Integration between ground based and satellite SAR data in landslide mapping: The San Fratello case study

AbstractThe potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty–clayey sedimentary cover.In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques.PS-InSAR™ (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to be very effective in landslide mapping in the San Fratello test site, representing a valid scientific support for local authorities and decision makers during the post-emergency management

Advanced radar-interpretation of InSAR time series for mapping and characterization of geological processes

We present a new post-processing methodology for the analysis of InSAR (Synthetic Aperture Radar Interferometry) multi-temporal measures, based on the temporal under-sampling of displacement time series, the identification of potential changes occurring during the monitoring period and, eventually, the classification of different deformation behaviours. The potentials of this approach for the analysis of geological processes were tested on the case study of Naro (Italy), specifically selected due to its geological setting and related ground instability of unknown causes that occurred in February 2005. The time series analysis of past (ERS1/2 descending data; 1992–2000) and current (RADARSAT-1 ascending data; 2003–2007) ground movements highlighted significant displacement rates (up to 6 mm yr<sup>−1</sup>) in 2003–2007, followed by a post-event stabilization. The deformational behaviours of instable areas involved in the 2005 event were also detected, clarifying typology and kinematics of ground instability. The urban sectors affected and unaffected by the event were finally mapped, consequently re-defining and enlarging the influenced area previously detected by field observations. Through the integration of InSAR data and conventional field surveys (i.e. geological, geomorphologic and geostructural campaigns), the causes of instability were finally attributed to tectonics

A multidisciplinary investigation of deep-seated landslide reactivation triggered by an extreme rainfall event: a case study of the Monesi di Mendatica landslide, Ligurian Alps

AbstractIn November 2016, an extreme rainfall event affected the Ligurian Alps (NW Italy). Consequently, several landslides and debris flows occurred in the upper Tanarello stream basin. In particular, the village of Monesi di Mendatica was severely damaged by two landslide phenomena: the activation of a rotational landslide, which caused the total collapse of two buildings and part of the main road, and the reactivation of a deep-seated planar massive and a complex landslide, which widely fractured most of the buildings in the village. The latter phenomenon was mostly unknown and had never been monitored prior to the 2016 event. Due to the extensive damage, the village of Monesi was completely evacuated, and the road connecting a ski resort area in the upper part of the valley was closed. Furthermore, a potentially dangerous situation related to the eventual progressive evolution of this landslide that could cause a temporary occlusion of the Tanarello stream still remains. For this reason, we defined the landslide behaviour, triggering conditions and chronological evolution leading to the 2016 event using a multidisciplinary approach. This approach consisted of field surveys, satellite DInSAR time series analyses, digital image correlation techniques, rainfall records analyses, postevent monitoring campaigns and subsurface investigation data analyses, and numerical modelling. This multidisciplinary approach enhanced our understanding of this landslide, which is fundamental to better comprehend its behaviour and possible evolution

A user-oriented methodology for DInSAR time series analysis and interpretation: landslides and subsidence case studies

Recent advances in multi-temporal Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) have greatly improved our capability to monitor geological processes. Ground motion studies using DInSAR require both the availability of good quality input data and rigorous approaches to exploit the retrieved Time Series (TS) at their full potential. In this work we present a methodology for DInSAR TS analysis, with particular focus on landslides and subsidence phenomena. The proposed methodology consists of three main steps: (1) pre-processing, i.e., assessment of a SAR Dataset Quality Index (SDQI) (2) post-processing, i.e., application of empirical/stochastic methods to improve the TS quality, and (3) trend analysis, i.e., comparative implementation of methodologies for automatic TS analysis. Tests were carried out on TS datasets retrieved from processing of SAR imagery acquired by different radar sensors (i.e., ERS-1/2 SAR, RADARSAT-1, ENVISAT ASAR, ALOS PALSAR, TerraSAR-X, COSMO-SkyMed) using advanced DInSAR techniques (i.e., SqueeSAR™, PSInSAR™, SPN and SBAS). The obtained values of SDQI are discussed against the technical parameters of each data stack (e.g., radar band, number of SAR scenes, temporal coverage, revisiting time), the retrieved coverage of the DInSAR results, and the constraints related to the characterization of the investigated geological processes. Empirical and stochastic approaches were used to demonstrate how the quality of the TS can be improved after the SAR processing, and examples are discussed to mitigate phase unwrapping errors, and remove regional trends, noise and anomalies. Performance assessment of recently developed methods of trend analysis (i.e., PS-Time, Deviation Index and velocity TS) was conducted on two selected study areas in Northern Italy affected by land subsidence and landslides. Results show that the automatic detection of motion trends enhances the interpretation of DInSAR data, since it provides an objective picture of the deformation behaviour recorded through TS and therefore contributes to the understanding of the on-going geological processes

Landslide mapping and monitoring by using radar and optical remote sensing: examples from the EC-FP7 project SAFER

This paper focuses on the Landslide Thematic services of the EU-funded FP7-SPACE project SAFER (Services and Applications For Emergency Response) for inventory mapping, monitoring and rapid mapping by using Earth Observation (EO). We exploited satellite Interferometric Synthetic Aperture Radar (InSAR) and Object-Based Image Analysis (OBIA), and discuss example applications in South Tyrol and Abruzzo (Italy), Lower Austria (Austria), Lubietova (Slovakia) and the Kaohsiung County (Taiwan). These case studies showcase the significance of radar and optical EO data, InSAR and OBIA methods for landslide mapping and monitoring in different geological environments and during all phases of emergency management: mitigation, preparedness, crisis and recovery

A robust sar speckle tracking workflow for measuring and interpreting the 3d surface displacement of landslides

We present a workflow for investigating large, slow‐moving landslides which combines the synthetic aperture radar (SAR) technique, GIS post‐processing, and airborne laser scanning (ALS), and apply it to Fels landslide in Alaska, US. First, we exploit a speckle tracking (ST) approach to derive the easting, northing, and vertical components of the displacement vectors across the rock slope for two five‐year windows, 2010–2015 and 2015–2020. Then, we perform post‐processing in a GIS environment to derive displacement magnitude, trend, and plunge maps of the landslide area. Finally, we compare the ST‐derived displacement data with structural lineament maps and profiles extracted from the ALS dataset. Relying on remotely sensed data, we estimate that the thickness of the slide mass is more than 100 m and displacements occur through a combination of slumping at the toe and planar sliding in the central and upper slope. Our approach provides information and interpretations that can assist in optimizing and planning fieldwork activities and site investigations at landslides in remote locations

A Robust SAR Speckle Tracking Workflow for Measuring and Interpreting the 3D Surface Displacement of Landslides

We present a workflow for investigating large, slow-moving landslides which combines the synthetic aperture radar (SAR) technique, GIS post-processing, and airborne laser scanning (ALS), and apply it to Fels landslide in Alaska, US. First, we exploit a speckle tracking (ST) approach to derive the easting, northing, and vertical components of the displacement vectors across the rock slope for two five-year windows, 2010–2015 and 2015–2020. Then, we perform post-processing in a GIS environment to derive displacement magnitude, trend, and plunge maps of the landslide area. Finally, we compare the ST-derived displacement data with structural lineament maps and profiles extracted from the ALS dataset. Relying on remotely sensed data, we estimate that the thickness of the slide mass is more than 100 m and displacements occur through a combination of slumping at the toe and planar sliding in the central and upper slope. Our approach provides information and interpretations that can assist in optimizing and planning fieldwork activities and site investigations at landslides in remote locations

Monitoring and structural significance of ground deformations at Campi Flegrei supervolcano (Italy) from the combined 2D and 3D analysis of PS-InSAR, geophysical, geological and structural data

Cities are growing around active volcanoes. Campi Flegrei supervolcano (CF, Italy) is a nested structure formed during two main collapses associated with two caldera-forming eruptions at 39 ka and 15 ka. The last event occurred in AD 1538 (Monte Nuovo volcano). CF hosts 350,000 people and two main uplift phases were recorded in 1968–1972 and 1982–1984 with deformations of about 2 m. The town of Pozzuoli was partially evacuated during the last crisis. Subsequent minor deformations (subsidence and uplift), seismicity, and diffuse CO2 degassing concentrate in the central part of the caldera. Here, we apply the Permanent Scatterers Synthetic Aperture Radar Interferometry (PS-InSAR) to investigate the ground deformations of CF by using data acquired from 1993 to 2007 from ascending and descending tracks by ERS-1 ,ERS-2 and RADARSAT satellites. Deformation maps identify a subsidence interrupted by micro-uplift episodes. These maps are combined with digitized topographic, geological (faults and landslides), seismic, and urbanization data. The merged information allow us to identify the areas involved in the deformation and the volcanotectonic structures activated during the uplift and subsidence episodes. We propose a structural-volcanological model for the unrest pisodes. Data indicate that uplift episodes, which re associated to seismicity, are followed by subsidence episodes accommodated by pre-existing faults. The urbanized areas subjected to the higher deformations and shaking are also identified and mapped. A multi-hazard zonation including landslides is also provided. The approach used here may be utilized to (a) recognize the tectonic and/or volcanic structures activated during ground deformations, (b) to investigate structural models, (c) to evaluate and map multi-risk zonations, and (c) monitor other volcanic areas or nonvolcanic zones subjected to gravity instability or tectonics