Lorenzo Solari

Badland susceptibility assessment in Volterra municipality (Tuscany, Italy) by means of GIS and statistical analysis

Badlands can be defined as complex and peculiar types of erosional formations that develop in clayey environments and are mainly favoured by lithological and topographic features, as well as by markedly seasonal climate. This work aims at assessing badland susceptibility in Volterra municipality located in Tuscany region (Italy) by means of bivariate statistical analysis implemented in a geographic information system. The Volterra municipality is affected by intense soil erosion processes, including rill and gully erosion usually turned out as badland forms, mostly occurring on Pliocene–Pleistocene clayey sediments. Firstly, an inventory of 234 badland areas was produced on the basis of an available pre-existing database, integrated with the interpretation of aerial photographs and supported by a field survey. Badlands were distinguished in type A and type B, according to different evolutional stage, vegetation presence and consequently different landforms. Then, nine geoenvironmental factors supposed to be predisposing for badland occurrence were chosen and combined with the spatial frequency of badland areas derived from the inventory, through Information Value Statistic approach. The result was a badland susceptibility map that highlights a strong control of lithology, slope gradient and land use in conditioning badland development in the investigated area. The effectiveness of the performed model was demonstrated by a validation test computed through a receiver operating characteristics analysis. The outcomes of this work provide an updated badland database that is useful for soil erosion management and further land-use planning within the Volterra municipality.

PSInSAR Analysis in the Pisa Urban Area (Italy): A Case Study of Subsidence Related to Stratigraphical Factors and Urbanization

Permanent Scatterer Interferometry (PSI) has been used to detect and characterize the subsidence of the Pisa urban area, which extends for 33 km2 within the Arno coastal plain (Tuscany, Italy). Two SAR (Synthetic Aperture Radar) datasets, covering the time period from 1992 to 2010, were used to quantify the ground subsidence and its temporal evolution. A geotechnical borehole database was also used to make a correspondence with the detected displacements. Finally, the results of the SAR data analysis were contrasted with the urban development of the eastern part of the city in the time period from 1978 to 2013. ERS 1/2 (European Remote-Sensing Satellite) and Envisat SAR data, processed with the PSInSAR (Permanent Scatterer InSAR) algorithm, show that the investigated area is divided in two main sectors: the southwestern part, with null or very small subsidence rates (<2 mm/year), and the eastern portion which shows a general lowering with maximum deformation rates of 5 mm/year. This second area includes deformation rates higher than 15 mm/year, corresponding to small groups of buildings. The case studies in the eastern sector of the urban area have demonstrated the direct correlation between the age of construction of buildings and the registered subsidence rates, showing the importance of urbanization as an accelerating factor for the ground consolidation process.

A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images

This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1) data and the DInSAR (Differential Interferometric Synthetic Aperture Radar) technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and ground-subsidence) of a given area by exploiting the wide area coverage and the high coherence and temporal sampling (revisit time up to six days) provided by the S-1 satellites. The main products of the procedure are two updatable maps: the deformation activity map and the active deformation areas map. These maps present two different levels of information aimed at different levels of geohazard risk management, from a very simplified level of information to the classical deformation map based on SAR interferometry. The methodology has been successfully applied to La Gomera, Tenerife and Gran Canaria Islands (Canary Island archipelago). The main obtained results are discussed.

The Calatabiano landslide (southern Italy): preliminary GB-InSAR monitoring data and remote 3D mapping

On 24 October 2015, following a period of heavy rainfall, a landslide occurred in the Calatabiano Municipality (Sicily Island, Southern Italy), causing the rupture of a water pipeline supplying water to the city of Messina. Following this event, approximately 250,000 inhabitants of the city suffered critical water shortages for several days. Consequently, on 6 November 2015, a state of emergency was declared (O.C.D.P. 295/2015) by the National Italian Department of Civil Protection (DPC). During the emergency management phase, a provisional by-pass, consisting of three 350-m long pipes passing through the landslide area, was constructed to restore water to the city. Furthermore, on 11 November 2015, a landslide remote-sensing monitoring system was installed with the following purposes: (i) analyse the landslide geomorphological and kinematic features in order to assess the residual landslide risk and (ii) support the early warning procedures needed to ensure the safety of the personnel involved in the by-pass construction and the landslide stabilization works. The monitoring system was based on the combined use of Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR) and terrestrial laser scanning (TLS). In this work, the preliminary results of the monitoring activities and a remote 3D map of the landslide area are presented.

Continuous, semi-automatic monitoring of ground deformation using Sentinel-1 satellites

We present the continuous monitoring of ground deformation at regional scale using ESA (European Space Agency) Sentinel-1constellation of satellites. We discuss this operational monitoring service through the case study of the Tuscany Region (Central Italy), selected due to its peculiar geological setting prone to ground instability phenomena. We set up a systematic processing chain of Sentinel-1 acquisitions to create continuously updated ground deformation data to mark the transition from static satellite analysis, based on the analysis of archive images, to dynamic monitoring of ground displacement. Displacement time series, systematically updated with the most recent available Sentinel-1 acquisition, are analysed to identify anomalous points (i.e., points where a change in the dynamic of motion is occurring). The presence of a cluster of persistent anomalies affecting elements at risk determines a significant level of risk, with the necessity of further analysis. Here, we show that the Sentinel-1 constellation can be used for continuous and systematic tracking of ground deformation phenomena at the regional scale. Our results demonstrate how satellite data, acquired with short revisiting times and promptly processed, can contribute to the detection of changes in ground deformation patterns and can act as a key information layer for risk mitigation.

Fast detection of ground motions on vulnerable elements using Sentinel-1 InSAR data

ABSTRACT The detection of active movements that could threat the infrastructures and the population is one of the main priorities of the risk management chain. Interferometric Synthetic Aperture Radar (InSAR) techniques represent one of the most useful answers to this task; however, it is difficult to manage the huge amount of information derived from the interferometric analysis. In this work, we present a procedure for deriving impact assessment maps, over a regional test site, using as starting point Sentinel-1 SAR (Synthetic Aperture Radar) images and a catalogue of elements at risk that acts as a second input of the methodology. We applied the proposed approach, named as Vulnerable Elements Activity Maps (VEAM), to the islands of Gran Canaria, La Gomera and Tenerife (Spain), where we analysed SAR images covering the time interval November 2014–September 2016. The methodology, meant to be a powerful tool for reducing the time needed for a complete analysis of a full stack of InSAR data, is ideally suited for Civil Protection Authorities. The application of the methodology allowed to detect 108 areas affected by active deformation that are threatening one or more elements at risk in 25 municipalities of the three islands.

Mapping Vulnerable Urban Areas Affected by Slow-Moving Landslides Using Sentinel-1 InSAR Data

Landslides are widespread natural hazards that generate considerable damage and economic losses worldwide. Detecting terrain movements caused by these phenomena and characterizing affected urban areas is critical to reduce their impact. Here we present a fast and simple methodology to create maps of vulnerable buildings affected by slow-moving landslides, based on two parameters: (1) the deformation rate associated to each building, measured from Sentinel-1 SAR data, and (2) the building damage generated by the landslide movement and recorded during a field campaign. We apply this method to Arcos de la Frontera, a monumental town in South Spain affected by a slow-moving landslide that has caused severe damage to buildings, forcing the evacuation of some of them. Our results show that maximum deformation rates of 4 cm/year in the line-of-sight (LOS) of the satellite, affects La Verbena, a newly-developed area, and displacements are mostly horizontal, as expected for a planar-landslide. Our building damage assessment reveals that most of the building blocks in La Verbena present moderate to severe damages. According to our vulnerability scale, 93% of the building blocks analysed present high vulnerability and, thus, should be the focus of more in-depth local studies to evaluate the serviceability of buildings, prior to adopting the necessary mitigation measures to reduce or cope with the negative consequences of this landslide. This methodology can be applied to slow-moving landslides worldwide thanks to the global availability of Sentinel-1 SAR data.

Remote 3D Mapping and GB-InSAR Monitoring of the Calatabiano Landslide (Southern Italy)

Open image in new window On October 24th 2015, following a period of heavy rainfall, a landslide triggered in the Calatabiano Municipality (Sicily Island, Southern Italy) causing the rupture of a water pipeline transect of the aqueduct supplying water to the city of Messina. This event, caused critical water shortages for several days to a large part of the city inhabitants. In order to restore the city water supplies, a provisional by-pass, consisting of three 350 m long pipes passing through the landslide area, was carried out. On November 11th 2015, a landslide monitoring system was installed, based on the combined use of advanced remote sensing techniques such as Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR), Terrestrial Laser Scanning (TLS) and Infrared Thermography (IRT). The installed monitoring system allowed to: (i) analyze the landslide geomorphological and kinematic features in order to assess the landslide residual risk; (ii) support the early warning procedures needed to ensure the safety of the personnel involved in the by-pass realization and the landslide stabilization works. In this work, the preliminary results of the monitoring activities and a 3-D mapping of the landslide area are presented.

Satellite Data to Improve the Knowledge of Geohazards in World Heritage Sites

According to the United Nations Educational, Scientific and Cultural Organization (UNESCO) agency, the World Heritage Sites (WHS) inscribed in the World Heritage List (WHL) must be safeguarded with an adequate protection system, in order to guarantee their integrity and authenticity. Currently, many UNESCO sites are threatened by geohazards, but the safeguard of these sites does not seem to be wide-ranging. Looking at the standard list of factors affecting the Outstanding Universal Value (OUV) of WHS, which has been adopted by the World Heritage Committee in 2008, it seems that only “sudden geological events” are considered as factors that undermine the protection of the properties. Furthermore, it is well known that slow-kinematic phenomena can also threaten cultural and natural heritage. This study proposes a satellite InSAR-based procedure to identify and monitor the temporal and spatial evolution of ground deformation related to slow-kinematic geohazards (slow-moving landslides and ground-subsidence). This procedure, applied in this work on the Tuscany Region (Italy), simplify the InSAR products interpretation, making them easily exploitable by the local WHS managers for long-term geohazards monitoring and conservation strategies. These activities, thanks to the main characteristics of the recent Sentinel-1 data (short revisit time, free availability without any restrictions and worldwide coverage), can be defined for each UNESCO site of the world.

A GIS-Based Procedure for Landslide Intensity Evaluation and Specific risk Analysis Supported by Persistent Scatterers Interferometry (PSI)

The evaluation of landslide specific risk, defined as the expected degree of loss due to landslides, requires the parameterization and the combination of a number of socio-economic and geological factors, which often needs the interaction of different skills and expertise (geologists, engineers, planners, administrators, etc.). The specific risk sub-components, i.e., hazard and vulnerability of elements at risk, can be determined with different levels of detail depending on the available auxiliary data and knowledge of the territory. These risk factors are subject to short-term variations and nowadays turn out to be easily mappable and evaluable through remotely sensed data and GIS (Geographic Information System) tools. In this work, we propose a qualitative approach at municipal scale for producing a “specific risk” map, supported by recent satellite PSI (Persistent Scatterer Interferometry) data derived from SENTINEL-1 C-band images in the spanning time 2014–2017, implemented in a GIS environment. In particular, PSI measurements are useful for the updating of a landslide inventory map of the area of interest and are exploited for the zonation map of the intensity of ground movements, needed for evaluating the vulnerability over the study area. Our procedure is presented throughout the application to the Volterra basin and the output map could be useful to support the local authorities with updated basic information required for environmental knowledge and planning at municipal level. Moreover, the proposed procedure is easily managed and repeatable in other case studies, as well as exploiting different SAR sensors in L- or X-band.