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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]

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 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]

Slope stability is influenced by a number of factors that modify the resisting/acting force ratio control landslide initiation and movement velocity. Among these, artificial vibrations have been identified as an important degrading factor for soil strength, but it is not fully clear if they can trigger or modulate movements of clay landslides. To contribute to a better understanding of the potential effect of vibrations on landslide movement, also in terms of boundary conditions, we analyzed monitoring data acquired at the toe of the Pietrafitta landslide in southern Italy. This landslide adjoins the SS87 national road that suffered periodic closure due to landslide activity and in April 2016 operates daytime only for risk mitigation purpose. This condition promoted a better identification of a potential cause-effect relation between traffic vibration and landslide movement. Results from data analysis and landslide modeling suggest that in condition of incipient movement, artificial vibrations, also of limited amplitude, are able to directly initiate clay landslide movement that due to the viscous nature of the involved material exhibit a specific displacement pattern that is not consistent with a sliding block model. [ABSTRACT FROM AUTHOR]

The morphological changes of unstable areas can be identified using different methodologies that allow repeated surveys over time. The integration between the data obtained from different remote sensing and ground-based techniques, characterized by different coverage, resolution, and precision, allows to describe the kinematic motion of landslides with high accuracy and details. The aim of this work is to monitor the displacements of the Patigno landslide, a deep-seated gravitational slope deformation located in the Northern Apennines (Zeri, Massa Carrara, Italy), using archival aerial photogrammetry (1975–2010), continuous GNSS observations (2004–2018), and multi-temporal InSAR data (2015–2019). The results obtained adopting the different techniques were cross-validated and integrated in order to better explain the kinematics of the landslides: the GNSS data analysis shows horizontal movements of about 43 mm/yr in the S-E direction and vertical deformations of 6.5 mm/yr, in agreement with the average displacement rates obtained from photogrammetry and InSAR processing. The analysis of multi-temporal aerial photogrammetric images allowed us to observe three sectors of the landslide body characterized by different velocities rates and planimetric directions, in agreement with the LOS InSAR displacement field. Furthermore, the correlation between the rainfall distribution and the GNSS time series shows an acceleration of the sliding movements after about 3–4 months of a strong rainfall period. This integrated approach allowed us to overcome the limitations of each technique and to provide a 44-year long monitoring of the Patigno landslide. We also show that a synergic use of ground-based and remote sensing methodologies can provide useful information for the planning of more effective landslide risk mitigation strategies. [ABSTRACT FROM AUTHOR]