The eye in the sky: Avalanche mapping from space

The Seward Highway in Alaska has over one hundred avalanche paths spread out along a 150 km major transportation corridor, which traverses three different avalanche climatic regimes. This coupled with a small staff can make avalanche debris detection and mapping difficult. With the use of satellite imaging we may have a reliable means of detecting and recording avalanche deposits. During the winter of 2016 the Seward Highway recorded an unprecedented amount of glide avalanche releases. Using SAR imagery we can accurately detect avalanche debris, further aiding in mitigation strategies and avalanche hazard management

Application of unmanned aerial vehicle data and discrete fracture network models for improved rockfall simulations

In this research, we present a new approach to define the distribution of block volumes during rockfall simulations. Unmanned aerial vehicles (UAVs) are utilized to generate high-accuracy 3D models of the inaccessible SW flank of the Mount Rava (Italy), to provide improved definition of data gathered from conventional geomechanical surveys and to also denote important changes in the fracture intensity. These changes are likely related to the variation of the bedding thickness and to the presence of fracture corridors in fault damage zones in some areas of the slope. The dataset obtained integrating UAV and conventional surveys is then utilized to create and validate two accurate 3D discrete fracture network models, representative of high and low fracture intensity areas, respectively. From these, the ranges of block volumes characterizing the in situ rock mass are extracted, providing important input for rockfall simulations. Initially, rockfall simulations were performed assuming a uniform block volume variation for each release cell. However, subsequent simulations used a more realistic nonuniform distribution of block volumes, based on the relative block volume frequency extracted from discrete fracture network (DFN) models. The results of the simulations were validated against recent rockfall events and show that it is possible to integrate into rockfall simulations a more realistic relative frequency distribution of block volumes using the results of DFN analyse

Earthquake-induced Landslides Mapping By Combined Analyses Of Satellite DInSAR And Optical Data: The 24th August, 2016 Amatrice Earthquake (Italy).

On the 24th August, 2016 Central Italy was struck by a Mw 6.0 earthquake with an epicentral area near the city of Amatrice. Several landslides were triggered by the shaking in an area circa 30km in radius from the epicentral area (http://www.ceri.uniroma1.it/index.php/web-gis/cedit/). Aiming at support the detection and mapping of earthqhake-induced landslides, Satellite DInSAR technique (Differential Synthetic Aperture Radar Interferometry) combined with satellite and aerial high resolution optical imagery was used. Specifically, Sentinel-1, COSMO-SkyMed and ALOS-2 (both ascending and descending) co-seismic differential interferograms were used in combination with optical datasets available through the Copernicus Emergency Management Service. Interferograms have been analysed firstly with un-supervised analyses, based on the detection of the fringes anomalies, i.e. particular patterns of the interferometric phase such as: i) irregular shaped fringes, ii) abrupt interruptions of the of regional co-seismic fringes, iii) localized changes in the fringes gradient. Then, fringes anomalies have been analysed in order to detect landslide-candidates according to the following criteria: i) fringes anomalies must be located in slope areas; ii) the mean coherence values of the fringes anomalies must behigher than a predefined threshold; iii) fringes anomalies are present in more than one interferogram. Finally, the landslide-candidates have been validated by a combined expert analysis with satellite and aerial optical images and field evidences included in the catalogue of Earthquake-induced ground failures in Italy (CEDIT). By combining Optical and SAR images, more than 60 landslides were detected, 8 of which recognized only thanks to fringes anomalies. As a matter of fact, slopes affected by small plastic deformations (from mm to cm order) cannot be recognized by the interpretation of optical images that, on the other hand, are the only ones able to detect small scale slope failures such as rockfalls. Further steps in this study will be the intergration of remotely sensed landslides in the catalogue of Earthquake-induced ground failures in Italy (CEDIT) and the analyses of the data available from the earthquakes occurred in Central Italy in October 2016