Search

The island of Gran Canaria (Canary Islands, Spain) is characterized by a large variability of volcanic rocks reflecting its volcanic evolution. The geological map provided by Geological Survey of Spain at 1:25.000 scale shows more than 109 different lithologies and it is too complex for environmental and engineering purposes. This work presents a simplified geotechnical map with a small number of classes grouping up units with similar geotechnical behaviours. The lithologies were grouped using about 350 rock samples, collected in the seven major islands of the Archipelago. The geotechnical map was used to model rockfall hazard in the entire island of Gran Canaria, where rockfalls are an important threat. The rockfall map was validated with 128 rockfall events along the GC-200 road, located in the NW sector of Gran Canaria. About 96% of the events occurred along sections of the road where the number of expected trajectories is high or moderate. [ABSTRACT FROM AUTHOR]

In the last decade satellite remote sensing has become an effective tool for monitoring geo-hazard-induced ground motions, and has been increasingly used by the scientific community. Direct and indirect costs due to geo-hazards are currently rising, causing serious socio-economics and casualty losses. Therefore, creating a priority list turns out to be essential to highlight the most relevant ground deformations and to better focus risk management practices at regional scale. The Sentinel-1 constellation, thanks to the 6-days repeatability and the free availability of the data, allows to easily update the geo-hazard-induced ground motions, compared to other kind of satellite sensors. In this work, a hot-spot-like method is presented by filtering a large stack of Sentinel-1 images processed by means of the SqueeSAR algorithm. Three periods, with six months repetitiveness, have been analysed in order to evaluate the behaviour and evolution of deformation clusters. The target area is Tuscany Region, located in the central part of Italy and affected by a wide gamma of geohazards, ranging from landslides to large subsidence areas. The final output is a geo-database of ground motions that can be used by regional authorities to prioritize and to effectively plan local risk reduction actions. [ABSTRACT FROM AUTHOR]

The 6-days repeatability of Sentinel-1 constellation allows building up an interferometric stack with unprecedented velocity. Easily updatable hot-spot analyses, frequently repeated following the update of Sentinel-1 images, represent very useful tools for MTInSAR (Multi-Temporal Interferometric Synthetic Aperture Radar) data analysis. Mountain regions are a challenging environment for interferometric analyses because of their climatic, morphological and land cover characteristics. In this context, MTInSAR data can retrieve reliable information over wide areas, with high cost-benefits ratio and where the installation of ground-based devices is not feasible. Considering the well-known limitations of interferometric techniques (such as fast motions or temporal and spatial decorrelation), hot-spot analyses are a viable solution for semi-automatic ground movements extraction over mountain regions. In this work, we present an example of a hot-spot analysis applied to a large stack of MTInSAR products generated by means of SqueeSAR technique over an alpine region (Valle d'Aosta, north-western Italy). The obtained outputs allow detecting 277 moving areas connected to landslides and mass wasting processes in general. These products are intended to be implemented in the landslide risk management chain of the region, focusing on landslide state of activity definition and landslide mapping. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]