Gianfranco Nicodemo

Empirical fragility and vulnerability curves for buildings exposed to slow-moving landslides at medium and large scales

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.

The Use of DInSAR Data for the Analysis of Building Damage Induced by Slow-Moving Landslides

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.

Analysis of building vulnerability to slow-moving landslides via A-DInSAR and damage survey data

The paper presents a procedure for the analysis of building vulnerability to slow-moving landslides via A-DInSAR and damage survey data. For this purpose, a test site in Calabria region (southern Italy) affected by slow-moving landslides, which over the time caused severe damage to buildings, was selected. The availability of remote sensing data such as those derived from the processing of Synthetic Aperture Radar images via Advanced Differential Interferometry techniques (A-DInSAR) and information concerning damage severity suffered by the facilities, collected by in situ damage surveys, allowed investigating the cause (differential settlement)—effect (damage) relationship. Then, empirical fragility curves for both reinforced concrete and masonry buildings were generated. These latter, once further validated, can be valuably used for damage analysis and forecasting purposes and framed within procedures for risk analysis and management over urban landslide-affected areas.

Geology, slow-moving landslides, and damages to buildings in the Verbicaro area (north-western Calabria region, southern Italy)

ABSTRACT 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.

Empirical Fragility Curves for Masonry Buildings in Slow-Moving Landslide-Affected Areas of Southern Italy

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).

Quantitative analysis of consequences to masonry buildings interacting with slow-moving landslide mechanisms: a case study

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.