Search

This paper shows the results of a study aimed at quantitatively estimating—in terms of direct (repair) costs, at large scale (1:5000)—the slow-moving landslide risk to a road network assumed as undamaged as well as the consequences to the same network in damaged conditions. The newly conceived methodological approaches address some challenging tasks concerning (i) the hazard analysis, which is expressed in terms of probability of occurrence of slow-moving landslides with a given intensity level that, in turn, is established based on empirical fragility curves, and (ii) the consequence analysis, which brings to the generation of time-dependent vulnerability curves. Their applicability is successfully tested in a case study in the Campania region (southern Italy) for which both very high-resolution DInSAR data and information gathered from in situ surveys on the severity of damage sustained by the selected road sections are available. Benefits associated with the use of the obtained results in informed decision-making processes are finally discussed.

Interferometric methods are drivers of the recent exponential growth in the use of synthetic aperture radar (SAR) for monitoring both natural and anthropogenic hazards. Since the first use of interferometric SAR (InSAR) in the late 1990s to detect deformations associated with earthquakes and volcanoes, important developments have improved sensor performance and data-processing capabilities for the extraction of information of interest in geophysical applications. Here, we describe the improvements that have enabled the 3D reconstruction and monitoring of buildings, with reference to their protection against and prevention of risks. We focus on buildings affected by systematic displacements related to natural hazards-specifically, landslides. We address the straightforward use of InSAR methods in the detection and characterization of the hazard as well as in higher-level exploitation for geotechnical and structural studies and, more generally, vulnerability analysis.

Persistent Scatterer Interferometry (PSI) data, deriving from the processing of SAR images acquired by high-resolution sensors such as TerraSAR-X, provide accurate measurements of displacements affecting structures (e.g., buildings) and linear infrastructure networks (e.g., roads, bridges, embankments, and pipelines). Such widespread displacements, when available on buildings on unstable slopes, offer new perspectives for their integration in procedures pursuing the analysis and the prediction of the physical vulnerability of exposed buildings. In this letter, both deterministic and probabilistic cause (differential settlements)-effects (damage) relationships are generated by using PSI-derived building settlements and the results of building damage surveys. The procedure is applied to El Papiol town (Spain), whose urban area has been suffering diffuse damage of different severity to buildings and roads due to extremely slow-moving landslide phenomena.

The reconnaissance, mapping and analysis of kinematic features of slow-moving landslides evolving along medium-deep sliding surfaces in urban areas can be a difficult task due to the presence and interactions of/with anthropic structures/infrastructures and human activities that can conceal morphological signs of landslide activity. The paper presents an integrated approach to investigate the boundaries, type of movement, kinematics and interactions (in terms of damage severity distribution) with the built environment of a roto-translational slow-moving landslide affecting the historic centre of Lungro town (Calabria region, southern Italy). For this purpose, ancillary multi-source data (e.g. geological-geomorphological features and geotechnical properties of geomaterials), both conventional inclinometer monitoring and innovative non-invasive remote sensing (i.e. A-DInSAR) displacement data were jointly analyzed and interpreted to derive the A-DInSAR-geotechnical velocity (DGV) map of the landslide. This result was then cross-compared with detailed information available on the visible effects (i.e. crack pattern and width) on the exposed buildings along with possible conditioning factors to displacement evolution (i.e. remedial works, sub-services, etc.). The full integration of multi-source data available at the slope scale, by maximizing each contribution, provided a comprehensive outline of kinematic-geometric landslide features that were used to investigate the damage distribution and to detect, if any, anomalous locations of damage severity and relative possible causes. This knowledge can be used to manage landslide risk in the short term and, in particular, is propaedeutic to set up an advanced coupled geotechnical-structural model to simulate both the landslide displacements and the behavior of interacting buildings and, therefore, to implement appropriate risk mitigation strategies over medium/long period.

This paper presents some results of a multidisciplinary research about the assessment of damages to ordinary buildings at the urban scale in landslide areas. The methodology represents part of a multi-level approach for landslide vulnerability assessment that has been recently developed. It is based on rapid visual inspections of the buildings, the application of ‘simple models’ to interpret the structural response, the geological and geotechnical knowledge of the site. The end-product is the landslide damage geotechnical chart, including: i) the damage grade of the buildings, ii) the geomorphological and geotechnical map of the area, iii) the direction of the settlements causing damages. The application of the methodology to an historical site in southern Italy is also outlined. Finally, the contribution of innovative non-invasive spaceborne remote sensing techniques to monitor landslide-affected urban areas is highlighted.

The paper presents a multi-source approach tailored for the analysis of ground movements affecting the village of Barberà de la Conca (Tarragona, Catalonia, Spain), where cracks on the ground and damage of different severity to structures and infrastructure was recorded. For this purpose, monitoring of ground displacements performed by topographic survey, geotechnical monitoring and remote sensing techniques (ground-based synthetic aperture radar, GBSAR) are combined with multi-temporal damage surveys and monitoring of cracks (crackmeters) to get an insight into the kinematics of the urban slope. The obtained results highlight the correspondence between the monitoring data and the effects on the exposed facilities induced by ground displacements, which seem to occur predominantly in the horizontal plane with diverging directions (northward and southward) from the main ground fracture crossing the centre of the village. The case study stands as a further contribution to fostering this kind of integrated approaches that via cross-validations can improve data reliability as well as enrich datasets for slope instability recognition and analysis, which are crucial to plan risk mitigation works.

The analysis of consequence induced by landslides to the built environment is a key step in the landslide risk management process. For this purpose, a thorough knowledge of both the landslide mechanisms and the behaviour/characteristics of the exposed elements turn out to be crucial. Currently, scientists and technicians have access to unprecedented big data sources that provide a variety of useful information on landslide-affected areas. With reference to slow-moving landslides, this paper presents some case studies of an ongoing research aimed at defining and testing original procedures pursuing the exploitation of innovative monitoring/surveying techniques for the analysis and forecasting of vulnerability of buildings and roads.

Quantitative analysis of consequences (in terms of expected monetary losses) induced by slow-moving landslide mechanisms to buildings or infrastructure networks is a key step in the landslide risk management framework. It can influence risk mitigation policies as well as help authorities in charge of land management in addressing/prioritizing interventions or restoration works. This kind of analysis generally requires multidisciplinary approaches, which cannot disregard a thorough knowledge of landslide mechanisms, and rich datasets that are seldom available as testified by the limited number of examples in the scientific literature. With reference to the well-documented case study of Lungro town (Calabria region, southern Italy)—severely affected by slow-moving landslides of different types—the present paper proposes and implements a multi-step procedure for monetary loss forecasting associated with different landslide kinematic/damage scenarios. Procedures to typify landslide mechanisms and physical vulnerability analysis, previously tested in the same area, are here appropriately merged to derive both kinematic and damage scenarios to the exposed buildings. Then, the outcomes are combined with economic data in order to forecast monetary loss at municipal scale. The proposed method and the obtained results, once further validated, could stand as reference case for other urban areas in similar geo-environmental contexts in order to derive useful information on expected direct consequences unless slow-moving landslide risk mitigation measures are taken.

This paper presents the results of a numerical analysis aimed at investigating the response – in terms of damage occurrence and development – of a masonry building undergoing settlements induced by a slow-moving landslide. The analysis is performed by applying the Equivalent Frame Method to a model representative of a low-rise building with shallow foundations located in the historic centre of Lungro town (Calabria region, southern Italy). As a main novelty, data collected by way of both conventional (i.e. inclinometers) and innovative (i.e. DInSAR) monitoring techniques are used to derive the three-dimensional settlement trough to be imposed to the building model’s foundation in the numerical analyses. The obtained outcomes are compared with information gathered from multi-temporal damage surveys to the modeled building. Based on previous studies aimed at typifying the slow-moving landslides, the results obtained could concur to the generation of certain building-foundation-landslide typified models helpful for damage forecasting at the municipal scale.

Statistical analyses have been often used for landslide susceptibility zoning at small to medium scale when relevant base and thematic maps are available. Since the beginning of the last decade, images remotely acquired by spaceborne Synthetic Aperture Radar (SAR) and processed via Differential SAR Interferometry (DInSAR) proved extremely useful for non-invasive and non-destructive monitoring of displacements of the topographic surface. The present paper proposes an original procedure for the definition of the state of activity of slow-moving landslides via the combined use of multivariate statistical analyses and DInSAR data. The procedure is based on the following essential elements: distinction between terrain units used for computational purposes and the final zoning units; independent statistical and DInSAR analyses and activity models leading to first-level state of activity zoning maps; a consistency model between statistical and DInSAR analyses; two confidence and combination models leading, respectively, to second- or third-level state of activity zoning maps. The application in a test area including 19 municipalities in southern Italy, where slow-moving landslides are widespread and accurately mapped by using geomorphological criteria, allowed the generation of the three above-mentioned levels of zoning maps. The results were successfully crosschecked by exploiting a different DInSAR dataset and the results of previous works based on the use of slow-moving landslide-induced damage to facilities surveys.

Several urban areas in Euro-Mediterranean countries are affected by slow-moving landslides that, even if rarely associated with the loss of human life, can cause damage to structures and infrastructure. In such contexts, the progressive decay of the built environment can bring along a generalized increase of the physical vulnerability and, as a result, slow-moving landslide risk increases over the time. Under these conditions, as long as suitable risk mitigation measures are lacking, the level of risk (also related to earthquakes) could turn out to be no longer acceptable within an a priori unknown time interval. This problem has a relevant social-economic impact, thus requiring the adoption of risk mitigation strategies that need to be effective and, at the same time, sustainable for the involved stakeholders. In this regard, this paper proposes a multi-scale methodological approach—based on the joint use of satellite-derived displacement monitoring data and the results of building damage surveys—whose applicability is tested with reference to urban areas affected by slow-moving landslides in Calabria region (southern Italy).

Slow-moving landslides are widespread natural hazards that can affect both social and economic activities causing damage to structures and infrastructure networks. This paper aims at providing an innovative simplified procedure to analyse road damage induced by slow-moving landslides based on the joint use of landslide inventory maps, a road damage database (collecting both the results of in-situ surveys and Google Street View images) and ground displacement measurements derived from the interferometric processing of satellite SAR images (DInSAR data). The procedure was applied to the case study of the Calabria region (southern Italy) following a two-scale approach. First, a regional-scale analysis was carried out to gather information on the level of road exposure (namely, Index of Exposed Roads) to slow-moving landslides in order to identify the most representative case studies. Then at local scale, relationships between road damage severity level and a selected parameter (i.e. differential settlement computed in two different ways) of slow-moving landslide intensity were derived for two road stretches that differ in geo-lithological and topographic conditions. The results underline the importance of the availability of both reliable landslide inventories and rich road damage databases as well as the potential of high-resolution DInSAR data for obtaining quantitative information on movement rates of roads useful to carry out in-depth studies pursing vulnerability analyses of the infrastructure.

High and very-high resolution remote sensing data provided by the processing of Synthetic Aperture Radar (SAR) images via Differential Interferometry techniques (DInSAR) allow detecting ground surface displacements that can be used in monitoring/control of urban areas and integrated within procedures aimed at analyzing the vulnerability of affected facilities (e.g. structures and infrastructure). In this regard, this paper presents the results of a study that combines DInSAR data and information gathered from damage surveys to buildings interacting with slow-moving landslides. In particular, relationships between cause (DInSAR-derived differential settlements of buildings) and effect (recorded building damages) are retrieved and empirical fragility and vulnerability curves (to be used for damage forecasting purposes) are generated. Considering the encouraging outcomes, the adopted methodological approach can be successfully integrated within a more general framework for the management of slow-moving landslide risk to which urban areas are exposed.

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 abovementioned 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.

This paper aims at providing helpful tools (i.e. empirical fragility curves) for the analysis and prediction of the damage to masonry buildings in areas affected by slow-moving landslides. This goal is pursued through the development of an innovative procedure based on the joint use of DInSAR data and building damage surveys and applied in two study areas of the Calabria region (southern Italy).

This paper presents a mass movement inventory map at 1:5000 scale of the Verbicaro area (about 13 km2) located in the Calabria region (southern Italy). The Main Map results from the visual interpretation of aerial photographs, multi-temporal geomorphological field surveys, and field investigations of damage suffered by buildings. Some 53% of the study area is affected by a total of 252 landslides, comprising different types, state of activity, and size. The mapped landslides, mainly complex type, involve low-grade metamorphic rocks; among these, 15% are active and slow-move on pre-existing sliding surfaces. Moreover, out of 492 surveyed buildings, 347 are located on landslide-affected areas and experienced damages covering a broad range of severity levels. The Main Map can represent a useful tool for authorities in charge of land-use planning and urban management and can be used to pursue landslide risk analyses.

This paper proposes a multi-sensor a priori PSI visibility map for Austria in order to evaluate the feasibility of Differential SAR Interferometric (DInSAR) applications for landslide-affected slopes. For this purpose, the range index RI, introduced for the determination of areas in layover and foreshortening on both ascending and descending acquisition geometries, is computed and applied to the most diffuse X-C-L band SAR sensors. A new method is introduced to improve the accuracy of those products by fusing CORINE data with sharper European JRC forest map and Imperviousness Copernicus map. The results are tested with six different available PSI datasets over Austria. Then, a priori visibility map and a PSI density map are also derived for seven different satellites by combining the RI index and an enhanced CORINE land cover map. Finally, PSI velocity values, along the Line of Sight (VLos) and projected along the steepest slope direction (VSlope), are used in order to produce a landslide velocity map for the Austrian region of Vorarlberg.

Slow-moving landslides yearly induce huge economic losses worldwide in terms of damage to facilities and interruption of human activities. Within the landslide risk management framework, the consequence analysis is a key step entailing procedures mainly based on identifying and quantifying the exposed elements, defining an intensity criterion and assessing the expected losses. This paper presents a two-scale (medium and large) procedure for vulnerability assessment of buildings located in areas affected by slow-moving landslides. Their intensity derives from Differential Interferometric Synthetic Aperture Radar (DInSAR) satellite data analysis, which in the last decade proved to be capable of providing cost-effective long-term displacement archives. The analyses carried out on two study areas of southern Italy (one per each of the addressed scales) lead to the generation, as an absolute novelty, of both empirical fragility and vulnerability curves for buildings in slow-moving landslide-affected areas. These curves, once further validated, can be valuably used as tools for consequence forecasting purposes and, more in general, for planning the most suitable slow-moving landslide risk mitigation strategies.

A proper analysis of slow-moving landslides calls for several efforts aiming at their characterization and mapping. Considering the uncertainties related to the landslide inventory maps the integration of conventional techniques with remote sensing data, such as differential SAR interferometry (DInSAR), can furnish a valuable contribution in a number of case studies. However, standardized procedures for the interpretation and the confident use of DInSAR data, according to landslide zoning developments, have not been fully investigated and validated, although algorithms for image processing have become more and more sophisticated. This work addresses a new methodology for the use of DInSAR data, at both full- and low-resolutions, in landslide analyses at different scales via the integration of remote sensing data with simple geomorphological models and geometric considerations. The methodology is tested inside a well documented area in Central–Southern Italy where an advanced dataset on base and thematic maps is available.

Geological and geomorphological criteria complemented with geotechnical monitoring of ground displacements are routinely applied for geometric and kinematic characterization of landslides. However, these activities may be challenging in densely built-up historic centres. In order to tackle all constraints posed by the presence of complex urban fabric, this paper proposes a procedure for integrating the results of geological/geomorphological analyses with deep and surface ground displacement data acquired via geotechnical monitoring and spaceborne Differential Interferometric Synthetic Aperture Radar (DInSAR) data. The selected test site is a village in southern Italian Apennines characterized by complex geological/geomorphological settings, widespread distribution of landslides and a peculiar urban fabric. The results of the integration procedure show that it is possible to overcome specific limits and provide a better understanding and definition of the geometry and kinematics of slow-moving landslides to be used for slope stability analyses and landslide risk management in historic centres.

The paper aims at checking the contribution that DInSAR data, processed via different algorithms, can provide to the analysis of damages recorded to buildings located in slow-moving landslide affected areas. For this purpose, an urban area in Calabria region, southern Italy, was selected due to the availability of both DInSAR data since 1992 and historic information concerning damage data recorded via municipal ordinances. The combination of DInSAR data and the results of supplementary damage surveys allowed the preliminary investigation of a cause (maximum velocity)—effect (damage) relationship which, once validated, can be valuably used for damage analysis and forecasting.

This work shows a methodological approach for the joint use of geological and geomorphological studies and conventional/innovative monitoring data in densely urbanized areas at landslide risk. The methodology is applied to a test area in the Calabria region (southern Italy) extensively affected by several active landslides involving urban areas. These landslides have been studied and monitored via ground-based techniques for many years. In the study area the comparison and interpretation of DInSAR data with geomorphological studies and inclinometric monitoring has been carried out. The results obtained, thanks to the validation of remote sensed data via ground-truths, provide a further step towards the integrated use of DInSAR data within landslide risk mitigation strategies. © Springer-Verlag Berlin Heidelberg 2013.

Differential Interferometry Synthetic Aperture Radar is a mature remote sensing technique broadly used for the measurement of slow deformations with major application in several fields. In the last years, the application to slow moving landslides has grown quickly and several examples of the monitoring capability can be found in the literature. Main goal of this work is the description of the advances in terms of products that can be achieved from both an innovative methodological approach to DInSAR data analysis and the technological improvements related to the last generation of sensors.

Testing innovative procedures and techniques to update landslide inventory maps is a timely topic widely discussed in the scientific literature. In this regard remote sensing techniques – such as the Synthetic Aperture Radar Differential Interferometry (DInSAR) – can provide a valuable contribution to studies concerning slow-moving landslides in different geological contexts all over the world. In this paper, DInSAR data are firstly analysed via an innovative approach aimed at enhancing both the exploitation and the interpretation of remote sensing information; then, they are complemented with the results of an accurate analysis of survey-recorded damage to facilities due to slow-moving landslides. In particular, after being separately analysed to provide independent landslide movement indicators, the two datasets are combined in a DInSAR-Damage matrix which can be used to update the state of activity of slow-moving landslides. Moreover, together with the information provided by geomorphological maps, the two datasets are proven to be useful in detecting unmapped phenomena. The potentialities of the adopted procedure are tested in an area of southern Italy where slow-moving landslides are widespread and accurately mapped by using geomorphological criteria.

Landslide studies over large areas call for multidisciplinary analyses supported by accurate ground displacement measurements. At present, conventional techniques can be valuably complemented by innovative satellite techniques such as Differential SAR Interferometry (DInSAR), furnishing huge amounts of data at competitively affordable costs. This work investigates the remote sensed data potential in landslide studies starting from the awareness of the present constraints of the technique. To this end, with reference to a sample area–within the territory of the National Basin Authority of Liri-Garigliano and Volturno rivers (Central-Southern Italy)–for which detailed base and thematic maps are available, quantitative examples of DInSAR data coverage on both different land-uses and landslide-affected areas are shown. Then, an original tool for “a priori DInSAR landslide visibility zoning” is proposed to address the choice of the most suitable image datasets. Finally, referring to the visible zones, the outcomes of DInSAR data for checking/updating landslide inventory maps at 1:25,000 scale highlight appealing perspectives, also holding the promise of obtaining relevant information in the landslide hazard evaluation.