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We use high-resolution electrical resistivity imaging to delineate the geometry of complex landslides in the Lucanian Apennine chain of southern Italy, to identify the discontinuity between the landslide material and bedrock, and to locate possible surfaces of reactivation. The Lucanian Apennine chain is characterized by high hydrogeological hazard and shows a complete panorama of mass movements. In this area, all typologies of landslides markedly predisposed and tightly controlled by the geostructural characteristics, are found: rotational and translational slides, rototranslational slides, earth and mudflows, as well as deep-seated gravitational slope phenomena with a predominance of rototranslational slides evolving as earthflow slides. Three test sites, characterized by complex geology and a high hydrogeologic hazard, are studied. The Giarrossa and Varco Izzo earthflow slides are located to the west and east of the town of Potenza, whereas the Latronico slide is located close to the town of Latronico. Electrical images are produced from dipole-dipole geoelectric data acquired along arrays spanning selected profiles positioned perpendicular and parallel to the landslide bodies. High-resolution electrical resistivity images are attained through the use of geologic and borehole constraints in the interpretation phase. Integration and comparison of our results with other geophysical data delineate the geometries and hydrologic characteristics of the landslide structures.

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For those working in the field of landslide prevention, the estimation of hazard levels and the consequent production of thematic maps are principal objectives. They are achieved through careful analytical studies of the characteristics of landslide prone areas, thus, providing useful information regarding possible future phenomena. Such maps represent a fundamental step in the drawing up of adequate measures of landslide hazard mitigation. However, for a complete estimation of landslide hazard, meant as the degree of probability that a landslide occurs in a given area, within a given space of time, detailed and uniformly distributed data regarding their incidence and causes are required. This information, while obtainable through laborious historical research, is usually partial, incomplete and uneven, and hence, unsatisfactory for zoning on a regional scale. In order to carry this out effectively, the utilization of spatial estimation of the relative levels of landslide hazard in the various areas was considered opportune. These areas were classified according to their levels of proneness to landslide activity without taking recurrence periods into account. Various techniques were developed in order to obtain upheaval numerical estimates. The method used in this study, which was applied in the area of Potenza, is based on techniques derived from artificial intelligence (Artificial Neural Network - ANN). This method requires the definition of appropriate thematic layers, which parameterize the area under study. These are recognized by means of specific analyses in a functional relationship to the event itself. The parameters adopted are: slope gradient, slope aspect, topographical index, topographical shape, elevation, land use and lithology

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Abstract.The objectives of spatial planning should include the definition and assessment of possible mitigation strategies regarding the effects of natural hazards on the surrounding territory. Unfortunately, however, there is often a lack of adequate tools to provide necessary support to the local bodies responsible for land management. This paper deals with the conception, the development and the validation of an integrated numerical model for assessing systemic vulnerability in complex and urbanized landslide-prone areas. The proposed model considers this vulnerability not as a characteristic of a particular element at risk, but as a peculiarity of a complex territorial system, in which the elements are reciprocally linked in a functional way. It is an index of the tendency of a given territorial element to suffer damage (usually of a functional kind) due to its interconnections with other elements of the same territorial system. The innovative nature of this work also lies in the formalization of a procedure based on a network of influences for an adequate assessment of such "systemic" vulnerability.This approach can be used to obtain information which is useful, in any given situation of a territory hit by a landslide event, for the identification of the element which has suffered the most functional damage, ie the most "critical" element and the element which has the greatest repercussions on other elements of the system and thus a "decisive" role in the management of the emergency.This model was developed within a GIS system through the following phases:1. the topological characterization of the territorial system studied and the assessment of the scenarios in terms of spatial landslide hazard. A statistical method, based on neural networks was proposed for the assessment of landslide hazard;Correspondence to: F. Sdao (francesco.sdao@unibas.it)2. the analysis of the direct consequences of a scenario event on the system; 3. the definition of the assessment model of systemic vulnerability in landslide-prone areas.To highlight the potentialities of the proposed approach we have described a specific case study of landslide hazard in the local council area of Potenza.