Guglielmo Rossi

Landslides triggered by rainfall: A semi-automated procedure to define consistent intensity-duration thresholds

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.

Improving basin scale shallow landslide modelling using reliable soil thickness maps

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.

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

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

Updating EWS rainfall thresholds for the triggering of landslides

In this paper, the updating of rainfall thresholds for landslide early warning systems (EWSs) is presented. Rainfall thresholds are widely used in regional-scale landslide EWSs, but the efficiency of those systems can decrease during the time, so a periodically updating should be required to keep their functionality. The updating of 12 of the 25 thresholds used in the EWS of Tuscany region (central Italy) is presented, and a comparison between performances of new and previous thresholds has been made to highlight the need of their periodical update. The updating has been carried out by collecting ca. 1200 new landslide reports (from 2010 to March 2013) and their respective rainfall data, collected by 332 rain gauges. The comparison has been made by the use of several statistical indexes and showed a marked increasing in the performances of the new thresholds with respect to previous ones.

KPol: liquid crystal polarimeter for K-corona observations from the SCORE coronagraph

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/▵λ ~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 LCVRs 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 LCVRs 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).

Soil characterization for shallow landslides modeling: a case study in the Northern Apennines (Central Italy)

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.

Multitemporal UAV Survey for Mass Movement Detection and Monitoring

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.

Short Term Weather Forecasting for Shallow Landslide Prediction

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.

A Regional Real Time Landslide Warning System Based on Spatially Variable Rainfall Thresholds

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.

Multitemporal UAV surveys for landslide mapping and characterization

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.