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"Messina (Italy)"
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Fault lines
Earth's fractured geology is visible in its fault lines. It is along these lines that earthquakes occur, sometimes with disastrous effects. These disturbances can significantly influence urban development, as seen in the aftermath of two earthquakes in Messina, Italy, in 1908 and in the Belice Valley, Sicily, in 1968. Following the history of these places before and after their destruction, this book explores plans and developments that preceded the disasters and the urbanism that emerged from the ruins. These stories explore fault lines between \"rural\" and \"urban,\" \"backwardness\" and \"development,\" and \"before\" and \"after,\" shedding light on the role of environmental forces in the history of human habitats.
eBook
Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy)
Debris flows are among the most hazardous phenomena in nature, requiring the preparation of susceptibility models in order to cope with this severe threat. The aim of this research was to verify whether a grid cell-based susceptibility model was capable of predicting the debris-flow initiation sites in the Giampilieri catchment (10 km
2
), which was hit by a storm on the 1st October 2009, resulting in more than one thousand landslides. This kind of event is to be considered as recurrent in the area as attested by historical data. Therefore, predictive models have been prepared by using forward stepwise binary logistic regression (BLR), a landslide inventory and a set of geo-environmental attributes as predictors. In particular, the effects produced in the quality of the predictive models by changing the grid cell size (2, 4, 16 and 32 m) have been explored in terms of predictive performance, robustness, importance and role of the selected predictors. The results generally attested for high predictive performances of the 2, 8 and 16 m model sets (AUROC > 0.8), with the latter producing slightly better predictions and the 32 m showing the worst yet still acceptable performance and the lowest robustness. As regards the predictors, although all the 4 sets of models share a common group (topographic attributes, outcropping lithology and land use), the similarity resulted higher between the 8 and 16 m sets. The research demonstrates that no meaningful loss in the predictive performance arises by adopting a coarser cell size for the mapping unit. However, the largest adopted cell size resulted in marginally worse model performance, with AUROC slightly below 0.8 and error rates above 0.3.
Journal Article
Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messina (Sicily, southern Italy)
This study aims to compare binary logistic regression (BLR) and stochastic gradient treeboost (SGT) methods in assessing landslide susceptibility within the Mediterranean region for multiple-occurrence regional landslide events. A test area was selected in the north-eastern sector of Sicily (southern Italy) where thousands of debris flows and debris avalanches triggered on the first October 2009 due to an extreme storm. Exploiting the same set of predictors and the 2009 event landslide archive, BLR- and SGT-based susceptibility models have been obtained for the two catchments separately, adopting a random partition (RP) technique for validation. In addition, the models trained in one catchment have been tested in predicting the landslide distribution in the second, adopting a spatial partition (SP)-based validation. The models produced high predictive performances with a general consistency between BLR and SGT in the susceptibility maps, predictor importance and role. In particular, SGT models reached a higher prediction performance with respect to BLR models for RP-modelling, while for the SP-based models, the difference in predictive skills dropped, converging to equally excellent performances. However, analysing the precision of the probability estimates, BLR produced more robust models around the mean value for each pixel, indicating possible overfitting effects, which affect decision trees to a greater extent. The assessment of the predictor roles allowed identifying the activation mechanisms which are primarily controlled by steep south-facing open slopes located near the coastal area. These slopes are characterised by low/middle altitude downhill from mountain tops, having a medium-grade metamorphic bedrock, under grassland and cultivated (terraced) uses.
Journal Article
Debris and mud flows runout assessment: a comparison among empirical geometric equations in the Giampilieri and Briga basins (east Sicily, Italy) affected by the event of October 1, 2009
Empirical/geometric methods rely on simple geometrical connections between some landslide parameters and the runout distance reached by the displaced material. Despite the extreme simplification of the dynamic of this landslide typology, those methods can provide useful information about the propagation of this shallow and fast landslide typology, joining the reliability of the results with easiness of use. The objective of this work is to compare the efficacy of different geometric relationships for the identification of the runout distances in a debris- and mud-flows-prone test area located in Sicily, southern Italy, where several events were analyzed, and a consistent set of data was collected and processed. Notwithstanding some uncertainties in the methodological approach and not negligible scattering between expected and observed runout distances, the use of such geometric approaches, together with the evaluation of kinematic parameters such as velocity and kinetic energy, can significantly boost the implementation of site-specific analyses for a more detailed definition of landslides susceptibility at a local scale.
Journal Article
Much ado about nothing
A comic book version of Shakespeare's comedy about mistaken identities, games, eavesdropping, and unrequited love.
BOOK
A simplified semi-quantitative procedure based on the SLIP model for landslide risk assessment: the case study of Gioiosa Marea (Sicily, Italy)
Landslide risk assessment is fundamental in identifying risk areas, where mitigation measures must be introduced. Most of the existing methods are based on susceptibility assessment strongly site-specific and require information often unavailable for damage quantification. This study proposes a simplified methodology, specific for rainfall-induced shallow landslides, that tries to overcome both these limitations. Susceptibility assessed from a physically-based model SLIP (shallow landslides instability prediction) is combined with distance derived indices representing the interference probability with elements at risk in the anthropized environment. The methodology is applied to Gioiosa Marea municipality (Sicily, south Italy), where shallow landslides are often triggered by rainfall causing relevant social and economic damage because of their interference with roads. SLIP parameters are first calibrated to predict the spatial and temporal occurrence of past surveyed phenomena. Susceptibility is then assessed in the whole municipality and validated by comparison with areas affected by slide movements according to the regional databases of historical landslides. It is shown that all the detected areas are covered by points where the SLIP safety factor ranges between 0 and 2. Risk is finally assessed after computation of distances from elements at risk, selected from the land use map. In this case, results are not well validated because of lack of details in the available regional hydrogeological plan, both in terms of extension and information. Further validation of the proposed interference indices is required, e.g., with studies of landslide propagation, which can also allow considerations on the provoked damage.
Journal Article