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Landslide susceptibility maps (LSM) are commonly used by local authorities for land use management and planning activities, representing a valuable tool used to support decision makers in urban and infrastructural planning. The accuracy of a landslide susceptibility map is affected by false negative and false positive errors which can decrease the reliability of this useful product. In particular, false negative errors, are generally worse in terms of social and economic losses with respect to the losses associated with false positives. In this paper, we present a new technique to improve the accuracy of landslide susceptibility maps using Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) data. The proposed approach uses two different data sets acquired in ascending and descending geometry. The PS velocity measured along the line of sight is re-projected into a new velocity along the steepest slope direction ( V Slope ). Integration between the LSM and the ground deformation velocity map along the slope was performed using an empirical contingency matrix, which takes into account the average V Slope and the susceptibility degree obtained using the Random Forests algorithm. The Results show that the susceptibility degree increased in 56.41 km 2 of the study area. The combination of PSInSAR data and the landslide susceptibility map (LSM) improved the prediction reliability of slow moving landslides, which particularly affect urbanized areas. The use of this procedure can be easily applied in different areas where PSI data sets are available. This approach will help planning and decision-making authorities produce reliable landslide susceptibility maps, correcting some of the LSM errors. [ABSTRACT FROM AUTHOR]

The management of the coastal environment is a complex issue, which needs for appropriate methodologies. Erosional processes and longshore currents present in the submerged beach represent a serious danger for both people and human infrastructures. A proper integration between traditional and innovative techniques can help in the characterization and management of the beach environment. Several different multispectral and hyperspectral techniques were used to retrieve information about the hydro and morphodynamic settings of the Pisa province coast (Tuscany, Italy). Results were validated using about 130 samples collected along the study area, between the mouths of the Serchio river and the Scolmatore canal. The composition of sand samples was evaluated by means of petrographic microscopy and grain size analyses. The same samples were analyzed using an Analytical Spectral Device (ASD) Fieldspec. The obtained sediment spectral library was used to evaluate the differences in mineralogical composition, which can be related to different source areas. Results coming from spectroscopy were compared to those obtained from the petrographic and grain size analysis. Furthermore a multispectral aerial image was used to evaluate sediment distribution along the submerged beach, to map the geomorphic features and to detect the presence of longshore and rip currents. This works suggests that optical remote sensing technique can be profitably used in order to reduce the need for expensive and time consuming conventional analysis. [ABSTRACT FROM AUTHOR]

Buildings are sensitive to movements caused by ground deformation. The mapping both of spatial and temporal distribution, and of the degree of building damages represents a useful tool in order to understand the landslide evolution, magnitude and stress distribution. The high spatial resolution of space-borne SAR interferometry can be used to monitor displacements related to building deformations. In particular, PSInSAR technique is used to map and monitor ground deformation with millimeter accuracy. The usefulness of the above mentioned methods was evaluated in San Fratello municipality (Sicily, Italy), which was historically affected by landslides: the most recent one occurred on 14th February 2010. PSInSAR data collected by ERS 1/2, ENVISAT, RADARSAT-1 were used to study the building deformation velocities before the 2010 landslide. The X-band sensors COSMO-SkyMed and TerraSAR-X were used in order to monitor the building deformation after this event. During 2013, after accurate field inspection on buildings and structures, damage assessment map of San Fratello were created and then compared to the building deformation velocity maps. The most interesting results were obtained by the comparison between the building deformation velocity map obtained through COSMO-SkyMed and the damage assessment map. This approach can be profitably used by local and Civil Protection Authorities to manage the post-event phase and evaluate the residual risks. [ABSTRACT FROM AUTHOR]

The instability of lava deltas is a recurrent phenomenon affecting volcanic islands, which can potentially cause secondary events such as littoral explosions (due to interactions between hot lava and seawater) and tsunamis. It has been shown that Interferometric Synthetic Aperture Radar (InSAR) is a powerful technique to forecast the collapse of newly emplaced lava deltas. This work goes further, demonstrating that the monitoring of lava deltas is a successful strategy by which to observe the long-term deformation of subaerial–submarine landslide systems on unstable volcanic flanks. In this paper, displacement measurements derived from Synthetic Aperture Radar (SAR) imagery were used to detect lava delta instability at Stromboli volcano (Italy). Recent flank eruptions (2002–2003, 2007 and 2014) affected the Sciara del Fuoco (SdF) depression, created a “stacked” lava delta, which overlies a pre-existing scar produced by a submarine–subaerial tsunamigenic landslide that occurred on 30 December 2002. Space-borne X-band COSMO-SkyMED (CSK) and C-band SENTINEL-1A (SNT) SAR data collected between February 2010 and October 2016 were processed using the SqueeSAR algorithm. The obtained ground displacement maps revealed the differential ground motion of the lava delta in both CSK and SNT datasets, identifying a stable area (characterized by less than 2 mm/y in both datasets) within the northern sector of the SdF and an unstable area (characterized by velocity fields on the order of 30 mm/y and 160 mm/y in the CSK and SNT datasets, respectively) in the central sector of the SdF. The slope stability of the offshore part of the SdF, as reconstructed based on a recently performed multibeam bathymetric survey, was evaluated using a 3D Limit Equilibrium Method (LEM). In all the simulations, Factor of Safety (F) values between 0.9 and 1.1 always characterized the submarine slope between the coastline and −250 m a.s.l. The critical surfaces for all the search volumes corresponded to the 30 December 2002 landslide, which involved the lava delta and its surrounding areas. InSAR data provided the post-effusive deformation field after the 2007 and 2014 flank eruptions, whereas LEM results highlighted that the accumulation of lava flows on the prone-to-failure SdF submarine slope is the main cause of the detected lava delta deformation. Lava delta instability, measured also at Pico Island (Azores) and Kilauea volcano (Hawaii), is evidence of the broader spectrum of instability phenomena that take place in the coastal or submarine area of the flanks of the volcanoes. At Kilauea, past lava deltas have moved faster than the surrounding slope and the recorded movements relate only to the collapses of the deltas themselves, producing rapid mass wasting near the coasts. In contrast, at Stromboli and Pico, lava deltas move at the same velocity as the surrounding slope. In these cases, the displacement at lava deltas can be considered as a proxy for the deformation of submarine slides. There are very few studies dealing with lava delta deformation, thus, the analysis presented in this work will benefit the monitoring of submarine slopes in other prone-to-failure coastal or island volcanic systems which have the potential to generate tsunamis. [ABSTRACT FROM AUTHOR]

The 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(tm) (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 14 min, 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. [ABSTRACT FROM AUTHOR]