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This paper illustrates the quantitative estimation of specific risk (i.e., the product of hazard and vulnerability) for 39 buildings located upon the Ancona landslide based on the characterization of landslide kinematics presented in a companion paper. Hazard is quantified based on intensity, intended as the damaging potential of the kinetic and/or geometric attributes of the landslide, and is expressed in terms of expected exceedance of preset cumulative displacement thresholds for a set of five reference time intervals, ranging from 1 to 100 years. The estimation of hazard relies sequentially on (1) Monte Carlo simulation of displacement series, with sampling distributions of average yearly displacement defined on the basis of the statistical processing of inclinometer and radar interferometer data; and (2) the subsequent spatialization of displacement using radial basis interpolation as described in the companion paper. The vulnerability of the set of buildings relies on a quantitative model in which vulnerability is a function of landslide intensity and the resilience of the buildings. Resilience is a function of a set of indicators including structural type, age, and foundation type and is temporally variable due to the progressive structural degradation. Hazard, vulnerability, and specific risk are estimated for the set of five aforementioned reference time intervals. The magnitude and temporal dependence of hazard, vulnerability, and specific risk are assessed critically. [ABSTRACT FROM AUTHOR]

The Ancona landslide is a complex, deep-seated landslide displaying composite rotational-translational kinematisms and affecting a large urban area in the Ancona municipality on the Adriatic coast of central Italy. The landslide was reactivated with a large and destructive event on 13 December 1982 following a long period of precipitation and has remained active since. This paper focuses on the estimation of the landslide kinematics (more specifically, the horizontal and vertical components of average yearly velocity) for subsequent estimation of risk for a set of 39 buildings as presented in a companion paper. The study relies both on the processing of inclinometer and radar interferometer monitoring data through statistical procedures. Triggering factors are not investigated. Outputs from the two sets of monitoring data are compared quantitatively and qualitatively. The inherent limitations in available data are discussed. The validity of the quantitative results in the context of the risk estimation effort is discussed. [ABSTRACT FROM AUTHOR]

The geometric and kinematic characterization of landslides affecting urban areas is a challenging goal that is routinely pursued via geological/geomorphological method and monitoring of ground displacements achieved by geotechnical and, more recently, advanced differential interferometric synthetic aperture radar (A-DInSAR) data. Although the integration of all the above-mentioned methods should be planned a priori to be more effective, datasets resulting from the independent use of these different methods are commonly available, thus making crucial the need for their standardized a posteriori integration. In this regard, the present paper aims to provide a contribution by introducing a procedure that, taking into account the specific limits of geological/geomorphological analyses and deep/surface ground displacement monitoring via geotechnical and A-DInSAR data, allows the a posteriori integration of the results by exploiting their complementarity for landslide characterization. The approach was tested in the urban area of Lungro village (Calabria region, southern Italy), which is characterized by complex geological/geomorphological settings, widespread landslides and peculiar urban fabric. In spite of the different level of information preliminarily available for each landslide as result of the independent use of the three methods, the implementation of the proposed procedure allowed a better understanding and typifying of the geometry and kinematics of 50 landslides. This provided part of the essential background for geotechnical landslide models to be used for slope stability analysis within landslide risk mitigation strategies. [ABSTRACT FROM AUTHOR]