Veronica Tofani

Recommendations for the quantitative analysis of landslide risk

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

Persistent Scatterer Interferometry (PSI) Technique for Landslide Characterization and Monitoring

: The measurement of landslide superficial displacement often represents the most effective method for defining its behavior, allowing one to observe the relationship with triggering factors and to assess the effectiveness of the mitigation measures. Persistent Scatterer Interferometry (PSI) represents a powerful tool to measure landslide displacement, as it offers a synoptic view that can be repeated at different time intervals and at various scales. In many cases, PSI data are integrated with in situ monitoring instrumentation, since the joint use of satellite and ground-based data facilitates the geological interpretation of a landslide and allows a better understanding of landslide geometry and kinematics. In this work, PSI interferometry and conventional ground-based monitoring techniques have been used to characterize and to monitor the Santo Stefano d’Aveto landslide located in the Northern Apennines, Italy. This landslide can be defined as an earth rotational slide. PSI analysis has contributed to a more in-depth investigation of the phenomenon. In particular, PSI measurements have allowed better redefining of the boundaries of the landslide and the state of activity, while the time series analysis has permitted better understanding of the deformation pattern and its relation with the causes of the landslide itself. The integration of ground-based monitoring data and PSI data have provided sound results for landslide characterization. The punctual information deriving from inclinometers can help in defining the actual location of the sliding surface and the involved volumes, while the measuring of pore water pressure conditions or water table level can suggest a correlation between the deformation patterns and the triggering factors.

Persistent Scatterers Interferometry Hotspot and Cluster Analysis PSI-HCA for detection of extremely slow-moving landslides

The synthetic aperture radar (SAR) interferometry (InSAR) technique has already shown its importance in landslide mapping and monitoring applications. However, the usefulness of traditional differential InSAR applications is limited by disturbing factors such as temporal decorrelation and atmospheric disturbances. The Persistent Scatterers Interferometry (PSI) technique is a recently developed InSAR approach. It generates stable radar benchmarks (namely persistent scatterers, PSI point targets) using a multi-interferogram analysis of SAR images. The PSI technique has the advantage of reducing temporal decorrelation and atmospheric artefacts. The PSI technique is suitable for the investigation of extremely slow-moving landslides due to its capability to detect ground displacements with millimetre precision. However, the interpretation of PSI outputs is sometimes difficult for the large number of possible persistent scatterers (PSs). A new approach of PSI Hotspot and Cluster Analysis (PSI-HCA) is introduced here in order to develop a procedure for mapping landslides efficiently and automatically. This analysis has been performed on PSs in hilly and mountainous areas within the Arno river basin (Italy). The aim is to use PSs processed from 4 years (2003–2006) of Radarsat images for identifying areas preferentially affected by extremely slow-moving landslides. The Getis–Ord Gi * statistic is applied in the study for the PSI-HCA approach. The velocity of PSs is used as weighting factor and the Gi * index is calculated for each single point target. The results indicate that both high positive and low negative Gi * values imply the clustering of potential mass movements. High positive values suggest the moving direction towards the sensor along the satellite line-of-sight (LOS), whereas low negative values imply the movement away from the sensor. Furthermore, the kernel function is used to estimate PS density based on these derived Gi * values. The output is a hotspot map which highlights active mass movements. This spatial statistic approach of PSI-HCA is considered an effective way to extract useful information from PSs at a regional scale, thus providing an innovative approach for rapid mapping of extremely slow-moving landslides over large areas.

Quantitative hazard and risk assessment for slow-moving landslides from Persistent Scatterer Interferometry

Preparation of reliable landslide hazard and risk maps is crucial for hazard mitigation and risk management. In recent years, various approaches have been developed for quantitative assessment of landslide hazard and risk. However, possibly due to the lack of new data, very few of these hazard and risk maps were updated after their first generation. In this study, aiming at an ongoing assessment, a novel approach for updating landslide hazard and risk maps based on Persistent Scatterer Interferometry (PSI) is introduced. The study was performed in the Arno River basin (central Italy) where most mass movements are slow-moving landslides which are properly within the detection precision of PSI point targets. In the Arno River basin, the preliminary hazard and risk assessment was performed by Catani et al. (Landslides 2:329–342, 2005) using datasets prior to 2002. In this study, the previous hazard and risk maps were updated using PSI point targets processed from 4 years (2003–2006) of RADARSAT images. Landslide hazard and risk maps for five temporal predictions of 2, 5, 10, 20 and 30 years were updated with the exposure of losses estimated in Euro (€). In particular, the result shows that in 30 years a potential loss of approximate €3.22 billion is expected due to these slow-moving landslides detected by PSI point targets.

GIS techniques for regional-scale landslide susceptibility assessment: the Sicily (Italy) case study

This study describes the assessment of landslide susceptibility in Sicily (Italy) at a 1:100,000 scale using a multivariate logistic regression model. The model was implemented in a GIS environment by using the ArcSDM (Arc Spatial Data Modeller) module, modified to develop spatial prediction through regional data sets. A newly developed algorithm was used to automatically extract the detachment area from mapped landslide polygons. The following factors were selected as independent variables of the logistic regression model: slope gradient, lithology, land cover, a curve number derived index and a pluviometric anomaly index. The above-described configuration has been verified to be the best one among others employing from three to eight factors. All the regression coefficients and parameters were calculated using selected landslide training data sets. The results of the analysis were validated using an independent landslide data set. On an average, 82% of the area affected by instability and 79% of the not affected area were correctly classified by the model, which proved to be a useful tool for planners and decision-makers.

Spaceborne, UAV and ground-based remote sensing techniques for landslide mapping, monitoring and early warning

BackgroundThe current availability of advanced remote sensing technologies in the field of landslide analysis allows for rapid and easily updatable data acquisitions, improving the traditional capabilities of detection, mapping and monitoring, as well as optimizing fieldwork and investigating hazardous or inaccessible areas, while granting at the same time the safety of the operators. Among Earth Observation (EO) techniques in the last decades optical Very High Resolution (VHR) and Synthetic Aperture Radar (SAR) imagery represent very effective tools for these implementations, since very high spatial resolution can be obtained by means of optical systems, and by the new generations of sensors designed for interferometric applications. Although these spaceborne platforms have revisiting times of few days they still cannot match the spatial detail or time resolution achievable by means of Unmanned Aerial Vehicles (UAV) Digital Photogrammetry (DP), and ground-based devices, such as Ground-Based Interferometric SAR (GB-InSAR), Terrestrial Laser Scanning (TLS) and InfraRed Thermography (IRT), which in the recent years have undergone a significant increase of usage, thanks to their technological development and data quality improvement, fast measurement and processing times, portability and cost-effectiveness. In this paper the potential of the abovementioned techniques and the effectiveness of their synergic use is explored in the field of landslide analysis by analyzing various case studies, characterized by different slope instability processes, spatial scales and risk management phases.ResultsSpaceborne optical Very High Resolution (VHR) and SAR data were applied at a basin scale for analysing shallow rapid-moving and slow-moving landslides in the emergency management and post- disaster phases, demonstrating their effectiveness for post-disaster damage assessment, landslide detection and rapid mapping, the definition of states of activity and updating of landslide inventory maps. The potential of UAV-DP for very high resolution periodical checks of instability phenomena was explored at a slope-scale in a selected test site; two shallow landslides were detected and characterized, in terms of areal extension, volume and temporal evolution. The combined use of GB-InSAR, TLS and IRT ground based methods, was applied for the surveying, monitoring and characterization of rock slides, unstable cliffs and translational slides. These applications were evaluated in the framework of successful rapid risk scenario evaluation, long term monitoring and emergency management activities. All of the results were validated by means of field surveying activities.ConclusionThe attempt of this work is to give a contribution to the current state of the art of advanced spaceborne and ground based techniques applied to landslide studies, with the aim of improving and extending their investigative capacity in the framework of a growing demand for effective Civil Protection procedures in pre- and post-disaster initiatives. Advantages and limitations of the proposed methods, as well as further fields of applications are evaluated for landslide-prone areas.

Integration of Remote Sensing Techniques for Intensity Zonation within a Landslide Area: A Case Study in the Northern Apennines, Italy

This paper describes the application of remote sensing techniques, based on SAR interferometry for the intensity zonation of the landslide affecting the Castagnola village (Northern Apennines of Liguria region, Italy). The study of the instability conditions of the landslide started in 2001 with the installation of conventional monitoring systems, such as inclinometers and crackmeters, ranging in time from April 2001 to April 2002, which allowed to define the deformation rates of the landslide and to locate the actual landslide sliding surface, as well as to record the intensity of the damages and cracks affecting the buildings located within the landslide perimeter. In order to investigate the past long-term evolution of the ground movements a PSI (Persistent Scatterers Interferometry) analysis has been performed making use of a set of ERS1/ERS2 images acquired in 1992–2001 period. The outcome of the PSI analysis has allowed to confirm the landslide extension as mapped within the official landslide inventory map as well as to reconstruct the past line-of-sight average velocities of the landslide and the time-series deformations. Following the high velocities detected by the PSI, and the extensive damages surveyed in the buildings of the village, the Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR) system has been installed. The GBInSAR monitoring system has been equipped during October 2008 and three distinct campaigns have been carried out from October 2008 until March 2009. The interpretation of the data has allowed deriving a multi-temporal deformation map of the landslide, showing the up-to-date displacement field and the average landslide velocity. A new landslide boundary has been defined and two landslide sectors characterized by different displacement rates have been identified.

Landslide Susceptibility Mapping at National Scale: The Italian Case Study

Landslide susceptibility maps are key tools for land use planning, management and risk mitigation. The Landslide susceptibility map of Italy, scale 1:1,000,000 is being realized by using the Italian Landslide Inventory – Progetto IFFI and a set of contributing factors, such as surface parameters derived from 20 to20 m DEM, lithological map obtained from the geological map of Italy 1:500,000, and land use map (Corine Land Cover 2000). These databases have been subjected to a quality analysis with the aim of assessing the completeness, homogeneity and reliability of data, and identifying representative areas which may be used as training and test areas for the implementation of landslide susceptibility models. In order to implement the models, physiographic domains of homogeneous geology and geomorphology have been identified, and landslides have been divided into three main classes in order to take into account specific sets of conditioning factors: (a) rockfalls and rock-avalanches; (b) slow mass movements, (c) debris flows. The modelling tests performed with different techniques (Discriminant Anaysis, Logistic Regression, Bayesian Tree Random Forest) provided good results, once applied with the appropriate selection of training and validations sets and with a significant number of statistical units.

Risk analysis for the Ancona landslide—II: estimation of risk to buildings

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.

A Procedure to Map Subsidence at the Regional Scale Using the Persistent Scatterer Interferometry (PSI) Technique

In this paper, we present a procedure to map subsidence at the regional scale by means of persistent scatterer interferometry (PSI). Subsidence analysis is usually restricted to plain areas and where the presence of this phenomenon is already known. The proposed procedure allows a fast identification of subsidences in large and hilly-mountainous areas. The test area is the Tuscany region, in Central Italy, where several areas are affected by natural and anthropogenic subsidence and where PSI data acquired by the Envisat satellite are available both in ascending and descending orbit. The procedure consists of the definition of the vertical and horizontal components of the deformation measured by satellite at first, then of the calculation of the “real” displacement direction, so that mainly vertical deformations can be individuated and mapped.