Francesca Ardizzone

Landslide inventory map for the Briga and the Giampilieri catchments, NE Sicily, Italy

On 1 October 2009, a high intensity storm hit the Ionian coast of Sicily, SW of Messina, Italy. The Santo Stefano di Briga rain gauge, located 2 km W of the Ionian coast, recorded 225 mm of rain in seven hours. The intense rainfall event triggered abundant slope failures, and resulted in widespread erosion and deposition of debris along ephemeral drainage channels, extensive inundation, and local modifications of the coastline. Landslides occurred in a territory prone to slope failures, due to the local geological and geomorphological settings. Many landslides were related to the presence of roads lacking adequate drainage. Abandoned terraced slopes lacking proper drainage, and unmaintained dry walls were also related to slope failures. Damage was particularly severe in small villages and at several sites along the transportation network. The shallow landslides and the inundation resulted in 37 fatalities, including 31 deaths and six missing persons, and innumerable injured people. After the event, an accurate landslide inventory map was prepared for the Briga and the Giampilieri catchments. The map shows: (i) the distribution of the event landslides triggered by the 1 October 2009 rainfall event; (ii) the distribution of the pre-existing slope failures; and (iii) other geomorphological features related to fluvial processes and slope movements. The landslide inventory map was prepared at 1:10,000 scale through a combination of field surveys and photo-interpretation of pre-event and post-event, stereoscopic and pseudo-stereoscopic, aerial photography. Different types of aerial photographs were analysed visually to prepare the landslide inventory map. The event landslides were mapped through the interpretation of pseudo-stereoscopic colour photographs taken shortly after the event at 1:3500 scale, combined with digital stereoscopic photographs at approximately 1:4500 scale, taken in November 2009. The pre-event landslides and the associated geomorphological features were mapped using 1:33,000 scale aerial photographs flown in 1954, 1955, and 2005. The event and pre-existing landslides were checked in the field in the period October–November 2009.

Very-High Resolution Stereoscopic Satellite Images for Landslide Mapping

Landslide inventory maps are essential for geomorphological studies, and to evaluate landslide hazard, vulnerability, and risk. Landslide maps, including geomorphological, event, seasonal, and multi-temporal inventory maps, are prepared using different techniques. We present the results of an experiment aimed a testing the possibility of using very high resolution, stereoscopic satellite images to map rainfall induced shallow landslides. Three landslide inventory maps were prepared for the Collazzone study area, Umbria, Italy. Two of the maps were prepared through the visual interpretation of stereoscopic satellite images and cover the periods January to March 2010, and March to May 2010. The third inventory map shows landslides occurred in the period January to May 2010, and was obtained through reconnaissance field surveys. We describe the statistics of landslide area for the three inventories, and compare quantitatively two of the landslide maps.

The Use of Stereoscopic Satellite Images to Map Rills and Ephemeral Gullies

Abstract: Accurate mapping and measurement of erosion channels is necessary to accurately estimate the impact of channeled erosion in an area. Field surveys can provide optimal quantitative results, but they are only applicable to small areas. Recently, photogrammetric techniques have been applied to small format aerial photographs that were taken by UAVs. Few studies have applied photogrammetry for mapping and measuring single permanent gullies using very high resolution stereoscopic satellite images. We explore the use of such images to map rills and ephemeral gullies and to measure the length, width and depth of individual erosion channels to estimate the eroded volumes. The proposed methodology was applied to the Collazzone area of Central Italy. All of the channel characteristics were determined using GeoEye-1 ® panchromatic stereoscopic satellite images of the 48-km 2 study area and a 3D floating cursor. We identified, mapped, and measured the lengths of 555 channel segments. The top width and depth could be measured in only a subset of the channel segments (the SMC subset). The SMC data were used to determine the coefficients of the power law relationship between the rill/gully volume and length (

Rainfall Thresholds for Possible Occurrence of Shallow Landslides and Debris Flows in Italy

In mountain regions worldwide, rainfall-induced landslides and associated debris flows erode slopes, scour channels, and contribute to the formation of alluvial fans that may harm humans and destroy buildings. Rainfall-induced slope failures are frequent and widespread in Italy, where individual rainfall events can result in single or multiple slope failures in small areas or in very large regions. Most of the harmful failures were rainfall-induced, and several were shallow slides or debris flows. In the 60-year period 1950–2009, casualties due to landslides were at least 6,349, an average of 16 harmful events per annum. The large number of harmful events indicates the considerable risk posed by rainfall-induced shallow landslides and debris flows to the population of Italy (Guzzetti et al. 2005a; Salvati et al. 2010).

Analysis of ground deformation using SBAS-DInSAR technique applied to COSMO-SkyMed images, the test case of Roma urban area

Differential Synthetic Aperture Radar Interferometry (DInSAR) represents a well-established remote sensing technique for the investigation of ground deformation phenomena.Among the DInSAR techniques, the Small BAseline Subset (SBAS) approach exploits ground surface at two mapping scales, low and high resolution, and allows the detection and monitoring of local deformation processes that may affect single buildings or man-made structures in urban areas. This work investigates the capability improvement of the SBAS-DInSAR technique to analyse deformation processes in urban areas by exploiting SAR data acquired by the Cosmo-SkyMed (CSM) constellation in comparison with the results obtained from data of first generation ERS/ENVISAT radar systems of he European Space Agency. In particular, we extracted mean deformation velocity maps as seen by the three different radar systems and, for each coherent pixel, we retrieved the corresponding displacement time series. Our analysis was focused on the Torrino area where independent studies had already revealed significant deformation signals testified by the serious damages on many buildings in the area. Moreover, in order to understand the causes of the CSM observed displacement rates, reaching few cm per year, we also performed a comparative analysis between DInSAR products and independent information derived from electrical resistivity tomography data and geological maps.

Impact of event landslides on road networks: a statistical analysis of two Italian case studies

Despite abundant information on landslides, and on landslide hazard and risk, in Italy, little is known on the direct impact of event landslides on road networks and on the related economic costs. We investigated the physical and economic damage caused by two rainfall-induced landslide events in Central and Southern Italy, to obtain road restoration cost statistics. Using a GIS-based method, we exploited road maps and landslide event inventory maps to compute different metrics that quantify the impact of the landslide events on the natural landscape and on the road networks, by road type. The maps were used with cost data obtained from multiple sources, including local authorities, and specific legislation, to evaluate statistically the unit cost per metre of damaged road and the unit cost per square metre of damaging landslide, separately for main and secondary roads. The obtained unit costs showed large variations which we attribute to the different road types in the two study areas and to the different abundance of landslides. Our work confirms the long-standing conundrum of obtaining accurate landslide damage data and outlines the need for reliable, standardized methods to evaluate landslide damage and associated restoration costs that regional and local administrations can use rapidly in the aftermath of a landslide event. We conclude recommending that common standardized procedures to collect landslide cost data following each landslide event are established, in Italy and elsewhere. This will allow for more accurate and reliable evaluations of the economic costs of landslide events.

GIS-Based Deterministic Analysis of Deep-Seated Slope Stability in a Complex Geological Setting

The r.slope.stability computer model evaluates the slope stability for large areas making use of a modification of the three-dimensional sliding surface model proposed by Hovland and revised and extended by Xie and co-workers. The initial version of the model was modified both to reduce computing time (parallel processing of tiles) and to explore the possibilities to perform slope stability modelling in a complex geological setting. The model was applied to the 10 km2 Ripoli area in Umbria, central Italy to demonstrate the importance of the setting of the geological layers as well as of the seepage direction of the groundwater for the model outcome of deep-seated slope stability modelling. Parallel processing allows reducing the computing time by approx. one order of magnitude.

Preliminary analysis of a correlation between ground deformations and rainfall: the Ivancich landslide, central Italy

We exploited Differential Synthetic Aperture Radar Interferometry (DInSAR) to investigate the geographical and the temporal pattern of ground deformations in the Ivancich landslide area, Assisi, Italy, in the 18.4-year period April 1992 - September 2010. We used SAR data obtained by the European Remote Sensing (ERS-1/2) satellites in the period April 1992 - July 2007, and SAR data captured by the ASAR sensor on board the Envisat satellite in the period October 2003 - September 2010. We used the Small Baseline Subset (SBAS) technique to process the SAR data, obtaining full resolution measurements for multiple radar targets inside and outside the landslide area, and the history of deformation of the individual targets. The geographical pattern of the ground deformation was found consistent with independent topographic information. The deformation time series of the individual targets were compared to the rainfall history in the area. Results revealed the lack of an immediate effect of rainfall on the ground deformation, and confirmed the existence of a complex temporal interaction between the rainfall and the ground deformation histories in the landslide area. Availability of very long, spatially distributed time series of surface deformation has provided an unprecedented opportunity to investigate the history of the active landslide area.

The Ivancich Active Landslide Process (Assisi, Central Italy) Analysed via Numerical Modeling Jointly Optimized by DInSAR and Inclinometric Data

The analysis of the displacement field due to a landslide process can be performed by means of either forward or inverse numerical models. Concerning the evolution of slow landslides, the Finite Element Method (FEM) represents a powerful tool to assess the relationships existing between the causative factors and the related effects, being the latter generally detected by field monitoring data. In this context, inverse models are useful to deduce the values of physical or mechanical parameters that control the landslide behavior over time. In this paper, we combined the potentiality of the FEM with Monte Carlo optimization procedures, based on a Genetic Algorithm (GA) technique, to back-analyze and interpret the kinematical evolution of very slow active landslides. In particular, we performed a two-dimensional time-dependent FE analysis by using a deviatoric creep model to simulate the evolution of the displacement field of the very slow Ivancich landslide (Assisi, Central Italy); an optimization procedure was performed by considering the Differential SAR Interferometry (DInSAR) data to derive the soil creep rate distribution, according to an inverse analysis approach. In particular the long-term Small BAseline Subset (SBAS) DInSAR analysis covering about 20 years was compared with the slope velocities calculated by the numerical model and the best-fit creep model was identified by considering the minimum Root Mean Square Error between field data and model results. Finally the model results in terms of slope displacements over time have been also compared with the available inclinometric measurements.

Considering parameter uncertainty in a GIS-based sliding surface model for large areas

The GIS-based open source software r.slope.stability computes broad-scale spatial overviews of shallow and deep-seated slope stability through physically-based modelling. We focus on the landslide-prone 90 km2 Collazzone area, central Italy, exploiting a comprehensive set of lithological, geotechnical and landslide inventory data available for that area. Inevitably, the geotechnical and geometric parameters are uncertain, particularly for their three-dimensional variability. Considering the most unfavourable set of geotechnical parameters (worst case scenario, appropriate for engineering purposes) is less useful to obtain an overview of the spatial probability (susceptibility) of landslides over tens of square kilometres. Back-calculation of the parameters based on topographic and geotechnical considerations would better suit for such a purpose, but obtaining one single parameter combination would require information on one of the parameters. Instead, we estimate the slope failure probability by testing multiple combinations of the model parameters sampled deterministically. Our tests indicate that (i) the geotechnical parameterization used allows to reproduce the observed landslide distribution partly (a challenge consists in the appropriate treatment of the variation of the geotechnical parameters with depth); (ii) the evaluation outcome depends strongly on the level of geographical aggregation; and (iii) when applied to large study areas, the approach is computing-intensive, and requires specific strategies of multi-core computing to keep computational times at an acceptable level.