Ivana Zinno

Magma injection beneath the urban area of Naples: a new mechanism for the 2012–2013 volcanic unrest at Campi Flegrei caldera

We found the first evidence, in the last 30 years, of a renewed magmatic activity at Campi Flegrei caldera from January 2012 to June 2013. The ground deformation, observed through satellite interferometry and GPS measurements, have been interpreted as the effect of the intrusion at shallow depth (3090 ± 138 m) of 0.0042 ± 0.0002 km3 of magma within a sill. This interrupts about 28 years of dominant hydrothermal activity and occurs in the context of an unrest phase which began in 2005 and within a more general ground uplift that goes on since 1950. This discovery has implications on the evaluation of the volcanic risk and in the volcanic surveillance of this densely populated area.

Ground deformation and source geometry of the 24 August 2016 Amatrice earthquake (Central Italy) investigated through analytical and numerical modeling of DInSAR measurements and structural-geological data

We investigate the ground deformation and source geometry of the 2016 Amatrice earthquake (Central Italy) by exploiting ALOS2 and Sentinel-1 coseismic differential interferometric synthetic aperture radar (DInSAR) measurements. They reveal two NNW-SSE striking surface deformation lobes, which could be the effect of two distinct faults or the rupture propagation of a single fault. We examine both cases through a single and a double dislocation planar source. Subsequently, we extend our analysis by applying a 3-D finite elements approach jointly exploiting DInSAR measurements and an independent, structurally constrained, 3-D fault model. This model is based on a double fault system including the two northern Gorzano and Redentore-Vettoretto faults (NGF and RVF) which merge into a single WSW dipping fault surface at the hypocentral depth (8 km). The retrieved best fit coseismic surface deformation pattern well supports the exploited structural model. The maximum displacements occur at 5–7 km depth, reaching 90 cm on the RVF footwall and 80 cm on the NGF hanging wall. The von Mises stress field confirms the retrieved seismogenic scenario.

SBAS-DInSAR Parallel Processing for Deformation Time-Series Computation

The aim of this paper is to design a novel parallel computing solution for the processing chain implementing the Small BAseline Subset (SBAS) Differential SAR Interferometry (DInSAR) technique. The proposed parallel solution (P-SBAS) is based on a dual-level parallelization approach and encompasses combined parallelization strategies, which are fully discussed in this paper. Moreover, the main methodological aspects of the proposed approach and their implications are also addressed. Finally, an experimental analysis, aimed at quantitatively evaluating the computational efficiency of the implemented parallel prototype, with respect to appropriate metrics, has been carried out on real data; this analysis confirms the effectiveness of the proposed parallel computing solution. In the current scenario, characterized by huge SAR archives relevant to the present and future SAR missions, the P-SBAS processing chain can play a key role to effectively exploit these big data volumes for the comprehension of the surface deformation dynamics of large areas of Earth.

SAR Imaging of Fractal Surfaces

A complete theoretical model for synthetic aperture radar (SAR) imaging of natural surfaces is introduced in this paper. The topography of the natural scenes is described via models derived from fractal geometry; scattering evaluations are performed via fractal scattering models appropriate to the employed fractal scene description. Scattering contributions are combined according to the SAR image impulse response function. The power spectral density of appropriate cuts of the SAR image are evaluated in closed form in terms of the surface fractal parameters. Our theoretical model is here conceptually assessed, analytically derived, graphically validated, numerically verified, and also tested on simulated SAR images. The introduced model allows defining innovative postprocessing inverse techniques to retrieve fractal parameters directly from SAR images.

Cloud Computing for Earth Surface Deformation Analysis via Spaceborne Radar Imaging: A Case Study

We present a case study on the migration to a Cloud Computing environment of the advanced differential synthetic aperture radar interferometry (DInSAR) technique, referred to as Small BAseline Subset (SBAS), which is widely used for the investigation of Earth surface deformation phenomena. In particular, we focus on the SBAS parallel algorithmic solution, namely P-SBAS, that allows the production of mean deformation velocity maps and the corresponding displacement time-series from a temporal sequence of radar images by exploiting distributed computing architectures. The Cloud migration is carried out by encapsulating the overall P-SBAS application in virtual machines running on the Cloud; moreover, the Cloud resources provisioning and configuration phases are implemented in an automatic way. Such an approach allows us to preserve the P-SBAS parallelization strategy and to straightforwardly evaluate its performance within a Cloud environment by comparing it with those achieved on a HPC in-house cluster. The results we present were achieved by using the Amazon Elastic Compute Cloud (EC2) of the Amazon Web Services (AWS) to process SAR datasets collected by the ENVISAT satellite and show that, thanks to the Cloud resources availability and flexibility, large DInSAR data volumes can be processed through the P-SBAS algorithm in short time frames and at reduced costs. As a case study, the mean deformation velocity map of the southern California area has been generated by processing 172 ENVISAT images. By exploiting 32 EC2 instances this processing took less than 17 hours to complete, with a cost of USD 850. Considering the available PB-scale archives of SAR data and the upcoming huge SAR data flow relevant to the recently launched (April 2014) Sentinel-1A and the forthcoming Sentinel-1B satellites, the exploitation of Cloud Computing solutions is particularly relevant because of the possibility to provide Cloud-based multi-user services allowing worldwide scientists to quickly process SAR data and to manage and access the achieved DInSAR results.

A First Assessment of the P-SBAS DInSAR Algorithm Performances Within a Cloud Computing Environment

We present in this work a first performance assessment of the Parallel Small BAseline Subset (P-SBAS) algorithm, for the generation of Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) deformation maps and time series, which has been migrated to a Cloud Computing (CC) environment. In particular, we investigate the scalable performances of the P-SBAS algorithm by processing a selected ENVISAT ASAR image time series, which we use as a benchmark, and by exploiting the Amazon Web Services (AWS) CC platform. The presented analysis shows a very good match between the theoretical and experimental P-SBAS performances achieved within the CC environment. Moreover, the obtained results demonstrate that the implemented P-SBAS Cloud migration is able to process ENVISAT SAR image time series in short times (less than 7 h) and at low costs (about USD 200). The P-SBAS Cloud scalable performances are also compared to those achieved by exploiting an in-house High Performance Computing (HPC) cluster, showing that nearly no overhead is introduced by the presented Cloud solution. As a further outcome, the performed analysis allows us to identify the major bottlenecks that can hamper the P-SBAS performances within a CC environment, in the perspective of processing very huge SAR data flows such as those coming from the existing COSMO-SkyMed or the upcoming SENTINEL-1 constellation. This work represents a relevant step toward the challenging Earth Observation scenario focused on the joint exploitation of advanced DInSAR techniques and CC environments for the massive processing of Big SAR Data.

Angle Independence Properties of Fractal Dimension Maps Estimated From SAR Data

The extremely remarkable properties of angle independence exhibited by an innovative SAR product, the fractal dimension map estimated from a single SAR image, are discussed. The theoretical analysis is supported by a noticeable data set of actual SAR images acquired, with look angles varying from 20° to 45°, in the stripmap operational mode by the COSMO-SkyMed constellation. The behavior of the fractal dimension maps at different look angles is discussed for both natural and urban scenarios and emphasis is also posed on areas within the same image that, according to the scene macroscopic topography, are characterized by different incidence angles. The whole analysis is aimed at highlighting, on the one hand, the specific independencies of natural surface fractal dimension maps from the look angle and from the local incidence angle, which can be very useful in information extraction and SAR post-processing techniques and, on the other hand, the different fractal dimension maps behavior whereas urban areas are analyzed.

COSMO-SkyMed AO projects - Use of high resolution SAR data for water resource management in semi arid regions

In this paper we present the results of a project approved in the frame of the 2007 Cosmo-Skymed AO, devoted to use high resolution data for hydrology applications in semi-arid context. A case study was developed in Burkina Faso, a West Africa country, characterized by the alternation of intense rainy and dry seasons. In this paper we present the rationale of the project along with two of the obtained products concerning the estimation of eroded areas and the surface water recharge.

On the fractal nature of volcano morphology detected via SAR image analysis: the case of Somma—Vesuvius Volcanic Complex

Abstract In this paper an innovative technique for the extraction of natural surfaces geomorphologic parameters from SAR data is presented and applied for volcano monitoring purposes. The observed surface is modeled as a fractal two-dimensional stochastic process. A theoretical framework for the analysis of the SAR imaging process is outlined. An algorithm founded on this imaging model is presented, allowing the retrieving of the point by point fractal dimension of the imaged surface. Significant results regarding the application of the proposed technique to the case study of the Somma-Vesuvius volcanic complex are shown, along with preliminary comments regarding the comparison with ground truth maps of the surface fractal dimension.

SBAS-DInSAR time series generation on cloud computing platforms

This paper proposes a parallel model for the Differential Interferometry Synthetic Aperture Radar approach referred to as Small BAseline Subset (SBAS) algorithm. This new computational model has been designed to be specifically exploited within the emerging cloud computing environments. An experimental analysis, involving two different case studies, has been carried out to demonstrate the effectiveness of the methodology. The major novelty of the proposed Parallel SBAS (P-SBAS) model consists in the capability of processing large SAR data sets in reasonable time-frames. This key feature may be of great impact not only for hazard monitoring and risk mitigation activities but also for data sharing and knowledge spreading within the scientific community.