 1188 and a diploma of Emperor Henry VI in 5 June 1191 suggest that when the Eugubini (the people of Gubbio), in the second half of the 12th century, decided to build the new city "on the mountain", they identified how the most suitable place for the fortified urban space, the one upstream of the great escarpment which divided in two parts the slope debris of Mt. Ingino. Later, especially during the 13th century, a consistent urbanization took place in Gubbio. This led to an inevitable expansion downstream of the urban core, which essentially took the shape of the current historic center of the city. On the specific topic of the relationship between the definition and development of the late medieval city of Gubbio and the conformation of the slope debris on which it was built, some preliminary considerations have already been formulated (Sannipoli, 2013). The research in progress is aimed at investigating some specific aspects of this interesting problem of urban geomorphology, both as regards a more precise definition of the geomorphological characteristics of the site, and in relation to the transformations of the first urban core of Gubbio, over the 13th and 14th centuries. Above all, it seems interesting to define what these transformations entailed, as regards the alterations of the geomorphological peculiarities of the site where the city was born and had subsequently developed.

Geological-geomorphological conditioning on the development of historical centers: the example of Gubbio (Umbria, central Italy)

In highly urbanized contexts for millennia, the presence of underground artificial cavities represents one of the most important opportunity for the investigation of geological subsoil. Thanks to urban geology, it is in fact possible to combine the intrinsic geological aspects and characteristics of a city’s underground with the man-made changes of the original natural landscape. This paper focuses on the investigation of a crucial key point for the geological and geomorphological arrangement of the Perugia’s hill, the capital city of the Umbria region (central Italy). The study case is the area close to the Etruscan Well (third century B.C.), one of the most relevant archeo-geosite in the downtown of the city. Through a multidisciplinary approach moving from a geological and geomorphological data to historical-archaeological ones (Melelli & Rosati, 2019) with information of the hydraulic works of Perugia (Bergamini, 1991), it has been possible to rebuild the architecture of the anthropic cavities and to establish the possible connection with this ancient hydraulic works, in relation to the geological and geomorphological structure of the area. In addition, non-invasive geomatics investigations such as terrestrial laser scanner (TLS) and ground penetrating radar (GPR) have been used. The GPR survey, successful already use in historical urban areas (Ercoli et al., 2016), was planned on the data formerly obtained by the georeferenced TLS survey. The result is a three-dimension visualization of the Etruscan Well and the surrounding area, enriched by the numerous subsoil profile collected. The elaboration of these profiles and their subsequent study have allowed to expand the knowledge on an area as old as it is still unknown: focused on the interpretation of the anomalies found in the subsoil, revealed other artefacts around the Well, such as buried tunnels or possible fragments of ancient roads (Melelli et al., 2021).

The key role of anthropic underground cavities in the urban geology: the Etruscan Well in Perugia’s upper town (Umbria, central Italy)

This century is the “century of the cities”, where rapid urbanization and greater global connection present unprecedented urban challenges and concentrates risk in urban areas making them increasingly vulnerable (Coaffee & Lee, 2016). The need arises for urban planning must be asked to fully incorporate an understanding of the sub-surface into the deliberation/decision-making process (Howard, 1997). The Urban Geo Footprint (UGF) is classification tool being developed by a sub-group of the Urban Geology Expert Group of EuroGeoSurvey (UGEG) and it is based on a multidisciplinary effort in which different skills and expertise come into play. The main objective of this project is to set up a classification method to identify the main geological and anthropic features that influence city's resilience related to its geological setting. A tool is being developed in order to clustering cities according to their geological and climatic features and to understand why target urban contexts have different issues (e.g. climate change, floods), and thus to assess the cities’ geo-resilience. The UGF will help cities to understand what ‘economic’ and ‘social well-being’ benefits (i.e. in terms of ‘geological resilience’) could derive from urban planning associated with subsoil knowledge. The salient features required for this tool are: - It must be user-friendly and easy to use by scientists and non-scientists - It must be available at European level (and maybe, once is tested in Europe, it could be extended worldwide). The following main 5 drivers are defined in the tool: Geology, Climate, Geohazards, Geomorphology, Subsoil anthropic pressure. The assessment method of UGF tool will consist in testing it with data of different EU pilot-cities. The work in progress is developing a complex worksheet (which can be defined as the UGF framework ) with several quantitative parameters related to the 5 drivers mentioned above. All these parameters are going to be indexed (using scores) and weighted based on two levels of investigation: “basic” and “advanced”. The final result for each city is a general UGF score that will be the combination of all the drivers specific scores. Each tested city will be classified also by the weight of each driver in the calculation. Other objectives of the project are: - Contributing to develop a method for the comparison of data from different cities and update all existing database. - Improving the European collaboration and, therefore, the exchange of ideas on good practices to increase cities’ resilience. - Improving citizens' awareness of both the resources and the threats associated with geology.

Preliminary activities aimed to cluster EU cities by a geological point of view: The Urban Geo Footprint tool

The present work describes SecureGeoStreet (SGS), a cyberinfrastructure entirely built in a GIS environment and accessible from many platforms such as pc, tablet, and smartphones. SGS provides a geological risk value to all segments of a road network of an area, through a semi-automated procedure.  Focused on the case study of Giarre municipality (eastern Sicily - Italy), this work is based on the calculation of several types of geo-hazard and their interaction with exposure. About geo-hazards, the analysis of geological and hydrological issues, geomorphological instability, and tectonic evidence have been performed; the identification of critical areas was done through the collection of bibliographic data from online databases, such as the IFFI project, the PAI cartography, and the Civil Protection Department database, and also through the creation of derived ancillary maps like TIN model, hillshade, slope and aspect charts.  The geo-hazard evaluation has been enriched by the interpretation of Persistent Scatterers (PSInSAR), obtained through the Rheticus® Displacement service by processing the Sentinel-1 images (from October 2014 to June 2018). The average velocity along the line-of-sight (LOS) and the displacements time-series were considered in order to identify the ground instability phenomena. The exposure corresponds here to the vehicle flow density per road. This value was calculated starting from two models: the first one, based on a source-destination matrix, derived from a demographic map and all points of interest, weighted according to their level of attractiveness; the second one, based on Google Traffic data, takes into account the traffic variability at different times in each day of the week. The workflow automation leads to the risk maps as well as to their web-interactive deployment, allowing at the same time, to select those road segments most susceptible to vulnerability monitoring.  The geoprocessing steps have been significantly automated creating 32 toolboxes through the use of ArcGIS Model Builder and the integration of some original Python scripts, guaranteeing the replicability in other areas and the possibility to update the risk-maps continuously over time.  Finally, the exploitation of the final risk maps has been made available online through a series of WebGIS solutions such as OGC (WMS and WFS) and KML services, cartographic previews through OpenLayers scripts, an ArcGIS Online geoportal, three Android apps, and a website with interactive maps. SGS end-users are private companies and public administrations, which can receive immediate support for the monitoring and territorial planning phases as well as mitigate the risk in the road network.

Next from SGI 2021

Geophysical characterization of Ceppo Lombardo Formation (Po Plain NE of Milan, Italy): new data from passive seismic surveys

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