Lava delta deformation as a proxy for submarine slope instability

Traglia, Federico Di; Nolesini, Teresa; Solari, Lorenzo; Ciampalini, Andrea; Frodella, William; Steri, Damiano; Allotta, Benedetto; Rindi, Andrea; Marini, L.; Monni, Niccolò; Galardi, Emanuele; Casagli, Nicola

doi:10.1016/j.epsl.2018.01.038

Cited by 51 publications

(44 citation statements)

References 44 publications

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“…During the 2014 eruption the seismic broadband network of Stromboli [29] was operating with 10 broadband seismic stations. In this work, we used data from 3 seismic stations ( Figure 1b).…”

Section: Seismic Network (Istituto Nazionale DI Geofisica E Vulcanolomentioning

confidence: 99%

The 2014 Effusive Eruption at Stromboli: New Insights from In Situ and Remote-Sensing Measurements

et al. 2018

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In situ and remote-sensing measurements have been used to characterize the run-up phase and the phenomena that occurred during the August–November 2014 flank eruption at Stromboli. Data comprise videos recorded by the visible and infrared camera network, ground displacement recorded by the permanent-sited Ku-band, Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR) device, seismic signals (band 0.02–10 Hz), and high-resolution Digital Elevation Models (DEMs) reconstructed based on Light Detection and Ranging (LiDAR) data and tri-stereo PLEIADES-1 imagery. This work highlights the importance of considering data from in situ sensors and remote-sensing platforms in monitoring active volcanoes. Comparison of data from live-cams, tremor amplitude, localization of Very-Long-Period (VLP) source and amplitude of explosion quakes, and ground displacements recorded by GBInSAR in the crater terrace provide information about the eruptive activity, nowcasting the shift in eruptive style of explosive to effusive. At the same time, the landslide activity during the run-up and onset phases could be forecasted and tracked using the integration of data from the GBInSAR and the seismic landslide index. Finally, the use of airborne and space-borne DEMs permitted the detection of topographic changes induced by the eruptive activity, allowing for the estimation of a total volume of 3.07 ± 0.37 × 106 m3 of the 2014 lava flow field emplaced on the steep Sciara del Fuoco slope.

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“…During the 2014 eruption the seismic broadband network of Stromboli [29] was operating with 10 broadband seismic stations. In this work, we used data from 3 seismic stations ( Figure 1b).…”

Section: Seismic Network (Istituto Nazionale DI Geofisica E Vulcanolomentioning

confidence: 99%

The 2014 Effusive Eruption at Stromboli: New Insights from In Situ and Remote-Sensing Measurements

et al. 2018

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“…The low vulnerability category contains formations like sandstones, tuffs, low grade metamorphics, and conglomerate, and the medium category clays, low-cohesion sedimentary rocks and soft tuffs. The classification is based on bibliographical research [Reid et al, 2001;Apuani, et al, 2005a,b;del Potro et al, 2008;Reid et al, 2010;Nolesini et al, 2013;, Di Traglia et al, 2018]. Non-cohesive materials, coarse and poorly sorted unconsolidated sediments and loose pyroclastics are ranked in the high vulnerability category.…”

Section: Ranking Variablesmentioning

confidence: 99%

“…Land cover, as a landslide factor, is also the most influenced by human activities, since it is easy to manage and change [Akgun and Türk, 2010;Di Traglia et al, 2017]. Land cover type can also function as a measure for surface roughness when not relative measurements exist, although roughness can be more detailed [Korzeniowska et al, 2018;Di Traglia et al, 2018]. In future works this indicator be supplemented by roughness measurement with the use of topographic (DEMs) and SAR data if available [Catani et al, 2013].…”

Section: Ranking Variablesmentioning

confidence: 99%

Preliminary Risk Assessment at Ustica Based on Indicators of Natural and Human Processes

Alexandrakis

Vita²,

Vito³

2019

Annals of Geophysics

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Geomorphological phenomena have significant repercussions on environmental evolution, triggering changes in natural processes that might have a severe socioeconomic impact. To date, vulnerability estimations have been primarily based on natural processes, and secondarily by combining the exposure resulting from socioeconomic variables, which can assist in identifying areas under risk. The present investigation proposes a methodology to examine the risk from natural hazards by introducing social indicators as exposure factors. The methodology is based on a combination of socioeconomic and natural indicators. In this work the different indicators form indices that are used to make holistic risk estimation for both inland areas and coastal areas. This approach includes four sub-indices that contribute to the overall risk estimation. The sub-indices refer to the geomorphological characteristics, together with natural forcing, coastal erosion for the estimation of the vulnerability and socioeconomic indicators for the estimation of exposure. All variables are ranked on a 1-5 scale, with rank 5 indicating the highest, and are estimated in a GIS model. The main difficulty in making these estimations lies in assessing and ranking the socioeconomic indicators, and especially cultural heritage sites since their importance cannot be measured. The risk is estimated by using the vulnerability of the area and the socioeconomic sub-index that function as the exposure variable in the estimations. This work is an initial approach as part of the Brains2Islands project funded by Fondazione con il Sud and aims to develop a best practice guide for cultural heritage resilience to natural hazards, that will be tested and validated through field studies, using as a case study the island of Ustica, an area of high cultural and economic value, with ancient monuments.

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“…Space-based technology is an efficient way to reconstruct 3D topography and monitor both natural and man-made disasters, such as earthquakes [1][2][3], volcanoes [4][5][6][7], landslides [8][9][10][11], and anthropogenic subsidence or uplift due to fluid withdrawal or injection [12][13][14][15]. One representative example is the spaceborne Synthetic Aperture Radar (SAR), which has a high spatial-temporal resolution and a broad spatial coverage, capable of precise topography measurement and deformation monitoring using advanced multi-temporal interferometric SAR (InSAR) techniques [16], such as persistent scatterer InSAR (PS-InSAR) [17][18][19][20], SBAS [21,22], SqueeSAR [23], CAESAR [24,25], PD-PSInSAR [26], and TomoSAR [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

An Improved Stanford Method for Persistent Scatterers Applied to 3D Building Reconstruction and Monitoring

Yang

Liu

et al. 2019

Remote Sensing

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Persistent scatterers interferometric Synthetic Aperture Radar (PS-InSAR) is capable of precise topography measurement up to sub-meter scale and monitoring subtle deformation up to mm/year scale for all the radar image pixels with stable radiometric characteristics. As a representative PS-InSAR method, the Stanford Method for Persistent Scatterers (StaMPS) is widely used due to its high density of PS points for both rural and urban areas. However, when it comes to layover regions, which usually happens in urban areas, the StaMPS is limited locally. Moreover, the measurement points are greatly reduced due to the removal of adjacent PS pixels. In this paper, an improved StaMPS method, called IStaMPS, is proposed. The PS pixels are selected with high density by the improved PS selection strategy. Moreover, the topography information not provided in StaMPS can be accurately measured in IStaMPS. Based on the data acquired by TerraSAR-X/TanDEM-X over the Terminal 3 E (T3 E) site of Beijing capital international airport and the Chaobai River of Beijing Shunyi District, a comparison between StaMPS-retrieved results and IStaMPS-retrieved ones is performed, which demonstrates that the density of PS points detected by IStaMPS is increased by about 1.8 and 1.6 times for these two areas respectively. Through comparisons of local statistical results of topography estimation and mean deformation rate, the improvement granted by the proposed IStaMPS is demonstrated for both urban areas with complex buildings or man-made targets and non-urban areas with natural targets. In terms of the spatio-temporal deformation variation, the northwest region of T3 E experienced an exceptional uplift during the period from Jun. 2012 to Aug. 2015, and the maximum uplift rate is approximately 4.2 mm per year.

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Lava delta deformation as a proxy for submarine slope instability

Cited by 51 publications

References 44 publications

The 2014 Effusive Eruption at Stromboli: New Insights from In Situ and Remote-Sensing Measurements

The 2014 Effusive Eruption at Stromboli: New Insights from In Situ and Remote-Sensing Measurements

Preliminary Risk Assessment at Ustica Based on Indicators of Natural and Human Processes

An Improved Stanford Method for Persistent Scatterers Applied to 3D Building Reconstruction and Monitoring

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