Current geodetic deformation of the Colli Albani volcano: a review

The quiescent Colli Albano volcano is presently characterised by moderate intensity earthquakes, seismic swarms, gas emissions and ongoing uplift that reflects the current evidences of its residual activity. An uplift of ~30 cm over the last 43 years was recently detected by levelling surveys performed in the time span 1950-1993 along a levelling line that crosses the highest elevation area of the western flank of the volcano. Space based GPS and Synthetic Aperture Radar Interferometry geodetic observations confirm that this uplift is distributed in a wide area around the craters of Albano and Nemi, where the most recent volcanic activity occurred. GPS data from continuous monitoring stations indicate that both horizontal and vertical deformations do occur and that can be addressed to a shallow magmatic source. All the geodetic observations are in agreement and highlight that the Colli Albani is still a potentially active volcano. Being located in a densely populated area close to Rome, the volcano should deserve the same monitoring and hazard assessment effort of any active volcano within urbanized areas. Here we review the geodetic results obtained during the last decades for the Colli Albani volcano

Corrigendum to "Co-seismic surface effects from very high resolution panchromatic images: the case of the 2005 Kashmir (Pakistan) earthquake" published in Nat. Hazards Earth Syst. Sci., 11, 931–943, 2011

No abstract available

Movements detection of deep seated gravitational slope deformations by means of InSAR data and photogeological interpretation: northern Sicily case study

We investigated the northern-central portion of Sicily region (southern Italy) using aerial photographs and Synthetic Aperture Radar (SAR) data obtained by ERS1 and ERS2 satellites. This area shows a geological-structural setting generated by the tectonic superposition of Apenninic-Maghrebian carbonatic structures on terrigenous deposits. Such a structural setting favoured the development of large-scale gravity driven phenomena (known in the geological literature as deep-seated gravitational slope deformations) that are mostly responsible for the landscape evolution of the whole area. Morphological evidences such as landslides, sacking or rock-flow, lateral spread and block slide can be detected from photogeological analysis. In order to understand the temporal behaviour and spatial distribution of such deformations we applied the interferometric SAR (InSAR) technique. Interferograms show fringe patterns spatially coinciding with some of the large-scale gravitative phenomena previously identified by means of aerialphoto analysis. The comparison between photogeological data and InSAR results allows delimiting the active sectors in the study area

Seismic Source Quantitative Parameters Retrieval from InSAR Data and Neural Networks

The basic idea of this thesis is to exploit the capabilities of neural networks in a very new framework: the quantitative modelling of the seismic source and the interferogram inversion for retrieving its geometric parameters. The problem can be sum up as follows. When a moderateto- strong earthquake occurs we can apply SAR Interferometry (InSAR) technique to compute a differential interferogram. The latter is used to detect and measure the surface displacement field. The earthquake has been generated by an active, seismogenic, fault having its own specific geometry. Therefore each differential interferogram contains the information concerning the geometry of the seismic source the earthquake comes from; its shape and size, the number of fringes, the lobe orientation and number are the main features of the surface effects field. Two problems have been analysed in this work. The first is the identification of the seismic source mechanism. The second is a typical inversion exercise concerning the fault plane parameter. To perform both exercises of the seismic fault a huge number of synthetic interferograms has been computed. Each of them is generated by a different combination of such geometric parameters. As far as the retrieval of the geometric parameters is concerned an artificial neural network has been properly generated and trained to provide an inversion procedure to single out the geometric parameters of the fault. Five among these latter, Length, Width, Dip, Strike, Depth, have been simultaneously inverted. The result is in agreement with those results based on different approaches. Furthermore the method seems very promising and leads to improve the studies concerning the combined use of neural networks and InSAR technique

The case of the 2005 Kashmir earthquake

The use of Very High Resolution (VHR) satellite panchromatic image is nowadays an effective tool to detect and investigate surface effects of natural disasters. We specifically examined the capabilities of VHR images to analyse earthquake features and detect changes based on the combination of visual inspection and automatic classification tools. In particular, we have used Quickbird (0.6m spatial resolution) images for detecting the three main coseismic surface features: damages, ruptures and landslides. The present approach has been applied to the 8 October 2005, Mw7.6 Kashmir, Pakistan, earthquake. We have focused our study in and around the main urban areas hit by the above earthquake specifically at Muzaffarabad and Balakot towns. The automatic classification techniques provided the best results wherever dealing with the damage to man-made structures and landslides. On the other hand, the visual inspection method demonstrated in addressing the identification of rupture traces and associated features. The synoptic view (concerning landslide, more than 190 millions of pixels have been automatically classified), the spatiotemporal sampling and the fast automatic damage detection using satellite images provided a reliable contribution to the prompt response during natural disaster and for the evaluation of seismic hazard as well

The August 17, 1999 Izmit, Turkey, earthquake: slip distribution from dislocation modeling of DInSAR and surface offset

We show the results of application of Differential SAR Interferometry to the MW 7.4, August 17, 1999, Izmit earthquake, Western Turkey. The differential interferogram is obtained using an interferometric ERS2 ascending pair with a time interval of 35 days (August 13th - September 17th). The fringe pattern clearly defines the coseismic displacement field extended in an area of about 100 km N-S and 120 km E-W. The analysis of the interferogram shows the right-lateral strike-slip movement on the activated section of the North Anatolian fault system. The maximum SAR-detected displacement ranges between 117.6 cm and 134.4 cm in the proximity of Gölcük. We invert SAR data for uniform dislocation on a single fault plane using a Montecarlo procedure, with the aim of testing a large set of a priori possible asperity distributions on the fault. We then use a forward modeling approach to evaluate the slip variability for the dislocation using additional constraints as surface offsets and seismicity distribution: in this case we allow unit cells to undergo different values of slip in order to refine the initial dislocation model. Misfits between SAR data and modeled slant range displacements are generally low for all our models (~ 12 cm). Our results indicate that slip is concentrated in the central-western part of the fault, in the upper 10-15 km, tapering to the fault tips. For the Izmit case, we note that a well constrained fault model can be obtained only integrating DInSAR data with additional observations. This is mainly due to an undersampling of the displacement field by DInSAR, caused by decorrelation and lack of image data

The relationship between seismic deformation and deep seated gravitational

This paper re-evaluates the origin of some peculiar patterns of ground deformation observed by space geodetic techniques during the two earthquakes of September 26th of the Colfiorito seismic sequence. The surface displacement field due to the fault dislocation, as modeled with the classic Okada elastic formulations, shows some areas with high residuals which cannot be attributed to unsimulated model complexities. The latter was investigated using geomorphological analysis, by recognising the geologic evidence of deep seated gravitational slope deformations (DSGSD) of the block-slide type. The shape and direction of the co-seismic ground displacement observed in these areas are correlated with the expected pattern of movement produced by the reactivation of the identified DSGSD. At least a few centimetres of negative Line of Sight ground displacement was determined for the Costa Picchio, Mt. Pennino, and Mt. Prefoglio areas. A considerable horizontal component of movement in the Costa Picchio DSGSD is evident from a qualitative analysis of ascending and descending interferograms. The timing of the geodetic data indicates that the ground movement occurred during the seismic shaking, and that it did not progress appreciably during the following months. In this work it has been verified the seismic triggering of DSGSD previously hypothesized by many authors. A further implication is that in the assessment of DSGSD hazard it is necessary to consider the seismic input as an important cause of acceleration of the deformation rates

The Sentinel-1 mission for the improvement of the scientific understanding and the operational monitoring of the seismic cycle

We describe the state of the art of scientific research on the earthquake cycle based on the analysis of Synthetic Aperture Radar (SAR) data acquired from satellite platforms. We examine the achievements and the main limitations of present SAR systems for the measurement and analysis of crustal deformation, and envision the foreseeable advances that the Sentinel-1 data will generate in the fields of geophysics and tectonics. We also review the technological and scientific issues which have limited so far the operational use of satellite data in seismic hazard assessment and crisis management, and show the improvements expected from Sentinel-1 dat

Volcanic ash detection and retrievals using MODIS data by means of neural networks

Volcanic ash clouds detection and retrieval represent a key issue for aviation safety due to the harming effects on aircraft. A lesson learned from the recent Eyjafjallajokull eruption is the need to obtain accurate and reliable retrievals on a real time basis. <br><br> In this work we have developed a fast and accurate Neural Network (NN) approach to detect and retrieve volcanic ash cloud properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) data in the Thermal InfraRed (TIR) spectral range. Some measurements collected during the 2001, 2002 and 2006 Mt. Etna volcano eruptions have been considered as test cases. <br><br> The ash detection and retrievals obtained from the Brightness Temperature Difference (BTD) algorithm are used as training for the NN procedure that consists in two separate steps: ash detection and ash mass retrieval. The ash detection is reduced to a classification problem by identifying two classes: "ashy" and "non-ashy" pixels in the MODIS images. Then the ash mass is estimated by means of the NN, replicating the BTD-based model performances. A segmentation procedure has also been tested to remove the false ash pixels detection induced by the presence of high meteorological clouds. The segmentation procedure shows a clear advantage in terms of classification accuracy: the main drawback is the loss of information on ash clouds distal part. <br><br> The results obtained are very encouraging; indeed the ash detection accuracy is greater than 90%, while a mean RMSE equal to 0.365 t km<sup>−2</sup> has been obtained for the ash mass retrieval. Moreover, the NN quickness in results delivering makes the procedure extremely attractive in all the cases when the rapid response time of the system is a mandatory requirement

Subsidence Detected by Multi-Pass Differential SAR Interferometry in the Cassino Plain (Central Italy): Joint Effect of Geological and Anthropogenic Factors?

In the present work, the Differential SAR Interferometry (DInSAR) technique has been applied to study the surface movements affecting the sedimentary basin of Cassino municipality. Two datasets of SAR images, provided by ERS 1-2 and Envisat missions, have been acquired from 1992 to 2010. Such datasets have been processed independently each other and with different techniques nevertheless providing compatible results. DInSAR data show a subsidence rate mostly located in the northeast side of the city, with a subsidence rate decreasing from about 5–6 mm/yr in the period 1992–2000 to about 1–2 mm/yr between 2004 and 2010, highlighting a progressive reduction of the phenomenon. Based on interferometric results and geological/geotechnical observations, the explanation of the detected movements allows to confirm the anthropogenic (surface effect due to building construction) and geological causes (thickness and characteristics of the compressible stratum