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Abstract: The present paper describes a multidisciplinary approach to the evaluation of a seismically triggered landslide that occurred in the Cerda area (Italy) on September 6, 2002, about 1 h after an earthquake took place in the south Tyrrhenian Sea. The study was focused on an analysis of the role of the seismic input in triggering the landslide, in view of the evidence that no other mass movement was recorded in the adjacent areas despite geological and geomorphological spatial homogeneity. The studied area is located on a slope of the western flank of the Fiume Imera Settentrionale (Northern Sicily), which is made up of clayey–arenitic rocks. The slope inclines gently but is not uniform due to fluvial, gravitative, and rainwash processes. Field data dealing with global positioning system (GPS), geology, geomorphology, geophysics (vertical electrical sounding, or VES), and geochemistry (soil gas fluxes and composition) were acquired and analysed in order to investigate the cause–effect relationships between the earthquake and the mass movement. The GPS survey allowed us to map the ground failures that have also been classified on the basis of their kinematical meaning (i.e., compressive, distensive, or transcurrent structures). The geological analysis revealed outcropping rocks and tectonic structures. The geomorphologic survey highlighted the presence of preexisting landslide bodies. The geophysical survey detected a buried surface located at a depth of about 100 m . Finally, the geochemical survey showed that the gas released from the displaced mass came from a shallow depth and was not related to any active fault system. The abovementioned information allowed us to interpret the landslide event as a partial reactivation of a preexisting landslide body that was triggered by the earthquake. [Copyright &y& Elsevier]

In the studies of landslide susceptibility assessment, which have been developed in recent years, statistical methods have increasingly been applied. Among all, the BLR (Binary Logistic Regression) certainly finds a more extensive application while MARS (Multivariate Adaptive Regression Splines), despite the good performance and the innovation of the strategies of analysis, only recently began to be employed as a statistical tool for predicting landslide occurrence. The purpose of this research was to evaluate the predictive performance and identify possible drawbacks of the two statistical techniques mentioned above, focusing in particular on the prediction of debris flows. To this aim, an inventory of debris flows triggered by the passage of the hurricane IDA and the low-pressure system associated with it 96E, on 7th and 8th November 2009, in an area of about 26 km2 close to the Caldera Ilopango, El Salvador (CA), was employed. Two validation strategies have been applied to both statistical techniques, thus obtaining four models - BLR (I), MARS (I), BLR (II) and MARS (II) - to be compared in pairs. Model performance was assessed in terms of AUC (area under the receiver operating characteristic (ROC) curve), Sensitivity, Specificity, Positive Prediction Value and Negative Prediction Value. Moreover, to evaluate the robustness of the modelling procedure, 50 replicates were created for each model and standard deviation was calculated for each of them. The results show that both techniques allow for obtaining good or excellent performances so that it is not possible to define one of the two techniques as absolutely better. However, the validation procedure reveals slightly better performance of the MARS models, with greater sensitivity and greater discrimination among True Negatives (TNs). [ABSTRACT FROM AUTHOR]

In landslide susceptibility modeling, the selection of the mapping units is a very relevant topic both in terms of geomorphological adequacy and suitability of the models and final maps. In this paper, a test to integrate pixels and slope units is presented. MARS (Multivariate Adaptive Regression Splines) modeling was applied to assess landslide susceptibility based on a 12 predictors and a 1608 cases database. A pixel-based model was prepared and the scores zoned into 10 different types of slope units, obtained by differently combining two half-basin (HB) and four landform classification (LCL) coverages. The predictive performance of the 10 models were then compared to select the best performing one, whose prediction image was finally modified to consider also the propagation stage. The results attest integrating HB with LCL as more performing than using simple HB classification, with a very limited loss in predictive performance with respect to the pixel-based model. [ABSTRACT FROM AUTHOR]

The results of a geomorphological study carried out in the urban area of Palermo are summarized in a thematic map. Field survey, analysis of aerial photographs and topographic maps, consultation of historical documents and maps, stratigraphic and topographic reconstruction from numerous wells and subsoil data, and bibliographic search were performed, in order to display the geomorphological changes produced by man over time in a densely populated area and to define the Anthropocene of the study area. Palermo town rises along large marine terrace surfaces cut by small river valleys and bordered by wide degraded and abandoned coastal cliffs. Over the last 2700 years, this area was affected by remarkable man-made changes to topographic surface and underground, exposing large areas of the city to hydraulic, sinkhole, and landslide risks, and increasing the levels of seismic susceptibility. In light of these results, the produced map is useful for urban planning studies. [ABSTRACT FROM AUTHOR]

Urban-geomorphology studies in historical cities provide a significant contribution towards the broad definition of the Anthropocene, perhaps even including its consideration as a new unit of geological time. Specific methodological approaches to recognize and map landforms in urban environments, where human-induced geomorphic processes have often overcome the natural ones, are proposed. This paper reports the results from, and comparison of, studies conducted in coastal historical cities facing the core of the Mediterranean Sea – that is, Genoa, Rome, Naples, Palermo (Italy) and Patras (Greece). Their settlements were facilitated by similar climatic and geographical contexts, with high grounds functional for defence, as well as by the availability of rocks useful as construction materials, which were excavated both in opencast and underground quarries. Over centuries, urbanization has also required the levelling of relief, which was performed by the excavation of heights, filling of depressions and by slope terracing. Consequently, highly modified hydrographic networks, whose streams were dammed, diverted, modified in a culvert or simply buried, characterize the selected cities. Their urban growth, which has been driven by maritime commercial activities, has determined anthropogenic coastal progradation through port and defence or waterfront works. Aggradation of artificial ground has also occurred as a consequence of repeated destruction because of both human and natural events, and subsequent reconstruction even over ruins, buried depressions and shallow cavities. As a result, the selected cities represent anthropogenic landscapes that have been predominately shaped by several human-driven processes, sometimes over centuries. Each landform represents the current result, often from multiple activities with opposing geomorphic effects. Beyond academic progress, we believe that detecting and mapping these landforms and processes should be compulsory, even in risk-assessment urban planning, because of the increase of both hazards and vulnerability as a result of climate-change-induced extreme events and extensive urbanization, respectively. [ABSTRACT FROM AUTHOR]

This paper proposes a morphoevolutionary model for western Sicily. Sicily is a chain-foredeep-foreland system still being built, with tectonic activity involving uplift which tends to create new relief. To reconstruct the morphoevolutionary model, geological, and geomorphological studies were done on the basis of field survey and aerial photographic interpretation. The collected data show large areas characterized by specific geological, geomorphological, and topographical settings with rocks, landforms, and landscapes progressively older from south to north Sicily. The achieved results display: (1) gradual emersion of new areas due to uplift, its interaction with the Quaternary glacio- eustatic oscillations of the sea level, and the following production of a flight of stair-steps of uplifted marine terraces in southern Sicily, which migrates progressively upward and inwards; in response to the uplift (2) triggering of down-cutting processes that gradually dismantle the oldest terraces; (3) competition between uplift and down-cutting processes, which is responsible for the genesis of river valleys and isolated rounded hills in central Sicily; (4) continuous deepening over time that results in the exhumation of older and more resistant rocks in northern Sicily, where the higher heights of Sicily are realized and the older forms are retained; (5) extensional tectonic event in the northern end of Sicily, that produces the collapse of large blocks drowned in the Tyrrhenian Sea and sealed by coastal-marine deposits during the Calabrian stage; (6) trigger of uplift again in the previously subsiding blocks and its interaction with coastal processes and sea level fluctuations, which produce successions of marine terraces during the Middle-Upper Pleistocene stages. [ABSTRACT FROM AUTHOR]

Soil erosion by water constitutes a serious problem affecting various countries. In the last few years, a number of studies have adopted statistical approaches for erosion susceptibility zonation. In this study, the Stochastic Gradient Treeboost (SGT) was tested as a multivariate statistical tool for exploring, analyzing and predicting the spatial occurrence of rill–interrill erosion and gully erosion. This technique implements the stochastic gradient boosting algorithm with a tree-based method. The study area is a 9.5 km 2 river catchment located in central-northern Sicily (Italy), where water erosion processes are prevalent, and affect the agricultural productivity of local communities. In order to model soil erosion by water, the spatial distribution of landforms due to rill–interrill and gully erosion was mapped and 12 environmental variables were selected as predictors. Four calibration and four validation subsets were obtained by randomly extracting sets of negative cases, both for rill–interrill erosion and gully erosion models. The results of validation, based on receiving operating characteristic (ROC) curves, showed excellent to outstanding accuracies of the models, and thus a high prediction skill. Moreover, SGT allowed us to explore the relationships between erosion landforms and predictors. A different suite of predictor variables was found to be important for the two models. Elevation, aspect, landform classification and land-use are the main controlling factors for rill–interrill erosion, whilst the stream power index, plan curvature and the topographic wetness index were the most important independent variables for gullies. Finally, an ROC plot analysis made it possible to define a threshold value to classify cells according to the presence/absence of the two erosion processes. Hence, by heuristically combining the resulting rill–interrill erosion and gully erosion susceptibility maps, an integrated water erosion susceptibility map was created. The adopted method offers the advantages of an objective and repeatable procedure, whose result is useful for local administrators to identify the areas that are most susceptible to water erosion and best allocate resources for soil conservation strategies. [ABSTRACT FROM AUTHOR]

A statistical approach was employed to model the spatial distribution of rainfall-triggered landslides in two areas in Sicily (Italy) that occurred during the winter of 2004–2005. The investigated areas are located within the Belice River basin and extend for 38.5 and 10.3 km 2 , respectively. A landslide inventory was established for both areas using two Google Earth images taken on October 25th 2004 and on March 18th 2005, to map slope failures activated or reactivated during this interval. Geographic Information Systems (GIS) were used to prepare 5 m grids of the dependent variables (absence/presence of landslide) and independent variables (lithology and 13 DEM-derivatives). Multivariate Adaptive Regression Splines (MARS) were applied to model landslide susceptibility whereas receiver operating characteristic (ROC) curves and the area under the ROC curve ( AUC ) were used to evaluate model performance. To evaluate the robustness of the whole procedure, we prepared 10 different samples of positive (landslide presence) and negative (landslide absence) cases for each area. Absences were selected through two different methods: (i) extraction from randomly distributed circles with a diameter corresponding to the mean width of the landslide source areas; and (ii) selection as randomly distributed individual grid cells. A comparison was also made between the predictive performances of models including and not including the lithology parameter. The models trained and tested on the same area demonstrated excellent to outstanding fit ( AUC > 0.8). On the other hand, predictive skill decreases when measured outside the calibration area, although most of the landslides occur where susceptibility is high and the overall model performance is acceptable ( AUC > 0.7). The results also showed that the accuracy of the landslide susceptibility models is higher when lithology is included in the statistical analysis. Models whose absences were selected using random circles showed a significantly better performance when learning and validation samples were extracted from the same area; whereas, conversely, no significant difference was observed when testing the models outside the training area. [ABSTRACT FROM AUTHOR]

In this paper, terrain susceptibility to earth-flow occurrence was evaluated by using geographic information systems (GIS) and two statistical methods: Logistic regression (LR) and multivariate adaptive regression splines (MARS). LR has been already demonstrated to provide reliable predictions of earth-flow occurrence, whereas MARS, as far as we know, has never been used to generate earth-flow susceptibility models. The experiment was carried out in a basin of western Sicily (Italy), which extends for 51 km 2 and is severely affected by earth-flows. In total, we mapped 1376 earth-flows, covering an area of 4.59 km 2 . To explore the effect of pre-failure topography on earth-flow spatial distribution, we performed a reconstruction of topography before the landslide occurrence. This was achieved by preparing a digital terrain model (DTM) where altitude of areas hosting landslides was interpolated from the adjacent undisturbed land surface by using the algorithm topo-to-raster. This DTM was exploited to extract 15 morphological and hydrological variables that, in addition to outcropping lithology, were employed as explanatory variables of earth-flow spatial distribution. The predictive skill of the earth-flow susceptibility models and the robustness of the procedure were tested by preparing five datasets, each including a different subset of landslides and stable areas. The accuracy of the predictive models was evaluated by drawing receiver operating characteristic (ROC) curves and by calculating the area under the ROC curve (AUC). The results demonstrate that the overall accuracy of LR and MARS earth-flow susceptibility models is from excellent to outstanding. However, AUC values of the validation datasets attest to a higher predictive power of MARS-models (AUC between 0.881 and 0.912) with respect to LR-models (AUC between 0.823 and 0.870). The adopted procedure proved to be resistant to overfitting and stable when changes of the learning and validation samples are performed. In conclusion, the highly acceptable predictive skill of the statistical models confirms the reliability of the procedure adopted to reconstruct the pre-failure topographic conditions. Such a method solves the conceptual problem arising when post-failure elevation data are the only source of topographic information available to model landslide susceptibility. Furthermore, with respect to other solutions proposed in the past, which identify as unstable the conditions of landslide surroundings, our approach allows for more accurate measurement of those variables (e.g. curvature, convergence index, topographic position index) that depend on the relative position of a cell with respect to its nearby pixels. [ABSTRACT FROM AUTHOR]

Abstract: This research aims at characterizing susceptibility conditions to gully erosion by means of GIS and multivariate statistical analysis. The study area is a 9.5km2 river catchment in central-northern Sicily, where agriculture activities are limited by intense erosion. By means of field surveys and interpretation of aerial images, we prepared a digital map of the spatial distribution of 260 gullies in the study area. In addition, from available thematic maps, a 5m cell size digital elevation model and field checks, we derived 27 environmental attributes that describe the variability of lithology, land use, topography and road position. These attributes were selected for their potential influence on erosion processes, while the dependent variable was given by presence or absence of gullies within two different types of mapping units: 5m grid cells and slope units (average size=2.66ha). The functional relationships between gully occurrence and the controlling factors were obtained from forward stepwise logistic regression to calculate the probability to host a gully for each mapping unit. In order to train and test the predictive models, three calibration and three validation subsets, of both grid cells and slope units, were randomly selected. Results of validation, based on ROC (receiving operating characteristic) curves, attest for acceptable to excellent accuracies of the models, showing better predictive skill and more stable performance of the susceptibility model based on grid cells. [Copyright &y& Elsevier]

Abstract: This work deals with an integrated geomorphological and chemical–physical study of “calanchi” landforms in two sites (Ottosalme and Catalfimo) of NW Sicily (southern Italy), developed on dominant silty-clay deposits. The calanchi fronts are characterized by different morphological features and dominant geomorphic processes. Sharp knife-edged ridges and concentrated water runoff dominate at Ottosalme, and smoother landforms affected by mass movements (mud flows and translational slides) prevail at Catalfimo. We focused on some geochemical and physical parameters such as pH, total dissolved salts, sodium adsorption ratio (SAR), porosity, plastic and liquid limits as possible causes of the above differences, with special emphasis on their role in discriminating the behavior of peculiar microforms, such as a weathered outer crust and the corresponding inner massive portion (unweathered substrate). Our results show that the main chemical–physical features of calanchi morphologies and microforms often display no clear correlations with respect to those reported in the existing literature, pointing to a higher complexity of patterns and behaviors. In particular, all samples consist of dispersive material (SAR values>10), but a more plastic and liquid behavior at Catalfimo can explain a higher occurrence of landslides and smoother morphology than at Ottosalme. Higher SAR values at Ottosalme well explain the dominance of concentrated water erosion. The chemical behavior of the studied microforms is better described by pH being alkaline with higher values in the inner substrate than the outer crust, and appears to minimize the effects of all other parameters and their responses to other external controlling factors. Lower SAR values in the crust suggest that clay dispersivity is not the prominent factor controlling its surface detachment and mobility downslope, which is more likely promoted by its higher porosity and consequent water absorption than the inner portion, with changes in the saturation state, shear strength and water pressure. [Copyright &y& Elsevier]