Search

Distributed physically based slope stability models represent the most advanced and scientifically sound method to forecast landslide triggering conditions. However, their operational application in regional warning systems is still hindered by some limitations. Among these, the problem of a robust validation (a task that is time consuming and not standardized) and the difficulty to manage a model output that (especially in the most advanced applications) is constituted by a raster of small pixels expressing the probability of landslide triggering: to activate an operational response an evaluation is usually performed on the overall conditions of larger spatial units and not on a pixel basis.To overcome these shortcomings, we developed a GIS tool that can be fed with the results of slope stability models (raster maps representing the probability of landslide occurrence) and landslide inventory maps. The tool automatically performs a long series of operations traditionally performed by GIS operators to validate their models: the raw instability maps are reaggregated from pixels to watershed; warning maps are drawn; they are compared with the landslide inventory; a contingency matrix (with true positives, true negatives, false positive, and false negatives) is built; the validation results are drawn in a map. The warning criterium is defined based on two threshold values: the probability of failure above which a pixel should be considered stable and the percentage of unstable pixels that a watershed needs to consider the hazard level widespread enough to justify the issuing of an alert. The tool was named Double Threshold Validation Tool (DTVT) and after some tests in three different test sites it was verified that: (i) DTVT can be used to carry out a standardized validation procedure in a very shorter time than traditional methods (ii) a reiterated application of the tool (by varying the values of the thresholds) can be used to identify the best warning criterion for each test site (e.g. which double threshold maximizes correct predictions while minimizing missed alarms). It is important to stress that DTVT does not improve the results obtained with the slope stability model; instead, this newly proposed tool that can be used to shift form a triggering model to a warning model, the latter being aimed at identifying when larger spatial units need the activation of operational procedures.

Solar abundances have been historically assumed to be representative of cosmic abundances. However, our knowledge of the solar abundance of helium, the second most abundant element, relies mainly on models1 and indirect measurements through helioseismic observations2, because actual measurements of helium in the solar atmosphere are very scarce. Helium cannot be directly measured in the photosphere because of its high first ionization potential, and measurements of its abundance in the inner corona have been sporadic3,4. In this Letter, we present simultaneous global images of the helium (out to a heliocentric distance of 3R⊙ (solar radii)) and hydrogen emission in the solar corona during the minimum of solar activity of cycle 23 and directly derive the helium abundance in the streamer region and surrounding corona (out to 2.2R⊙). The morphology of the He+ corona is markedly different from that of the H corona, owing to significant spatial variations in helium abundance. The observations show that the helium abundance is shaped according to and modulated by the structure of the large-scale coronal magnetic field and that helium is almost completely depleted in the equatorial regions during the quiet Sun. This measurement provides a trace back to the coronal source of the anomalously slow solar wind observed in the heliosphere at the Sun–Earth Lagrangian point L1 in 2009, during the exceptionally long-lasting minimum of solar activity cycle 23. Global images of helium and hydrogen emission are used to directly derive the helium abundance out to 2.2R⊙. The helium abundance is shaped by the large-scale coronal magnetic field. Helium is almost completely depleted near the equator in the quiet Sun.

Wildfires have affected global forests and the Mediterranean area with increasing recurrency and intensity in the last years, with climate change resulting in reduced precipitations and higher temperatures. To assess the impact of wildfires on the environment, burned area mapping has become progressively more relevant. Initially carried out via field sketches, the advent of satellite remote sensing opened new possibilities, reducing the cost uncertainty and safety of the previous techniques. In the present study an experimental methodology was adopted to test the potential of advanced remote sensing techniques such as multispectral Sentinel-2, PRISMA hyperspectral satellite, and UAV (unmanned aerial vehicle) remotely-sensed data for the multitemporal mapping of burned areas by soil–vegetation recovery analysis in two test sites in Portugal and Italy. In case study one, innovative multiplatform data classification was performed with the correlation between Sentinel-2 RBR (relativized burn ratio) fire severity classes and the scene hyperspectral signature, performed with a pixel-by-pixel comparison leading to a converging classification. In the adopted methodology, RBR burned area analysis and vegetation recovery was tested for accordance with biophysical vegetation parameters (LAI, fCover, and fAPAR). In case study two, a UAV-sensed NDVI index was adopted for high-resolution mapping data collection. At a large scale, the Sentinel-2 RBR index proved to be efficient for burned area analysis, from both fire severity and vegetation recovery phenomena perspectives. Despite the elapsed time between the event and the acquisition, PRISMA hyperspectral converging classification based on Sentinel-2 was able to detect and discriminate different spectral signatures corresponding to different fire severity classes. At a slope scale, the UAV platform proved to be an effective tool for mapping and characterizing the burned area, giving clear advantage with respect to filed GPS mapping. Results highlighted that UAV platforms, if equipped with a hyperspectral sensor and used in a synergistic approach with PRISMA, would create a useful tool for satellite acquired data scene classification, allowing for the acquisition of a ground truth.

The analysis of slope stability over large areas is a demanding task for several reasons, such as the need for extensive datasets, the uncertainty of collected data, the difficulty of accounting for site-specific factors, and the considerable computation time required due to the size of investigated areas, which can pose major barriers, particularly in civil protection contexts where rapid analysis and forecasts are essential. However, as the identification of zones of higher failure probability is very useful for stakeholders and decision-makers, the scientific community has attempted to improve capabilities to provide physically based assessments. This study combined a transient seepage analysis of an unsaturated-saturated condition with an infinite slope stability model and probabilistic analysis through the use of a high-computing capacity parallelized platform. Both short- and long-term analyses were performed for a study area, and roles of evapotranspiration, vegetation interception, and the root increment of soil strength were considered. A model was first calibrated based on hourly rainfall data recorded over a 4-day event (December 14–17, 1999) causing destructive landslides to compare the results of model simulations to actual landslide events. Then, the calibrated model was applied for a long-term simulation where daily rainfall data recorded over a 4-year period (January 1, 2005–December 31, 2008) were considered to study the behavior of the area in response to a long period of rainfall. The calibration shows that the model can correctly identify higher failure probability within the time range of the observed landslides as well as the extents and locations of zones computed as the most prone ones. The long-term analysis allowed for the identification of a number of days when the slope factor of safety was lower than 1.2 over a significant number of cells. In all of these cases, zones approaching slope instability were concentrated in specific sectors and catchments of the study area. In addition, some subbasins were found to be the most recurrently prone to possible slope instability. Interestingly, the application of the adopted methodology provided clear indications of both weekly and seasonal fluctuations of overall slope stability conditions.

Unmanned aerial vehicle (UAV) photogrammetry has recently become a widespread technique to investigate and monitor the evolution of different types of natural processes. Fluvial geomorphology is one of such fields of application where UAV potentially assumes a key role, since it allows for overcoming the intrinsic limits of satellite and airborne-based optical imagery on one side, and in situ traditional investigations on the other. The main purpose of this paper was to obtain extensive products (digital terrain models (DTMs), orthophotos, and 3D models) in a short time, with low costs and at a high resolution, in order to verify the capability of this technique to analyze the active geomorphic processes on a 12 km long stretch of the French–Italian Roia River at both large and small scales. Two surveys, one year apart from each other, were carried out over the study area and a change detection analysis was performed on the basis of the comparison of the obtained DTMs to point out and characterize both the possible morphologic variations related to fluvial dynamics and modifications in vegetation coverage. The results highlight how the understanding of different fluvial processes may be improved by appropriately exploiting UAV-based products, which can thus represent a low-cost and non-invasive tool to crucially support decisionmakers involved in land management practices.

In the last years, the use of Unmanned Aerial Vehicles (UAVs) has developed rapidly across several field of earth sciences application, including landslides characterisation and monitoring, therefore providing a strong support for hazard and risk management activities especially with the introduction and advances in the miniaturization of traditional and new generation sensors. The flexibility, low cost, easy operability, and rapidness of intervention in emergency situation gives to these instruments, a strong potential in opening up a vast new area of opportunities in remote sensing for observation, measuring, mapping, monitoring, and management in various landslide environment. Unless initially only air photography was the main application for UAVs, recently new sensors, both passive and active, are being increasingly used. This paper, through some case studies on landslide investigations, aims at giving an overview on several sensors and techniques using UAVs platform addressed to landslide detection, characterization and monitoring.

Physically-based models employed for landslide forecasting are extremely sensitive to the use of geological information and a standard, universally accepted method to input maps containing information of geological interest into the models still has never been established. In this study, we used the information contained in a geo-database aimed to characterize the geotechnical and hydrological parameters of the hillslopes deposits in Tuscany, to find out how to organize and group the measurements to spatially create classes that mirror the distribution of the various types of bedrock lithology. Despite the deposits analysed are mainly consisting of well sorted silty sands, statistical analyses carried out on geotechnical and hydrological parameters highlighted that it is not possible to define a typical range of values with relation to the main mapped lithologies, because soil characteristics are not simply dependent on the bedrock typology from which the deposits originated. Instead, the analysis of the relationship of soil parameters with morphometric parameters (slope angle, profile curvature, planar curvature) shows that the highest correlation between the soil grain size class type (USCS classification) and morphometric attributes is with slope curvature, both profile and planar.

This paper presents the preliminary results of the IPL project 196 “Development and applications of a multi-sensor drone for geohazards monitoring and mapping.” The objective of the project is to test the applicability of a multi-sensor drone for the mapping and monitoring of different types of geohazards. The Department of Earth Sciences of the University of Florence has developed a new type of drone airframe. Several survey campaigns were performed in the village of Ricasoli, in the Upper Arno river Valley (Tuscany, Italy) with the drone equipped with an optical camera to understand the possibility of this rising technology to map and characterize landslides. The aerial images were combined and analyzed using Structure-from-Motion (SfM) software. The collected data allowed an accurate reconstruction and mapping of the detected landslides. Comparative analysis of the obtained DTMs also permitted the detection of some slope portions being prone to failure and to evaluate the area and volume of the involved mass.

Distributed physically based slope stability models usually provide outputs representing, on a pixel basis, the probability of failure of each cell. This kind of result, although scientifically sound, from an operational point of view has several limitations. First, the procedure of validation lacks standards. As instance, it is not straightforward to decide above which percentage of failure probability a pixel (or larger spatial units) should be considered unstable. Second, the validation procedure is a time-consuming task, usually requiring a long series of GIS operations to overlap landslide inventories and model outputs to extract statistically significant performance metrics. Finally, if model outputs are conceived to be used in the operational management of landslide hazard (e.g., early warning procedures), the pixeled probabilistic output is difficult to handle and a synthesis to characterize the hazard scenario over larger spatial units is usually required to issue warnings aimed at specific operational procedures. In this work, a tool is presented that automates the validation procedure for physically based distributed probabilistic slope stability models and translates the pixeled outputs in warnings released over larger spatial units like small watersheds. The tool is named DTVT (double-threshold validation tool) because it defines a warning criterion on the basis of two threshold values—the probability of failure above which a pixel should be considered stable (failure probability threshold, FPT) and the percentage of unstable pixels needed in each watershed to consider the hazard level widespread enough to justify the issuing of an alert (instability diffusion threshold, IDT). A series of GIS operations were organized in a model builder to reaggregate the raw instability maps from pixels to watershed; draw the warning maps; compare them with an existing landslide inventory; build a contingency matrix counting true positives, true negatives, false positive, and false negatives; and draw in a map the results of the validation. The DTVT tool was tested in an alert zone of the Aosta Valley (northern Italy) to investigate the high sensitivity of the results to the values selected for the two thresholds. Moreover, among 24 different configurations tested, we performed a quantitative comparison to identify which criterion (in the case of our study, there was an 85% or higher failure probability in 5% or more of the pixels of a watershed) produces the most reliable validation results, thus appearing as the most promising candidate to be used to issue alerts during civil protection warning activities.

The Department of Earth Sciences of Florence (DST) has developed a new type of drone chassis., Several survey campaigns were performed in Ricasoli village, in the Upper Arno river Valley (Tuscany, Italy) with the drone equipped with an optical camera, to understand the possibility of this rising technology to map and to characterize landslides. The aerial RGB images were analysed and combined using SfM (Structure from Motion) software. The comparative analysis of the obtained DTMs allowed an accurate reconstruction and mapping of the detected landslides. The collected data also allowed to precisely detect some slope portions prone to failure and to evaluate the area and volume of the involved masses.

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b), makes use of LAMI rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain-gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult and it provides different outputs. Switching among different views, the system is able to focus both on monitoring of real time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a very straightforward view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain-gauges can be displayed and constantly compared with rainfall thresholds. To better account for the high spatial variability of the physical features, which affects the relationship between rainfall and landslides, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of 332 rain gauges, it allows monitoring each alert zone separately and warnings can be issued independently from an alert zone to another. An important feature of the warning system is the use of thresholds that may vary in time adapting at the conditions of the rainfall path recorded by the rain-gauges. Depending on when the starting time of the rainfall event is set, the comparison with the threshold may produce different outcomes. Therefore, a recursive algorithm was developed to check and compare with the thresholds all possible starting times, highlighting the worst scenario and showing in the WebGIS interface at what time and how much the rainfall path has exceeded or will exceed the most critical threshold. Besides forecasting and monitoring the hazard scenario over the whole region with hazard levels differentiated for 25 distinct alert zones, the system can be used to gather, analyze, visualize, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

In the context of environmental monitoring, it is very important to improve systems for the identification, assessment and management of environmental risks through the use and integration of analytical techniques combined with hyperspectral airborne sensing technologies. Remote-sensing applications are varied, but nevertheless an accurate mapping of the soil required the use of complex scientific instruments installed on airplanes or helicopters. The high integration of electronics, combined with the computing power of modern processors, allows the development of integrated and compact hyperspectral systems installed on drones.1 The drone era poses new challenges to optical devices design: they shall be light, compact and robust, easy to assemble and to control. This work explains the optical system design of HYDRACAM (HYperspectral DRone Advanced CAMera), an instrument devoted to hyperspectral imaging by using an electro-optical liquid crystal tunable filter combined with a commercial camera. The commercial ray tracing software Zemax/OpticStudio2 was used to perform the optical design. The main challenge was to manufacture a low cost optical device, containing the mass and the total length to suit a drone payload. A huge effort was made in order to combine strict constraints (such as the filter narrow entrance aperture and its acceptance angle) with ambitious optical performance requirements (high spatial resolution, large field of view). First, a description of the work done to find a trade-off between cost and opto-mechanical constraints is provided: the choice of the commercial objective, the choice of the custom lenses materials and shapes and some optical design original solutions are addressed. Then, the details of the optical performance analysis are discussed.

In this work, we apply a physically-based model, namely the HIRESSS (High REsolution Stability Simulator) model, to forecast the occurrence of shallow landslides at regional scale. The final aim is the set-up of an early warning system at regional scale for shallow landslides. HIRESSS is a physically based distributed slope stability simulator for analysing shallow landslide triggering conditions in real time and in large areas using parallel computational techniques. The software can run in real-time by assimilating weather data and uses Monte Carlo simulation techniques to manage the geotechnical and hydrological input parameters. The test area is a portion of the Valle d'Aosta region, located in North-West Alpine mountain chain. The geomorphology of the region is characterized by steep slopes with elevations ranging from 400 m a.s.l. of Dora Baltea's river floodplain to 4810 m a.s.l. of Mont Blanc. In the study area, the mean annual precipitation is about 800–900 mm. These features lead to a high hydrogeological hazard in the whole territory, as mass movements interest the 70 % of the municipality areas (mainly shallow rapid landslides and rock falls). In order to apply the model and to increase its reliability, an in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslides formation was conducted. In particular, two campaigns of on site measurements and laboratory experiments were performed with 12 survey points. The data collected contributes to generate input map of parameters for HIRESSS model. In order to take into account the effect of vegetation on slope stability, the contribution of the root cohesion has been also taken into account based on the vegetation map and literature values. The model was applied in back analysis on two past events that have affected Valle d'Aosta region between 2008 and 2009, triggering several fast shallow landslides. The validation of the results, carried out using a database of past landslides, has provided good results and a good prediction accuracy of the HIRESSS model both from temporal and spatial point of view. A statistical analysis of the HIRESSS outputs in terms of failure probability has been carried out in order to define reliable alert levels for regional landslide early warning systems.

In this work, we apply a physically based model, namely the HIRESSS (HIgh REsolution Slope Stability Simulator) model, to forecast the occurrence of shallow landslides at the regional scale. HIRESSS is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions during a rainfall event. The modeling software is made up of two parts: hydrological and geotechnical. The hydrological model is based on an analytical solution from an approximated form of the Richards equation, while the geotechnical stability model is based on an infinite slope model that takes the unsaturated soil condition into account. The test area is a portion of the Aosta Valley region, located in the northwest of the Alpine mountain chain. The geomorphology of the region is characterized by steep slopes with elevations ranging from 400 m a.s.l. on the Dora Baltea River's floodplain to 4810 m a.s.l. at Mont Blanc. In the study area, the mean annual precipitation is about 800–900 mm. These features make the territory very prone to landslides, mainly shallow rapid landslides and rockfalls. In order to apply the model and to increase its reliability, an in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslide formation was conducted. In particular, two campaigns of on site measurements and laboratory experiments were performed using 12 survey points. The data collected contributed to the generation of an input map of parameters for the HIRESSS model. In order to consider the effect of vegetation on slope stability, the soil reinforcement due to the presence of roots was also taken into account; this was done based on vegetation maps and literature values of root cohesion. The model was applied using back analysis for two past events that affected the Aosta Valley region between 2008 and 2009, triggering several fast shallow landslides. The validation of the results, carried out using a database of past landslides, provided good results and a good prediction accuracy for the HIRESSS model from both a temporal and spatial point of view.

The 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. Spaceborne 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. The 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.

In the last decade, the combination of rapid development of low cost and small Unmanned Aerial Vehicles (UAVs), improved battery technology and conventional sensors (Optical and LiDAR) in terms of cost and dimensions, led to new opportunities in environmental remote-sensing and 3D surface modelling. A long term monitoring campaign was performed in Ricasoli village, in the Upper Arno river Valley (Tuscany, Italy), to understand the possibility of this rising technology to characterize and to monitor landslides. The RGB and multispectral imageries were analyzed and combined using SfM (Structure from Motion) software, in order to obtain high resolution orthomosaics, point clouds and 3D digital terrain models (DTM). The comparative analysis of the obtained DTMs allowed a very accurate reconstruction and mapping of the detected landslides. The collected data also allowed to precisely detect some slope portions prone to failure and to evaluate the area and volume of the involved masses as well as displacement rates.

In this paper, we present preliminary results of the IPL project No. 198 “Multi-scale rainfall triggering models for Early Warning of Landslides (MUSE).” In particular, we perform an assessment of the geotechnical and hydrological parameters affecting the occurrence of landslides. The aim of this study is to improve the reliability of a physically based model high resolution slope stability simulator (HIRESSS) for the forecasting of shallow landslides. The model and the soil characterization have been tested in Northern Tuscany (Italy), along the Apennine chain, an area that is historically affected by shallow landslides. In this area, the main geotechnical and hydrological parameters controlling the shear strength and permeability of soils have been determined by in situ measurements integrated by laboratory analyses. Soil properties have been statistically characterized to provide more refined input data for the slope stability model. Finally, we have tested the ability of the model to predict the occurrence of shallow landslides in response to an intense meteoric precipitation.

Open image in new window In this work we perform an assessment of the geotechnical and hydrological parameters affecting the occurrence of landslides. The aim of this study is to improve the reliability of the physically-based model HIRESSS (HIgh REsolution Slope Stability Simulator), for the forecasting of shallow landslides. The model and the soil characterization has been tested in northern Tuscany, in Italy, along the Apennine chain, an area that is historically affected by shallow landslides. In the area selected, the main geotechnical and hydrological parameters controlling the shear strength and permeability of soils have been determined by in situ measurements integrated by laboratory analyses. Around 60 survey points have been analyzed. The data obtained have been studied in order to assess the relationships existing among the different parameters and the bedrock lithology. Soil properties have been then statistically characterized and used to define the input parameters in the physical model, with the final aim of testing the ability of the model to predict shallow landslide occurrence in response of an intense meteoric precipitation. The rainfall event selected dates back to October 2010 when an intense precipitation affected the area, triggering around 50 reported shallow landslides. The geotechnical and hydrological data collected allowed to generate input map of parameters for the HIRESSS and the simulations showed substantial improvements in the results compared to the use of literature parameters.

Although shallow landslides are a very widespread phenomenon, large area (e.g. thousands of square kilometres) early warning systems are commonly based on statistical rainfall thresholds, while physically based models are more commonly applied to smaller areas. This work provides a contribution towards the filling of this gap: a forecasting chain is designed assembling a numerical weather prediction model, a statistical rainfall downscaling tool and a geotechnical model for the distributed calculation of the factor of safety on a pixel-by-pixel basis. The forecasting chain can be used to forecast the triggering of shallow landslides with a 48 h lead time and was tested on a 3200 km2 wide area.

In this paper the set-up of a fully functional landslide warning system, based on rainfall thresholds, is described. This work was developed in Tuscany region (Italy), an area characterized by a heterogeneous distribution of relieves and rainfalls. The work started with the initial definition of a single set of rainfall thresholds, but it resulted to be ineffective to EWS purposes. Then a software capable to analyze several rainfall events in short time was developed, in order to overcome the problem of the subjectivity of the analyses. Once the thresholds were defined, a WebGis-based warning system was developed. This system can use both real time and forecasting rainfall data and identifies the most hazardous rainfall of each rain event. The last step of this work was the updating of the thresholds using an enhanced calibration dataset, to enhance the performances of the EWS and to account for the changes on territory and on rainfall distribution.

This work proposes a methodology to compare the forecasting effectiveness of different rainfall threshold models for landslide forecasting. We tested our methodology with two state-of-the-art models, one using intensity–duration thresholds and the other based on cumulative rainfall thresholds. The first model identifies rainfall intensity–duration thresholds by means of a software program called MaCumBA (MAssive CUMulative Brisk Analyzer) (Segoni et al., 2014a) that analyzes rain gauge records, extracts intensity (I) and duration (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram and identifies the thresholds that define the lower bounds of the I–D values. A back analysis using data from past events is used to identify the threshold conditions associated with the least number of false alarms. The second model (SIGMA) (Sistema Integrato Gestione Monitoraggio Allerta) (Martelloni et al., 2012) is based on the hypothesis that anomalous or extreme values of accumulated rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations. To perform a quantitative and objective comparison, these two models were applied in two different areas, each time performing a site-specific calibration against available rainfall and landslide data. For each application, a validation procedure was carried out on an independent data set and a confusion matrix was built. The results of the confusion matrixes were combined to define a series of indexes commonly used to evaluate model performances in natural hazard assessment. The comparison of these indexes allowed to identify the most effective model in each case study and, consequently, which threshold should be used in the local early warning system in order to obtain the best possible risk management. In our application, none of the two models prevailed absolutely over the other, since each model performed better in a test site and worse in the other one, depending on the characteristics of the area. We conclude that, even if state-of-the-art threshold models can be exported from a test site to another, their employment in local early warning systems should be carefully evaluated: the effectiveness of a threshold model depends on the test site characteristics (including the quality and quantity of the input data), and a validation procedure and a comparison with alternative models should be performed before its implementation in operational early warning systems.

We propose an original approach to develop rainfall thresholds to be used in civil protection warning systems for the occurrence of landslides at regional scale (i.e. tens of thousands of kilometres), and we apply it to Tuscany, Italy (23 000 km2). Purpose-developed software is used to define statistical intensity–duration rainfall thresholds by means of an automated and standardized analysis of rainfall data. The automation and standardization of the analysis brings several advantages that in turn have a positive impact on the applicability of the thresholds to operational warning systems. Moreover, the possibility of defining a threshold in very short times compared to traditional analyses allowed us to subdivide the study area into several alert zones to be analysed independently, with the aim of setting up a specific threshold for each of them. As a consequence, a mosaic of several local rainfall thresholds is set up in place of a single regional threshold. Even if pertaining to the same region, the local thresholds vary substantially and can have very different equations. We subsequently analysed how the physical features of the test area influence the parameters and the equations of the local thresholds, and found that some threshold parameters can be put in relation with the prevailing lithology. In addition, we investigated the possible relations between effectiveness of the threshold and number of landslides used for the calibration. A validation procedure and a quantitative comparison with some literature thresholds showed that the performance of a threshold can be increased if the areal extent of its test area is reduced, as long as a statistically significant landslide sample is present. In particular, we demonstrated that the effectiveness of a warning system can be significantly enhanced if a mosaic of site-specific thresholds is used instead of a single regional threshold.

SIMBIOSYS is a highly integrated instrument suite that will be mounted on-board BepiColombo, which is the fifth cornerstone mission of the European Space Agency dedicated to the exploration of the planet Mercury and it is expected to be launched in 2016. The SIMBIOSYS instrument consists of three channels: the STereo imaging Channel (STC), with broad spectral bands in the 400–950 nm range and medium spatial resolution (up to 50 m/px); the High Resolution Imaging Channel (HRIC), with broad spectral bands in the 400–900 nm range and high spatial resolution (up to 5 m/px), and the Visible and near- Infrared Hyperspectral Imaging channel (VIHI), with high spectral resolution (up to 6 nm) in the 400–2000 nm range and spatial resolution up to 100 m/px. The on-ground calibration system has to cover the full spectral range of the instrument, i.e. from 400 to 2000 nm, and the emitted radiance has to vary over a range of four decades to account for both simulations of Mercury surface acquisition and star field observations. The methods and the results of the measurements done to calibrate the integrating sphere needed for the on-ground radiometric testing of the SIMBIOSYS instrument will be given and discussed. Temporal stability, both on short and long periods, spatial and spectral uniformity, and the emitted radiance for different lamp configurations and different shutter apertures have been measured. The results of the data analysis confirm that the performance of the integrating sphere is well suited for the radiometric calibration of all the three different channels of the SIMBIOSYS instrument.

In this paper, a methodology to automate and standardize the identification of rainfall intensity-duration thresholds for landslides triggering is presented. A newly developed software called MaCumBA (MAssive CUMulative Brisk Analyzer) can be used to analyze rain-gauge records, extract the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plot these values on a diagram and identify thresholds that define the lower bounds of the aforementioned I-D values. Because the methodology is automated, it is possible to process a relevant amount of data in short times, while allowing for user decision input. A back analysis using data from past events that did not trigger landslides can be used to identify the threshold conditions associated with the least amount of false alarms. We applied the methodology in two test sites. A validation procedure returned satisfactory results, demonstrating the potential utility of the proposed methodology in the development of landslide warning systems.

The HERSCHEL/SCORE is a suborbital mission which will observe the solar corona in UV and in visible light for measurements of solar corona. The coronagraph for such observation is an Italian instrument and, in particular, the CCD camera detectors are developed at the XUVLab of the Department of Astronomy and Space Science of Florence University. Such detectors communicate with the onboard computer by means the IEEE1355 Spacewire standard interface (developed in our laboratories) and implement a lot of smart and custom procedures for imaging. The main innovation of SCORE coronagraph is the first use in space of a variable retarder plate based on liquid crystals and the optical design capable of simultaneous observation in UV and Visible light.

In the Tuscany region (23,000 km2, Central Italy) landslides triggered by rainfall are a recurring phenomenon. We set up a regional warning system for the prediction and monitoring of the occurrence of landslides, which is based on statistical intensity–duration rainfall thresholds. Since a single regional threshold would be affected by a too large uncertainty, the region was partitioned into 25 alert zones and for each of them an independent set of thresholds was defined analyzing with an automated and objective procedure the rainfall measurements connected to the triggering of 2,132 past landslides.

"The paper describes the activities developed within the work package 4.1 of the UE\/FP7 SAFELAND Project. The first scope of this research activity is to define and to implement a warning system for shallow landslide prediction, at large and slope scale, based on the forecast precipitation. The warning system is based on different numerical tools and simulation models: stability analysis model at slope and regional scale and numerical weather prediction models (global and regional) and downscaling algorithms"

The fluorescent emission from film samples of representative oils has been investigated by means of two independent experiments: (i) time-resolved fluorosensing at a fixed excitation frequency, by which the spectral emission yield and the associated decay times, tau(lambda), were determined, and (ii) monitoring of the integrated fluorescence in a fixed spectral band as a function of film thickness, from which extinction coefficients alpha(lambda) were derived at a number of excitation frequencies. After checking the good mutual consistency of corresponding emission data obtained in the two types of experiments, a unified analysis was elaborated in terms of a renormalized conversion efficiency, i.e., correcting the measured spectral yields for the ratio (tau/alpha). This quantity can be shown by an ppropriate model to be typical of the emitting fluorophores but independent of absorption or quenching effects due to the complex oil medium. This was indeed found to be the case for a large variety of oils, in spite of extreme variations in their absolute emission yield.

The HERSCHEL (helium resonant scattering in the corona and heliosphere) experiment is a rocket mission that was successfully launched last September from White Sands Missile Range, New Mexico, USA. HERSCHEL was conceived to investigate the solar corona in the extreme UV (EUV) and in the visible broadband polarized brightness and provided, for the first time, a global map of helium in the solar environment. The HERSCHEL payload consisted of a telescope, HERSCHEL EUV Imaging Telescope (HEIT), and two coronagraphs, HECOR (helium coronagraph) and SCORE (sounding coronagraph experiment). The SCORE instrument was designed and developed mainly by Italian research institutes and it is an imaging coronagraph to observe the solar corona from 1.4 to 4 solar radii. SCORE has two detectors for the EUV lines at 121.6 nm (HI) and 30.4 nm (HeII) and the visible broadband polarized brightness. The SCORE UV detector is an intensified CCD with a microchannel plate coupled to a CCD through a fiber-optic bundle. The SCORE visible light detector is a frame-transfer CCD coupled to a polarimeter based on a liquid crystal variable retarder plate. The SCORE coronagraph is described together with the performances of the cameras for imaging the solar corona.

Solar coronagraphs in formation ying require several mechanical and technological constraints to be met. One of the most critical issues is the external occulter design and its optimization. The occulter edge requires special attention in order to minimize the diraction while being compatible with the constraints of handling and integrating large delicate space components. Moreover, it is practically impossible to realize a full scale model for laboratory tests. This article describes the results of tests performed with a scaled-model breadboard of the ASPIICS coronagraph disk edge, using the Articial Sun facility at Laboratoire d'Astrophysique de Marseille.

HERSCHEL is a suborbital mission which will observe the solar corona in the UV and visible light by means of two coronagraphs and an EUV imager. One of the two coronagraphs is SCORE (Sounding CORonagraphic Experiment), developed mainly by some Italian scientific institutions. SCORE performs imaging of the extended corona from 1.4 to 4 solar radii in the broadband visible and in the UV lines HI 121.6 nm and HeII 30.4 nm. The CCD visible camera (VLD) of SCORE has been designed, built and characterized at the XUVLab of the University of Florence. In this paper we will describe the VLD calibration and testing performed before launch in order to evaluate the performances of SCORE.

We describe the design and first calibration tests of an imaging polarimeter based on Liquid Crystal Variable Retarders (LCVRs), for the study of the solar K-corona. This K-polarimeter (KPol) is part of the visible light path of the UltraViolet and Visible-light Coronal Imager (UVCI) of the Sounding-rocket Coronagraphic Experiment (SCORE). SCORE/UVCI is an externally occulted, off-axis Gregorian telescope, optimized for the narrow-band (i.e., λ/uλ ~10) imaging of the HeII, λ 30.4 nm and HI λ 121.6 nm coronal emission. We present some preliminary results of the application of LCVR plates to measurements of linear polarized radiation. LCVR plates replace mechanically rotating retarders with electro-optical devices, without no moving parts. LCVR are variable waveplates, in which the change of the retardance is induced by a variable applied voltage. The retardance of a LCVR is a function of the wavelength. KPol observations of the visible coronal continuum of the Sun (K-corona) will be made over the 450-600 nm wavelength band. We have studied the LCVR's properties in this bandpass. We tested a LCVR plate assembled in a linear polarization rotator configuration to measure the polarization plane rotation of input radiation as a function of wavelength. We estimated the LCVR's chromatic response in the KPol wavelength bandpass. The preliminary results show reasonable achromatic behaviour at high regimes of the driving voltage, Vd (i.e., Vd>3 volt).

Limite de detection de 8 pg/ml permettant la determination directe de thallium dans 3 echantillons commerciaux de Pb

A carbon rod atomizer was used for sample introduction into a commercial inductively coupled plasma for the determination of lead in whole blood. Samples of known lead concentration were either treated with Triton-X or nitric acid or diluted 1+5 with distilled water and analyzed by comparison against graphs obtained using aqueous solutions and using the standard additions method. Both approaches produced similar results indicating no appreciable matrix influence. The Pb concentration values obtained were in close agreement with those previously determined by ETA-AAS, Delves′ cup-FAAS and anodic stripping voltammetry. Signal integration and careful selection of the measurement period were critical to obtain accurate results. Derived concentrations were shown to be essentially independent of the heating rate of the vaporization unit and the length of tubing used to transport the material into the plasma. Using a 1 μg ml−1 lead aqueous standard, a signal to background ratio of 5.5 was obtained under...

Soil thickness is a well-known factor controlling shallow landsliding. Notwithstanding, its spatial organisation over large areas is poorly understood, and in basin scale slope analyses it is often established using simple methods. In this paper, we apply five different soil thickness models in two test sites, and we use the obtained soil thickness maps to feed a slope stability model. Validation quantifies how errors in soil thickness influence the resulting factor of safety and points out which method grants the best results. In particular, in our cases, slope-derived soil thickness patterns produced the worst slope stability assessment, while the use of reliable soil thickness maps obtained by means of a more complex geomorphologically indexed model improved shallow landslides modelling.

A simple method for the determination of lead in blood by atomic-fluorescence spectrometry is described in which the sample is diluted with Triton-X (1+10). The sample is then nebulised directly into an argon-separated air-acetylene flame burning on a circular, home-made, capillary burner. Aqueous standards can be used for calibration purposes. The direct line fluorescence of lead at 405.8 nm is measured after excitation at 283.3 nm provided by a frequency doubled pulsed tunable dye laser pumped by a XeCl excimer laser, thus avoiding any scattering due to the matrix. The laser peak power was approximately 40 kW at the UV wavelength and the fluorescence was highly saturated even when the beam size was expanded in the flame to ca. 15 mm diameter. By diluting 0.1 ml of blood to 1 ml and using discrete sampling in the flame, the detection limit was found to be 4 ng ml–1 and can be decreased considerably by taking a larger volume of blood. Several blood samples, as well as quality control samples, were analysed and the results found to be in very close agreement with those provided by the well established Delves cup atomic-absorption, graphite furnace atomic-absorption and anodic-stripping voltammetry methods.

A double-beam thermal lensing experiment based upon a pulsed dye laser as the excitation beam and a He-Ne laser as a probe beam is described. The technique has been used to detect the small absorptions given by uranyl ions in aqueous solution. The system is capable of detecting absorption coefficients as low as 5 × 10–7 cm–1. Moreover, by changing several dyes, an absorption spectrum can be obtained at concentration levels (ca. 4 × 10–6M) far below (ca. 103×) those obtained by conventional absorption spectrophotometry, thereby allowing the direct study of the chemical equilibria involved. The sensitivity of the present apparatus is limited by short-term fluctuations of the probe laser.