7 research outputs found
Remote monitoring of the Comba Citrin landslide using discontinuous GBInSAR campaigns
No full textThis paper describes the use of the discontinuous Ground-Based Interferometric Synthetic Aperture Radar technique (GBInSAR) to monitor the displacement of the Comba Citrin landslide in the North Western Italian Alps. Two GBInSAR surveys were carried out respectively during the summer and the fall of 2015 separated by a temporal baseline of 63 days. For each GBInSAR survey, which lasted respectively 166.2 h (6 dd, 22 h, 12′) and 238.3 h (9 dd, 22 h, 18′), two sets of 139 and 275 SAR images were acquired. After the selection of a specific stack of Persistent Scatterers, the SAR images of each survey were analyzed separately and in combination with the images of the other survey to detect the possible displacements occurred both in every single survey as well as in the elapsed time between the two different campaigns. The displacement maps showed that two different sectors of the monitored slope were affected by millimetres to centimetres movements during the monitoring period. The results obtained for the Comba Citrin landslide show that the discontinuous GBInSAR can be reliably adopted to monitor the displacement of landslides moving at an average rate of few centimetres per year
Satellite interferometric data for landslide intensity evaluation in mountainous regions
No full textMulti-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
Remote monitoring of the Comba Citrin landslide using discontinuous GBInSAR campaigns
No full textThis paper describes the use of the discontinuous Ground-Based Interferometric Synthetic Aperture Radar technique (GBInSAR) to monitor the displacement of the Comba Citrin landslide in the North Western Italian Alps. Two GBInSAR surveys were carried out respectively during the summer and the fall of 2015 separated by a temporal baseline of 63 days. For each GBInSAR survey, which lasted respectively 166.2 h (6 dd, 22 h, 12′) and 238.3 h (9 dd, 22 h, 18′), two sets of 139 and 275 SAR images were acquired. After the selection of a specific stack of Persistent Scatterers, the SAR images of each survey were analyzed separately and in combination with the images of the other survey to detect the possible displacements occurred both in every single survey as well as in the elapsed time between the two different campaigns. The displacement maps showed that two different sectors of the monitored slope were affected by millimetres to centimetres movements during the monitoring period. The results obtained for the Comba Citrin landslide show that the discontinuous GBInSAR can be reliably adopted to monitor the displacement of landslides moving at an average rate of few centimetres per year
Integration of satellite interferometric data in civil protection strategies for landslide studies at a regional scale
No full textMulti-Temporal Satellite Interferometry (MTInSAR) is gradually evolving from being a tool developed by the scientific community exclusively for research purposes to a real operational technique that can meet the needs of different users involved in geohazard mitigation. This work aims at showing the innovative operational use of satellite radar interferometric products in Civil Protection Authority (CPA) practices for monitoring slow-moving landslides. We present the example of the successful ongoing monitoring system in the Valle D’Aosta Region (VAR-Northern Italy). This system exploits well-combined MTInSAR products and ground-based instruments for landslide management and mitigation strategies over the whole regional territory. Due to the critical intrinsic constraints of MTInSAR data, a robust regional satellite monitoring integrated into CPA practices requires the support of both in situ measurements and remotely sensed systems to guarantee the completeness and reliability of information. The monitoring network comprises three levels of analysis: Knowledge monitoring, Control monitoring, and Emergency monitoring. At the first monitoring level, MTInSAR data are used for the preliminary evaluation of the deformation scenario at a regional scale. At the second monitoring level, MTInSAR products support the prompt detection of trend variations of radar benchmarks displacements with bi-weekly temporal frequency to identify active critical situations where follow-up studies must be carried out. In the third monitoring level, MTInSAR data integrated with ground-based data are exploited to confirm active slow-moving deformations detected by on-site instruments. At this level, MTInSAR data are also used to carry out back analysis that cannot be performed by any other tool. From the example of the Valle D’Aosta Region integrated monitoring network, which is one of the few examples of this kind around Europe, it is evident that MTInSAR provides a great opportunity to improve monitoring capabilities within CPA activities
Assessing the rock failure return period on an unstable Alpine rock wall based on volume-frequency relationships: The Brenva Spur (3916 m a.s.l., Aosta Valley, Italy)
No full textInternational audienceDefining the relationship between volume and return period is critical when estimating the risk of rockfalls and/ or rock avalanche, especially during continued global warming at high altitudes that threatens rock wall stability. Characterizing the volume-frequency relationship based on historical datasets is, however, limited by observation and quantification biases, which have not received enough attention. Here, to monitor recent activities for the Brenva Spur (Mont-Blanc massif, Italy) that is also a rock avalanche scar and estimate the return period of future rock failures based on the volume-frequency relationship (and the corresponding uncertainty), a structure-from-motion photogrammetric survey was conducted from 2017 to 2021. 39 rockfall sources with volumes ranging from 11 to 13,250 m 3 were identified within the scar. The total failure volume is 22,438 m 3 , with an associated erosion rate of 15.5 mm/year, indicating very active morphodynamics possibly linked to the permafrost evolution in the spur. The volumes were characterized by a negative power-law that fits significant two events in 2016 (3.4 × 10 4 m 3) and one in 1997 (2.0 × 10 6 m 3) remarkably well, and the randomness of the fit was evaluated by a Monte Carlo approach. 7 potential failure scenarios ranging from 3.1 × 10 4 m 3 (S 1) to 4.8 × 10 6 m 3 (S 7) were defined according to a structural analysis and the sloping local base level concept. Their extrapolated return periods derived by the power-law fit indicate a longer return period for the maximum failure scenario than for the smaller scenarios. S 1 has a 50% chance of occurring every 3 years, while S 7 has a 50% chance of occurring every 31 years. Though the median return period of S 7 is 31 years, the 95% and 68.2% confidence intervals range from 8 to 399 years and 14 to 93 years, respectively, which reflects a high level of uncertainty but is realistic when considering global warming, progressive rock failure, etc. In addition to characterizing recent rock failure activities in high mountains, this study offers a preliminary examination of the return periods of some extreme scenarios and provides primary data for risk management in mountainous areas that are very sensitive to global warming
Hydrogeological forecasting of deep-seated landslides dynamics: structure and sensitivity of tank models
No full textInternational audienc
A Sentinel-1 based hot-spot analysis: landslide mapping in north-western Italy
No full textThe 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.</p
