Search

This paper presents the results obtained by an audio-magnetotelluric (AMT) survey carried out crossing the western sector of Montemurro village (Southern Italy) affected by an intense hydrogeological instability. The AMT investigation was aimed to settle the question concerning the possible prosecution toward SE of the Eastern Agri Fault System whose surficial evidences could be blinded by extensive landslides phenomena and by anthropization of the territory. The AMT profile was oriented in NE-SW direction, orthogonal to the main geological structures of the investigated area. It crossed longitudinally the area affected by instability. The AMT model provides new insights on already known faults (i.e. Montemurro Faults) and imaged their in-depth immersion thus answering to still open geological question in the investigated areas. Furthermore, the high resolution of the model allowed the imaging of the boundaries, in terms of resistivity contrast, between material affected/unaffected by the sliding dynamics or characterized by an higher water content. The results provide new knowledge about the geological and geoelectrical structures in the area. They will be fully integrated with the results of the on-going research activities in the area and will represent an additional step for the multiscale and multiparametrical characterization of the Agri Valley geological setting. [ABSTRACT FROM AUTHOR]

This paper presents the results obtained by the elaboration of an artificial neuronal network for the creation of a rockfall susceptibility map. The analysis was carried out by analysing the predisposing and triggering factors of the rockfall phenomenon. The parameters considered for this study and representing the input data of the artificial neural network are factors such as: gradient, soil use, lithology, rockfall source areas and kinetic energy values obtained by considering the probable pathways of the blocks through simulations with dedicated softwares, DEMs and niches of the rockfalls that have already occurred in the past. The processing of this data (required in a versatile dedicated software for the realization of the artificial neural network in ASCII format) is done using GIS softwares, useful tools for the creation of hazard maps. An important step is the realization of the rockfall inventory map: it allows to identify the training set (consisting of 50% of the pixels relative to the rockfall niches) for the network training and the testing set (considering the remaining 50% of the pixels relative to the rockfall niches) to assess the network accuracy by overlaying the rockfall niches belonging to the testing set with the obtained susceptibility map. [ABSTRACT FROM AUTHOR]