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Rockfalls are frequent and harmful phenomena occurring in mountain ranges, coastal cliffs, and slope cuts. Although several natural processes occur in their formation and triggering, rainfall is one of the most common causes. The prediction of rock failures is of social significance for civil protection purposes and can rely on the statistical analysis of past rainfall conditions that caused the failures. The paper describes the analysis of information on rainfall-induced rock-falls in Gran Canaria and Tenerife, Canary Islands (Spain). An analysis of the monthly rainfall versus the monthly distribution of rockfalls reveals that they are correlated for most of the year, except in summer, when other triggers act to induce collapses. National and regional catalogs with hourly and daily rainfall measurements are used to reconstruct the cumulated amount (E) and the duration (D) of the rainfall responsible for the rock failures. Adopting a consolidated statistical approach, new ED rainfall thresholds for possible rockfall occurrence and the associated uncertainties are calculated for the two test sites. As far as is known, this is the first attempt to predict this type of failure using the threshold approach. Using the rainfall information, a map of the mean annual rainfall is obtained for Gran Canaria and Tenerife, and it is used to assess the differences between the thresholds. The results of this study are expected to improve the ability to forecast rockfalls in the Canary Islands in view of implementing an early-warning system to mitigate the rockfall hazard and reduce the associated risk.
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https://www.tandfonline.com/doi/suppl/10.1080/17445647.2020.1806125?scroll=top
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The InSAR technique has been proved to be a powerful tool in order to detect, monitoring and analyse movements related to geological phenomena. Its application ranges from regional/national scale to a very detailed scale, up to a single building analysis. Moreover, since 2014, the free and constant availability of Sentinel-1 data has been helping the tendency of using more and more this technique in the institutional risk management activities. Many European and national projects have been financed in order to investigate and improve the processing performances and broaden the operational use and application of the results. In this work, we present the first results developed in the framework of the project Riskcoast (SOE3/P4/E0868) over an area of around 4 km 2 in AndalucĂa (Spain), including the city and the coast of Granada. Riskcoast has been funded by the Interreg Sudoe Programme through the European Regional Development Fund (ERDF). The presented work is as an example of multi scale (medium to large) application of InSAR for geohazard applications. The velocity map including the estimation of the displacement time series have been produced over the whole area by processing 139 radar images of the Sentinel-1 (A and B). Starting from those results a rapid and semi-automatic extraction of the most significant active displacement areas (ADA) has been performed. Then, after a classification of the detected areas, a more detailed analysis has been done over some selected costal landslides. Over those landslides a damage mapping has been generated based on field surveys, and then analysed together with the spatial gradient of displacement derived by the InSAR results. The Riskcoast project will be introduced and the first results presented. Powered by TCPDF (www.tcpdf.org)
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Rockfalls are the most frequent and dangerous instability phenomena in mountainous areas, causing high economic and social damages. Rockfalls are triggered by complex instability mechanisms and the source areas are controlled by environmental factors like geology, the presence of discontinuities and slope angle. Modeling rockfall phenomena is complex and requires diversified input including parameters controlling the boulders trajectories and the source areas identification. In the Canary Islands, the steep topography and the geological complexity influence the activation of slope dynamics and the occurrence of slope failures. In particular, rockfalls are very common and they represent a major threat to society, costing lives, disrupting infrastructures and destroying livelihoods. In 2011 the volcanic crisis in El Hierro Island triggered numerous rockfalls that affected the road network causing a great social alarm. After the recent event, we have attempted to identify rockfall source areas using different approaches including probabilistic modeling. The probabilistic approach applies a combination of multiple statistical models and requires a map of the observed source areas as dependent variable and a set of thematic information as independent variables (e.g., morphometric parameters derived from DTM, lithological information that considers the mechanical behavior of the rocks). For the purpose, we have identified various scenarios selecting different training and validation zones and evaluating for each scenario the associated errors. The maps resulting from the models, provide for the whole El Hierro Island, the probability of a pixel being a source area and can be used as input for the rockfall modeling. Powered by TCPDF (www.tcpdf.org)
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Abstract. Rockfalls are frequent and harmful phenomena occurring in mountain ranges, coastal cliffs and slope cuts. Albeit several natural processes concur in their formation and triggering, rainfall is one of the most common causes. The prediction of rock failures is of social significance for civil protection purposes and can rely on the statistical analysis of past rainfall conditions that caused the failures. The paper describes the analysis of information on rainfall-induced rockfalls in Gran Canaria and Tenerife, Canary Islands (Spain). An analysis of the monthly rainfall versus the monthly distribution of rockfalls reveals that they are correlated for most of the year, except in summer, when other triggers act to induce collapses. National and regional catalogues with hourly and daily rainfall measurements are used to reconstruct the cumulated amount ( E ) and the duration ( D ) of the rainfall responsible for the rock failures. Adopting a consolidated statistical approach, new ED rainfall thresholds for possible rockfall occurrence and the associated uncertainties are calculated for the two test sites. As far as is known, this is the first attempt to predict this type of failure using the threshold approach. Using the rainfall information, a map of the mean annual rainfall is obtained for Gran Canaria and Tenerife, and it is used to assess the differences between the thresholds. The results of is study are expected to improve the ability to forecast rockfalls in the Canary Islands, in view of implementing an early warning system to mitigate the rockfall hazard and reduce the associated risk.
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Multi-Temporal Interferometric Synthetic Aperture Radar (MTInSAR) data offer a valuable support to landslide mapping and to landslide activity estimation in mountain environments, where in situ measures are sometimes difficult to gather. Nowadays, the interferometric approach is more and more used for wide-areas analysis, providing useful information for risk management actors but at the same time requiring a lot of efforts to correctly interpret what satellite data are telling us. In this context, hot-spot-like analyses that select and highlight the fastest moving areas in a region of interest, are a good operative solution for reducing the time needed to inspect a whole interferometric dataset composed by thousands or millions of points. In this work, we go beyond the concept of MTInSAR data as simple mapping tools by proposing an approach whose final goal is the quantification of the potential loss experienced by an element at risk hit by a potential landslide. To do so, it is mandatory to evaluate landslide intensity. Here, we estimate intensity using Active Deformation Areas (ADA) extracted from Sentinel-1 MTInSAR data. Depending on the localization of each ADA with respect to the urban areas, intensity is derived in two different ways. Once exposure and vulnerability of the elements at risk are estimated, the potential loss due to a landslide of a given intensity is calculated. We tested our methodology in the Eastern Valle d'Aosta (north-western Italy), along four lateral valleys of the Dora Baltea Valley. This territory is characterized by steep slopes and by numerous active and dormant landslides. The goal of this work is to develop a regional scale methodology based on satellite radar interferometry to assess the potential impact of landslides on the urban fabric.
