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In statistical landslide susceptibility evaluation, the quality of the model and its prediction image heavily depends on the quality of the landslide inventories used for calibration. However, regional-scale inventories made available by public territorial administrations are typically affected by an unknown grade of incompleteness and mapping inaccuracy. In this research, a procedure is proposed for verifying and solving such limits by applying a two-step susceptibility modeling procedure. In the Torto River basin (central-northern Sicily, Italy), using an available regional landslide inventory (267 slide and 78 flow cases), two SUFRA_1 models were first prepared and used to assign a landslide susceptibility level to each slope unit (SLU) in which the study area was partitioned. For each of the four susceptibility classes that were obtained, 30% of the mapping units were randomly selected and their stable/unstable status was checked by remote analysis. The new, increased inventories were finally used to recalibrate two SUFRA_2 models. The prediction skills of the SUFRA_1 and SUFRA_2 models were then compared by testing their accuracy in matching landslide distribution in a test sub-basin where a high-resolution systematic inventory had been prepared. According to the results, the strong limits of the SUFRA_1 models (sensitivity: 0.67 and 0.57 for slide and flow, respectively) were largely solved by the SUFRA_2 model (sensitivity: 1 for both slide and flow), suggesting the proposed procedure as a possibly suitable modeling strategy for regional susceptibility studies. [ABSTRACT FROM AUTHOR]

The coastal domain of central western Sicily is characterized by the presence of rocky coasts, which mainly consist of pocket beaches situated between bedrock headlands that constitute ecological niches of great touristic and economic value. In this peculiar morphodynamic system, the sedimentary contributions are mainly derived from the rockfall that affects the back of nearby cliffs or the sediment supply of small streams that flow into it. In this study, we investigated the geomorphological processes and related landforms that contribute to the evolution of a pocket beach area located in a coastal sector of NW Sicily Island. The cliffs in this are affected by several rockfalls, and deposits from these rockfalls also add to the rate of sedimentary contribution. The analysis was conducted through the application of traditional approaches and contemporary methods that have previously been used to forecast the collection of input data in the field, often under difficult conditions due to the accessibility of the sites, and which have been supported by UAV surveys. Through the analysis of the digital models of terrain and orthophotos, geometrical and multitemporal analyses of landforms were carried out. A dedicated software was utilized for the detection of rockfall runout zones and block trajectories and for defining the automatic extraction of rock mass discontinuities. The data were compared with those derived from traditional geomechanical surveys. The availability of the existing and acquired remote sensing data proved essential for this study for both defining the reference geological model and for performing the site-specific analysis of rockfall. [ABSTRACT FROM AUTHOR]

Optimally sizing grid cells is a relevant research issue in landslide susceptibility evaluation. In fact, the size of the adopted mapping units influences several aspects spanning from statistical (the number of positive/negative cases and prevalence and resolution/precision trade-off) and purely geomorphological (the representativeness of the mapping units and the diagnostic areas) to cartographic (the suitability of the obtained prediction images for the final users) topics. In this paper, the results of landslide susceptibility modelling in a 343 km2 catchment for three different types of landslides (rotational/translational slides, slope flows and local flows) using different pixel-size mapping units (5, 8, 10, 16 and 32 m) are compared and discussed. The obtained results show that the higher-resolution model (5 m) did not produce the best performance for any of the landslide typologies. The model with 8 m sized pixels displayed the optimal threshold size for slides and slope flows. In contrast, for local flows, an increasing trend of model prediction accuracy was reached with 32 m pixels, which was a higher value than that presented using 8 m pixels. The variable importance analysis demonstrated that the better performance of the 8 m cells was due to their effectiveness in capturing morphological conditions which favour slope instability (profile curvature and middle and high ridges). [ABSTRACT FROM AUTHOR]

In recent decades, coastal erosion phenomena have increased due to climate change. The increased frequency and intensity of extreme events and the poor sediment supply by anthropized river basins (dams, river weirs, culverts, etc.) have a crucial role in coastal erosion. Therefore, an integrated analysis of coastal erosion is crucial to produce detailed and accurate coastal erosion vulnerability information to support mitigation strategies. This research aimed to assess the erosion vulnerability of the Sicilian coast, also including a validation procedure of the obtained scenario. The coastal vulnerability was computed by means of the CeVI (Coastal Erosion Vulnerability Index) approach, which considers physical indicators such as geomorphology and geology, coastal slope, sea storms, wave maxima energy flux and sediment supply to river mouths. Each indicator was quantified using indexes which were assessed considering transects orthogonal to the coastline in 2020. These transects were clustered inside natural compartments called littoral cells. Each cell was assumed to contain a complete cycle of sedimentation and not to have sediment exchange with the near cells. Physical parameters were identified to define a new erosion vulnerability index for the Sicilian coast. By using physical indexes (geological/geomorphological, erosion/sediment supply, sea storms, etc.), the CeVI was calculated both for each littoral cell and for the transects that fall into retreating/advancing coastal areas. The vulnerability index was then validated by comparing CeVI values and the coastline change over time. The validation study showed a direct link between the coastline retreat and high values of CeVI. The proposed method allowed for a detailed mapping of the Sicilian coastal vulnerability, and it will be useful for coastal erosion risk management purposes. [ABSTRACT FROM AUTHOR]

In landslide susceptibility studies, the type of mapping unit adopted affects the obtained models and maps in terms of accuracy, robustness, spatial resolution and geomorphological adequacy. To evaluate the optimal selection of these units, a test has been carried out in an important catchment of northern Sicily (the Imera River basin), where the spatial relationships between a set of predictors and an inventory of 1608 rotational/translational landslides were analysed using the multivariate adaptive regression splines (MARS) method. In particular, landslide susceptibility models were prepared and compared by adopting four different types of mapping units: the largely adopted grid cells (PX), the typical contributing area–controlled slope units (5000_SLU), the recently optimized parameter-free multiscale slope units (PF_SLU) and a new type (LCL_SLU) of slope unit obtained by crossing classic hydrological partitioning with landform classification. At the same time, once a pixel-based model was prepared, four different SLU modelling strategies were applied to each of the obtained slope unit layers, including two different types of pixel score zoning, a pixel score re-modelling and a factor-based SLU re-modelling. According to the achieved results, LCL_SLUs produced the highest performance and reliability, offering an optimal compromise between the high-performing but scattered and the smoothed but lower-performing prediction images that were obtained from pixel-based and hydrologic SLU–based modelling, respectively. Additionally, among the four adopted SLU modelling strategies, the new proposed procedure, which uses the zoned pixel–based score deciles as the LCL_SLU predictors for a new regression, resulted in the best outstanding performance (ROC_AUC = 0.95). [ABSTRACT FROM AUTHOR]

A map derived by rockfall analysis at Mount Pellegrino is presented herein. The study area is affected by several phenomena of rockfall which caused numerous damage and a strong social and economic impact. Official reports and maps that give a general assessment of rockfall hazard are available in this respect, however, it would be advisable to provide a more specific cartographic support useful for land management and planning. The drafting of new maps showing the rockfall runout areas is an additional tool that may be used in conjunction with the existing maps as a means of risk mitigation and reduction. On the basis of geological, geomorphological, and geomechanical analysis and exploiting the information relating to a landslides inventory obtained by using both analytical and empirical methods, two different rockfall propagation areas were reconstructed. The final thematic map permit to appreciate the differences and similarities between the obtained runout areas. [ABSTRACT FROM AUTHOR]