Investigating slope instabilities through SAR interferometry: examples on hilly villages in Southern Italy (Conference Presentation)

2019 ◽  
Author(s):  
Fabio Bovenga ◽  
Alberto Refice ◽  
Guido Pasquariello ◽  
Giuseppe Spilotro ◽  
Raffaele Nutricato ◽  
...  
Keyword(s):  
Southern Italy ◽  
Sar Interferometry ◽  
Slope Instabilities

scholarly journals Application of field surveys and multitemporal in-SAR interferometry analysis in the recognition of deep-seated gravitational slope deformation of an urban area of Southern Italy

2019 ◽  
Vol 10 (1) ◽  
pp. 1327-1345 ◽  
Author(s):  
Mario Bentivenga ◽  
Salvatore I. Giano ◽  
Beniamino Murgante ◽  
Gabriele Nolè ◽  
Giuseppe Palladino ◽  
...  
Keyword(s):  
Urban Area ◽  
Southern Italy ◽  
Slope Deformation ◽  
Sar Interferometry ◽  
Field Surveys

scholarly journals Subsidence Trends of Volturno River Coastal Plain (Northern Campania, Southern Italy) Inferred by SAR Interferometry Data

Geosciences ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 8 ◽  
Author(s):  
Fabio Matano ◽  
Marco Sacchi ◽  
Marco Vigliotti ◽  
Daniela Ruberti
Keyword(s):  
Coastal Plain ◽  
Southern Italy ◽  
Sar Interferometry ◽  
Volturno River

scholarly journals POTENTIAL OF SENTINEL-1A FOR NATION-WIDE ROUTINE UPDATES OF ACTIVE LANDSLIDE MAPS

2016 ◽  
Vol XLI-B7 ◽  
pp. 775-781 ◽  
Author(s):  
M. Lazecky ◽  
F. Canaslan Comut ◽  
E. Nikolaeva ◽  
M. Bakon ◽  
J. Papco ◽  
...  
Keyword(s):  
Arid Regions ◽  
Emergency Services ◽  
Sar Interferometry ◽  
Economic Damage ◽  
Movement Activity ◽  
Mountainous Regions ◽  
Susceptibility Maps ◽  
Active Landslide ◽  
Slope Instabilities ◽  
Semi Arid

Slope deformation is one of the typical geohazards that causes an extensive economic damage in mountainous regions. As such, they are usually intensively monitored by means of modern expertise commonly by national geological or emergency services. Resulting landslide susceptibility maps, or landslide inventories, offer an overview of areas affected by previously activated landslides as well as slopes known to be unstable currently. Current slope instabilities easily transform into a landslide after various triggering factors, such as an intensive rainfall or a melting snow cover. In these inventories, the majority of the existing landslide-affected slopes are marked as either stable or active, after a continuous investigative work of the experts in geology. In this paper we demonstrate the applicability of Sentinel-1A satellite SAR interferometry (InSAR) to assist by identifying slope movement activity and use the information to update national landslide inventories. This can be done reliably in cases of semi-arid regions or low vegetated slopes. We perform several analyses based on multitemporal InSAR techniques of Sentinel-1A data over selected areas prone to landslides.

scholarly journals <sup>GA</sup><i>SAKe</i>: forecasting landslide activations by a genetic-algorithms based hydrological model

2015 ◽  
Vol 8 (2) ◽  
pp. 1225-1291
Author(s):  
O. G. Terranova ◽  
S. L. Gariano ◽  
P. Iaquinta ◽  
G. G. R. Iovine
Keyword(s):  
Genetic Algorithms ◽  
Early Warning ◽  
Hydrological Model ◽  
Southern Italy ◽  
Fitness Function ◽  
Slope Movement ◽  
Rainfall Series ◽  
Temporal Validation ◽  
Slope Instabilities ◽  
Sorrento Peninsula

Abstract. GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is based on genetic-algorithms and allows to obtaining thresholds of landslide activation from the set of historical occurrences and from the rainfall series. GASAKe can be applied to either single landslides or set of similar slope movements in a homogeneous environment. Calibration of the model is based on genetic-algorithms, and provides for families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting from these latter, the corresponding mobility functions (i.e. the predictive tools) can be obtained through convolution with the rain series. The base time of the kernel is related to the magnitude of the considered slope movement, as well as to hydro-geological complexity of the site. Generally, smaller values are expected for shallow slope instabilities with respect to large-scale phenomena. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing recorded or forecasted rainfall series. Example of application of GASAKe to a medium-scale slope movement (the Uncino landslide at San Fili, in Calabria, Southern Italy) and to a set of shallow landslides (in the Sorrento Peninsula, Campania, Southern Italy) are discussed. In both cases, a successful calibration of the model has been achieved, despite unavoidable uncertainties concerning the dates of landslide occurrence. In particular, for the Sorrento Peninsula case, a fitness of 0.81 has been obtained by calibrating the model against 10 dates of landslide activation; in the Uncino case, a fitness of 1 (i.e. neither missing nor false alarms) has been achieved against 5 activations. As for temporal validation, the experiments performed by considering the extra dates of landslide activation have also proved satisfactory. In view of early-warning applications for civil protection purposes, the capability of the model to simulate the occurrences of the Uncino landslide has been tested by means of a progressive, self-adaptive procedure. Finally, a sensitivity analysis has been performed by taking into account the main parameters of the model. The obtained results are quite promising, given the high performance of the model obtained against different types of slope instabilities, characterized by several historical activations. Nevertheless, further refinements are still needed for applications to landslide risk mitigation within early-warning and decision-support systems.

scholarly journals Design Strategies to Mitigate Slope Instabilities in Structurally Complex Formations

Geosciences ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 82 ◽  
Author(s):  
Paolo Ruggeri ◽  
Viviene M. E. Fruzzetti ◽  
Giuseppe Scarpelli
Keyword(s):  
Mechanical Characteristics ◽  
East Coast ◽  
Southern Italy ◽  
Soil Mass ◽  
Design Strategies ◽  
Failure Event ◽  
Zone Of Influence ◽  
Slope Instabilities ◽  
Complex Formations ◽  
Construction Works

Stiff jointed clays (SJC) belong to so-called structurally complex formations in which the macroscale features of the deposit, that is the pattern of discontinuities affecting the soil mass, influence its response at the scale of engineering works. Such peculiar response was largely recognized during the excavation works carried out for the construction of two new road segments in southern Italy, where several structurally conditioned instability processes were triggered during excavation works. These phenomena mainly involved the Plio-Pleistocene marine clayey formation outcropping along the East coast of the Calabria region, where it constitutes most of the hills interested by construction works. Under a geotechnical perspective, the SJC-formation exhibits good mechanical characteristics at the scale of samples but, if considered as a whole, its behaviour is governed by the presence of discontinuities along which strength is typically at residual. Building on the author’s experience of some exemplary failure events, this paper aims at defining possible design strategies to minimize the risk of adverse and unexpected instability phenomena during construction in structurally complex formations. Design strategies oriented at reducing and possibly avoiding stress releases in the zone of influence were found to be most effective at preventing failures or restoring safety after the occurrence of a failure event.

MTInSAR long-term monitoring of nonlinear slope instabilities on hilltop villages in Southern Italy

2020 ◽  
Author(s):  
Alberto Refice ◽  
Fabio Bovenga ◽  
Guido Pasquariello ◽  
Ilenia Argentiero ◽  
Giuseppe Spilotro ◽  
...  
Keyword(s):  
Time Series ◽  
Spatial Resolution ◽  
Early Warning ◽  
European Space Agency ◽  
Sar Interferometry ◽  
Temporal Sampling ◽  
Area Of Interest ◽  
Non Linear ◽  
Satellite Missions ◽  
Slope Instabilities

&lt;p&gt;Multi-temporal SAR interferometry (MTInSAR) provides mean displacement maps and displacement time series over coherent objects on the Earth surface, allowing analysis of wide areas to identify ground deformations, and studying evolution of displacement phenomena over long time scales. MTInSAR techniques have proven very useful for detecting and monitoring also slope instabilities.&lt;/p&gt;&lt;p&gt;Nowadays, several satellite missions are available providing InSAR data at different wavelengths, spatial resolutions, and revisit times. The Italian X-Band COSMO-SkyMed constellation acquires data with spatial resolution reaching metric values, and provides revisit times of up to a few days, leading to an increase in the density of the measurable targets, thus&amp;#160; improving the monitoring of local scale events as well as the detection of non-linear displacements.&amp;#160; The recent Sentinel-1 C-band mission from the European Space Agency (ESA) provides a spatial resolution comparable to previous ESA SAR missions, but a nominal revisit time reduced to 6 days. By offering regular global-scale coverage, better temporal resolution and freely available imagery, Sentinel-1 improves the performance of MTInSAR for ground displacement investigations. In particular, the short revisit time allows a better time series analysis by improving the temporal sampling and thus the chances to catch pre-failure signals characterised by high rate and non-linear behaviour. Moreover, it allows collecting large data stacks in a short time periods, thus improving MTInSAR performance in emergency (post-event) scenarios. These characteristics are very promising for early warning of slope failure events and monitoring subsequent displacements trends.&amp;#160;&lt;/p&gt;&lt;p&gt;In this work, we present the results obtained by using both COSMO-SkyMed and Sentinel-1 data for investigating the ground stability of hilly villages located in Southern Italian Apennine (Basilicata region). In the area of interest, several landslides occurred in the recent past (e.g. Montescaglioso in 2013) and more recently (e.g. Pomarico in 2019), causing extensive damage to houses, commercial buildings, and infrastructures.&lt;/p&gt;&lt;p&gt;SAR datasets acquired by COSMO-SkyMed and Sentinel-1 from both ascending and descending orbits have been processed by using the SPINUA MTInSAR algorithm, in order to exploit the potentials of these two satellite missions to investigate ground displacements related to slope instabilities.&amp;#160; Mean velocity maps and displacement time series have been analysed looking, in particular, for non-linear trends that are possibly related to relevant ground instability episodes and, thanks to the high spatial resolution, useful in terms of early warning, in the case of rigid soil masses. Results are presented and discussed in relation to known events occurred in the area of interest.&lt;/p&gt;

scholarly journals <sup>GA</sup><i>SAKe</i>: forecasting landslide activations by a genetic-algorithms-based hydrological model

2015 ◽  
Vol 8 (7) ◽  
pp. 1955-1978 ◽  
Author(s):  
O. G. Terranova ◽  
S. L. Gariano ◽  
P. Iaquinta ◽  
G. G. R. Iovine
Keyword(s):  
Genetic Algorithms ◽  
Early Warning ◽  
Hydrological Model ◽  
Southern Italy ◽  
Slope Movement ◽  
Rainfall Series ◽  
Medium Size ◽  
Slope Movements ◽  
Slope Instabilities ◽  
Sorrento Peninsula

Abstract. GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is based on genetic algorithms and allows one to obtain thresholds for the prediction of slope failures using dates of landslide activations and rainfall series. It can be applied to either single landslides or a set of similar slope movements in a homogeneous environment. Calibration of the model provides families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting from the kernels, the corresponding mobility functions (i.e., the predictive tools) can be obtained through convolution with the rain series. The base time of the kernel is related to the magnitude of the considered slope movement, as well as to the hydro-geological complexity of the site. Generally, shorter base times are expected for shallow slope instabilities compared to larger-scale phenomena. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing measured or forecasted rainfall series. Examples of application of GASAKe to a medium-size slope movement (the Uncino landslide at San Fili, in Calabria, southern Italy) and to a set of shallow landslides (in the Sorrento Peninsula, Campania, southern Italy) are discussed. In both cases, a successful calibration of the model has been achieved, despite unavoidable uncertainties concerning the dates of occurrence of the slope movements. In particular, for the Sorrento Peninsula case, a fitness of 0.81 has been obtained by calibrating the model against 10 dates of landslide activation; in the Uncino case, a fitness of 1 (i.e., neither missing nor false alarms) has been achieved using five activations. As for temporal validation, the experiments performed by considering further dates of activation have also proved satisfactory. In view of early-warning applications for civil protection, the capability of the model to simulate the occurrences of the Uncino landslide has been tested by means of a progressive, self-adaptive procedure. Finally, a sensitivity analysis has been performed by taking into account the main parameters of the model. The obtained results are quite promising, given the high performance of the model against different types of slope instabilities characterized by several historical activations. Nevertheless, further refinements are still needed for application to landslide risk mitigation within early-warning and decision-support systems.

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