Anthropogenic sinkholes of the city of Naples, Italy: an update

In recent years, the study of anthropogenic sinkholes in densely urbanized areas has attracted the attention of both researchers and land management entities. The city of Naples (Italy) has been frequently affected by processes generating such landforms in the last decades: for this reason, an update of the sinkhole inventory and a preliminary susceptibility estimation are proposed in this work. Starting from previous data, not modified since 2010, a total of 270 new events occurred in the period February 2010–June 2021 were collected through the examination of online newspapers, local daily reports, council chronicle news and field surveys. The final consistence of the updated inventory is of 458 events occurred between 1880 and 2021, distributed through time with an increasing trend in frequency. Spatial analysis of sinkholes indicates a concentration in the central sector of the city, corresponding to its ancient and historic centre, crossed by a dense network of underground tunnels and cavities. Cavity-roof collapse is confirmed as one of the potential genetic types, along with processes related to rainfall events and service lines damage. A clear correlation between monthly rainfall and the number of triggered sinkholes was identified. Finally, a preliminary sinkhole susceptibility assessment, carried out by Frequency Ratio method, confirms the central sector of city as that most susceptible to sinkholes and emphasizes the predisposing role of service lines, mostly in the outermost areas of the city

Rainfall-Induced Shallow Landslide Detachment, Transit and Runout Susceptibility Mapping by Integrating Machine Learning Techniques and GIS-Based Approaches

Rainfall-induced shallow landslides represent a serious threat in hilly and mountain areas around the world. The mountainous landscape of the Cinque Terre (eastern Liguria, Italy) is increasingly popular for both Italian and foreign tourists, most of which visit this outstanding terraced coastal landscape to enjoy a beach holiday and to practice hiking. However, this area is characterized by a high level of landslide hazard due to intense rainfalls that periodically affect its rugged and steep territory. One of the most severe events occurred on 25 October 2011, causing several fatalities and damage for millions of euros. To adequately address the issues related to shallow landslide risk, it is essential to develop landslide susceptibility models as reliable as possible. Regrettably, most of the current land-use and urban planning approaches only consider the susceptibility to landslide detachment, neglecting transit and runout processes. In this study, the adoption of a combined approach allowed to estimate shallow landslide susceptibility to both detachment and potential runout. At first, landslide triggering susceptibility was assessed using Machine Learning techniques and applying the Ensemble approach. Nine predisposing factors were chosen, while a database of about 300 rainfall-induced shallow landslides was used as input. Then, a Geographical Information System (GIS)-based procedure was applied to estimate the potential landslide runout using the “reach angle” method. Information from such analyses was combined to obtain a susceptibility map describing detachment, transit, and runout. The obtained susceptibility map will be helpful for land planning, as well as for decision makers and stakeholders, to predict areas where rainfall-induced shallow landslides are likely to occur in the future and to identify areas where hazard mitigation measures are needed

Monitoring and 3D surveys for the safety fruition of a hypogeum site

The metropolitan area of Napoli (Italy) is characterized by a subsoil rich in cavities and tunnels, initially born as material quarries present in all architectural contexts of Campania. The cavities were reused in later times for different purposes: mainly funeral and burial activities since the Hellenistic revival during the Roman period and later during the Christian era although, in the latter case, the catacombs were even used as place for worshipping functions. Religious activities were not the only reuse for these underground cavities as they were used as aqueducts and tunnels. This underground network of tunnels and cavities includes the numerous archaeological quarries and constitute a patrimony to preserve and enhance. The current use of the Naples underground is cultural tourism, which involves a very high annual passage of visitors in environments that need maximum structural safety. And essential, in order to ensure the safety fruition of the site, assess their stability conditions. In this paper we report the multidisciplinary investigations carried out on an ancient tuff quarry, known as Cimitero delle Fontanelle, in Napoli. In detail the result of diagnostic surveys, geological and geotechnical investigations, and the set-up of monitoring system in order to plan scheduled maintenance were discussed, starting from the previous works carried out in order to design the remedial measure necessary to reopen the tourist site in safety

Comparison of two machine learning algorithms for anthropogenic sinkhole susceptibility assessment in the city of Naples (Italy)

Sinkholes are common phenomena in the world that occur as a result of collapse processes due to natural and/or anthropogenic causes. Sinkholes consist of three-dimensional funnel-shaped depressions, predominantly circular on the surface, deep from centimeters to several meters. Sinkholes in urban areas, also called “anthropogenic” sinkholes, can be very dangerous from an engineering point of view, causing instability or damaging buildings and infrastructures or even leading to the death of people. In Naples (Italy), the presence of a dense underground cavity network, generated as a result of ancient and historical quarrying of bedrock volcanic tuff (used as building material), promotes the generation of sinkholes occurrence. In this work, sinkhole susceptibility analysis was conducted for the production and the comparison of two different sinkhole susceptibility maps by means of statistical-based algorithms (Random Forest and Maximum Entropy). Twelve environmental variables have been used for the susceptibility assessment, such as groundwater depth, bedrock depth and maps of density and distance from different predisposing factors (aqueducts, roads, sewers, anthropic cavities and underground railroad networks). Both produced maps present good predictive performance and indicate a very high sinkhole susceptibility in the city center of Naples, in agreement with the high density of underground cavities, supporting the importance of the latter as predisposing factor. The road network, considered in this work as representative of secondary aqueduct and sewer systems generally located under such infrastructures, also appears to be an important variable. This study aims to represent a useful tool to improve the development of sinkhole susceptibility maps and to support the local government to protect its cultural heritage