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The spatial resolution of digital elevation models (DEMs) is an important factor for reliable landslide studies. Multi-interferometric techniques such as persistent scatterer interferometric synthetic aperture radar (PSInSAR) are used to evaluate the landslide state of activity and its ground deformation velocity, which is commonly measured along the satellite line of sight (LOS). In order to compare velocities measured by different satellites in different periods, their values can be projected along the steepest slope direction, which is the most probable direction of real movement. In order to achieve this result, DEM-derived products are needed. In this paper, the effectiveness of different DEM resolutions was evaluated in order to project ground deformation velocities measured by means of PSInSAR technique in two different case studies in the Messina Province (Sicily, southern Italy): San Fratello and Giampilieri. Three DEMs were used: (i) a 20-m resolution DEM of the Italian Military Geographic Institute (IGM), (ii) a 2-m resolution DEM derived from airborne laser scanning (ALS) light detection and ranging (LiDAR) data for the San Fratello 2010 landslide, and (iii) a 1-m resolution DEM derived from ALS LiDAR data for the area of Giampilieri. The evaluation of the applied method effectiveness was performed by comparing the DEMs elevation with those of each single permanent scatterer (PS) and projecting the measured velocities along the steepest slope direction. Results highlight that the higher DEM resolution is more suitable for this type of analysis; in particular, the PS located nearby the watershed divides is affected by geometrical problems when their velocities are projected along the steepest slope. [ABSTRACT FROM AUTHOR]

The results of the continuous monitoring of ground deformation throughout the Tuscany region using radar images acquired by the Sentinel-1 satellite constellation of the European Space Agency (ESA) are presented here. This new monitoring approach, based on systematic imagery processing and analysis of deformation time series, is discussed at regional (for the entire Tuscany) and at local scale in the context of a case study of the Carpineta landslide, which is a large, active earth slide in the Northern Apennines (Pistoia province). The landslide registered an acceleration during the winter and spring of 2018 as a direct consequence of rainfall and snow melt. The increase in the deformation rate of the landslide, which led to the damage of several buildings, was promptly detected and monitored due to the enhanced temporal repetitiveness offered by the Sentinel-1 constellation. The results demonstrate that advances in satellite sensors, increases in computing capacity and the refinement of processing approaches and data screening tools can contribute to the development of new paradigms in satellite-based monitoring systems. Sentinel-1 data, which are systematically acquired with short revisiting times and then promptly processed, can now be used as a tool for the systematic tracking of ground deformation at the regional scale and for the continuous monitoring of slow and very slow landslides. [ABSTRACT FROM AUTHOR]

The High City of Antananarivo is one of the most important cultural heritage sites of Madagascar, on the UNESCO Tentative List since 2016. Built on the hilltop of the Analamanga Hill, a granite ridge overlooking the Ikopa River valley, it is renowned for its baroque-style palaces, such as the Rova royal complex, and neo-Gothic cathedrals dating back to the nineteenth century. During the winter of 2015, the twin cyclones Bansi and Chedza hit the urban area of Antananarivo, triggering floods and shallow landslides, as well as causing thousands of evacuees and many casualties. Between 2018 and 2019 several rockfalls occurred from the rock cliffs of the Analamanga hills, destroying housings and killing over 30 people. Both events showed that landslides can pose a high risk to the safety of the inhabitants, the infrastructure, and the cultural heritage of the High City. To assess the landslide hazard in the Analamanga Hill area, an integrated approach was adopted by means of the following actions: (i) creation of a multitemporal detailed scale landslide map; (ii) geotechnical characterization of the involved materials; (iii) analysis of landslide susceptibility in soils/loose deposits; (iv) runout analysis of debris flows channeling within large creek gullies; (v) landslide kinematic analysis of the rockmass; (vi) simulation of rockfall trajectories; (vii) analysis of rainfall data. The results show that the main factors affecting landslides are slope, lithology, creek-gully erosion, and anthropization, while most of the landslide events are clearly triggered by heavy rainfall. The landslide-prone areas (the phenomena include shallow landslides, rock falls, and debris flows) are located primarily along the cliff bounding the western hill slope, the southeastern sector (where abandoned quarries form large slope cuts), and subordinately in the steep creek catchment just east of the Rova. The thematic maps produced represent fundamental land use management tools to be used in Geo Disaster Risk Reduction (GDRR) by scientists, practitioners and the decision-makers involved in the High City protection and conservation. The study conducted represents an important contribution for improving the knowledge on landslide processes in an area with limited data such as Madagascar, and may be reproduced in cultural heritage sites characterized by similar geomorphological and urban scenarios. [ABSTRACT FROM AUTHOR]

In this manuscript, an integrated strategy that exploits both phase and amplitude features of satellite SAR (synthetic aperture radar) images and ground data is proposed for deriving the deformation field induced by a complex landslide that affected part of the village of Ponzano (Abruzzi Region, Central Italy). The February 12, 2017, landslide was triggered by the combined effects of intense rainfalls and snowmelt that saturated the slope. The SqueeSAR algorithm was applied to two C-band SAR datasets, composed by Radarsat-2 and Sentinel-1 images, spanning a nine-year time interval before the landslide occurrence. Moreover, the amplitude information carried by two TerraSAR-X images, acquired immediately before and after the event, was exploited to derive the total displacement generated by the landslide movement by means of the RMT (rapid motion tracking) algorithm. The obtained results allow describing the landslide behavior before and after its failure. In particular, the back-monitoring analysis shows that the landslide was already slowly moving, with deformation rates increasing from the Radarsat-2 to the Sentinel-1 monitored periods, 10 years before its complete mobilization. The landslide failure of February 2017 produced maximum displacements of about 10 m in some sectors of the affected area. The registered deformation rates and the localization of the maximum displacements areas were confirmed by field data, collected during a field campaign and a helicopter recognizance of the damaged areas, both performed after the event. [ABSTRACT FROM AUTHOR]

Susceptibility of intrusion-related landslides in an active volcano was evaluated coupling the landslide susceptibility estimation by random forest (RF), and the probabilistic volcanic vent opening distribution, as proxy for magma injection, using the QVAST tool. In order to develop and test the method proposed here, the RF/QVAST approach was adopted for Stromboli volcano (Southern Italy) since it experienced moderate to huge instability events, it is geomorphologically prone to instability events, and it is affected by active intense volcanic activity that can produce slope instability. The main destabilizing factors of the volcanic flanks are the slope, the aspect, the terrain roughness, the land cover and the litho-technical features of the outcropping rocks. Estimation of volcanic susceptibility shows that the areas with high probability of new vent opening are located in the north-western unstable volcano flank (Sciara del Fuoco), in the volcano summit and the north-eastern volcano flank coherent with the possible re-activation of the eruptive fissures related to the regional tectonic setting. The areas with higher probability of intrusion-related landslides are located in the upper part of the Sciara del Fuoco, while the rest of the island show moderate to low probability of intrusion-related landslide occurrence. [ABSTRACT FROM AUTHOR]