Hot Spots for Simplified Risk Scenarios of the Trafoi Rockslide (South Tyrol)

Corsini, Alessandro; Iannacone, Jean Pascal; Ronchetti, Francesco; Salvini, Riccardo; Mair, Volkmar; Nössing, Ludwig; Stefani, Martina; Unterthiner, Günther; Valentinotti, Giorgio

doi:10.1007/978-3-642-31319-6_94

Cited by 1 publication

(2 citation statements)

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“…The landslide can be subdivided into two main units. Unit A (1.2 km 2 ) comprises the main deep-seated rockslide that is located in the central part of the slope (where the rock mass is highly fractured, generating also abundant material for debris flows) and the uppermost DSGSD, which causes double crested ridges and trenches [29,30]. Unit B (1.3 km 2 ) comprises a more evolved rockslide deposit which locally evolves into earth slides.…”

Section: Test Sitesmentioning

confidence: 99%

“…At the same time, inclinometers have shown that Unit B moves locally at a few cm/year. In this portion there is no potential for a catastrophic evolution, but nonetheless such movements have repeatedly damaged a hotel and the national road SS 38 [29,30]. Land cover is bare ground on scree slopes and most of the Unit A rockslide, determining a quite favorable condition for airborne DIC.…”

Section: Test Sitesmentioning

confidence: 99%

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Detecting Recent Dynamics in Large-Scale Landslides via the Digital Image Correlation of Airborne Optic and LiDAR Datasets: Test Sites in South Tyrol (Italy)

Tondo,

Mulas,

Ciccarese

et al. 2023

Remote Sensing

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Large-scale slow-moving deep-seated landslides are complex and potentially highly damaging phenomena. The detection of their dynamics in terms of displacement rate distribution is therefore a key point to achieve a better understanding of their behavior and support risk management. Due to their large dimensions, ranging from 1.5 to almost 4 km2, in situ monitoring is generally integrated using satellite and airborne remote sensing techniques. In the framework of the EFRE-FESR SoLoMon project, three test-sites located in the Autonomous Province of Bolzano (Italy) were selected for testing the possibility of retrieving significant slope displacement data from the analysis of multi-temporal airborne optic and light detection and ranging (LiDAR) surveys with digital image correlation (DIC) algorithms such as normalized cross-correlation (NCC) and phase correlation (PC). The test-sites were selected for a number of reasons: they are relevant in terms of hazard and risk; they are representative of different type of slope movements (earth-slides, deep seated gravitational slope Deformation and rockslides), and different rates of displacement (from few cm/years to some m/years); and they have been mapped and monitored with ground-based systems for many years (DIC results can be validated both qualitatively and quantitatively). Specifically, NCC and PC algorithms were applied to high-resolution (5 to 25 cm/px) airborne optic and LiDAR-derived datasets (such as hillshade and slope maps computed from digital terrain models) acquired during the 2019–2021 period. Qualitative and quantitative validation was performed based on periodic GNSS surveys as well as on manual homologous point tracking. The displacement maps highlight that both DIC algorithms succeed in identifying and quantifying slope movements of multi-pixel magnitude in non-densely vegetated areas, while they struggle to quantify displacement patterns in areas characterized by movements of sub-pixel magnitude, especially if densely vegetated. Nonetheless, in all three landslides, they proved to be able to differentiate stable and active parts at the slope scale, thus representing a useful integration of punctual ground-based monitoring systems.

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Section: Test Sitesmentioning

confidence: 99%

Section: Test Sitesmentioning

confidence: 99%