Fabio Malvarosa

A New Method for Identification and Analysis of Persistent Scatterers in Series of SAR Images

Synthetic aperture radar (SAR) interferometry is a powerful technology for measuring slow terrain movements. The extraction of this information is a complex task, because the phase of the signal is measured only modulo 2pi and is affected by noise and systematic terms. The persistent scatterer (PS) approach brought important advances in the solution of this problem. In this work, we present a new method, named persistent scatterer pairs (PSP) method, for the identification and the analysis of PS in series of full resolution SAR images. The problems coming from orbital and atmosphere phase artifacts are effectively overcome by exploiting their spatial correlation, without using model based interpolations or fits, which can be advantageous when the atmospheric artifacts or the displacement to be retrieved are not very well described by the models used in the standard PS approach. Moreover, the proposed method does not need a preprocessing to calibrate the data and is insensitive to the density of PS candidates, it is able to identify PS in natural terrains and PS characterized by non linear movements, is computationally efficient and highly parallelizable. The results obtained on real ERS SAR data confirm the validity of the proposed approach.

A three-dimensional phase unwrapping algorithm for processing of multitemporal SAR interferometric measurements

Phase unwrapping is the problem of reconstructing a function on a grid given its values modulo 2/spl pi/. This is a key problem in SAR interferometry and in other fields. The typical availability of multiple 2D SAR interferograms of the same scene suggest the possibility of considering the data as samples of a function in a 3D space-time. This helps better reconstructing the right solution, in the same way as 2D phase unwrapping provides more reliable solutions than the 1D (quite trivial) algorithm. However, computational needs result increased in the 3D case. In this work we describe the proposed algorithm for 3D phase unwrapping, and show the results obtained on simulated and real SAR images.

A General Formulation for Redundant Integration of Finite Differences and Phase Unwrapping on a Sparse Multidimensional Domain

Phase unwrapping and integration of finite differences are key problems in several technical fields, among which is synthetic aperture radar (SAR) interferometry. In this paper, we propose a general formulation for robust and efficient integration of finite differences and for phase unwrapping, which includes standard techniques (e.g., minimum cost flow and least squares phase unwrapping) as subcases. The proposed approach allows obtaining more reliable and accurate solutions by exploiting redundant differential estimates (not only between nearest neighboring points) and multidimensional information (e.g., multitemporal). In addition, a model of the signal (e.g., multibaseline or multifrequency) or external data (e.g., GPS or leveling measurements) can be integrated. The method requires the solution of linear or quadratic programming problems, for which computationally efficient algorithms exist. The validation tests performed on real and simulated SAR data confirm the validity of the method, which was integrated in our production chain and successfully used also in massive productions.

Persistent Scatterer Pair Interferometry: Approach and Application to COSMO-SkyMed SAR Data

Persistent scatterer interferometry is a widely used technique to detect and monitor slow terrain movements, with millimetric accuracy, from satellite synthetic aperture radar (SAR) data. We have recently proposed a method, named persistent scatterer pair (PSP), aimed at overcoming some limitations of standard techniques. The PSP method is characterized by the fact of exploiting only the relative properties of neighboring pairs of points for both detection and analysis of persistent scatterers (PSs), intended in the general sense of scatterers that exhibit interferometric coherence for the time period and baseline span of the acquisitions, including both point-like and distributed scatterers. Thanks to the pair-of-point approach, the PSP technique is intrinsically not affected by artifacts slowly variable in space, like those depending on atmosphere or orbits. Moreover, by exploiting a very redundant set of pair-of-point connections, the PSP approach guarantees extremely dense and accurate displacement and elevation measurements, both in correspondence of structures and when the backscattering is weak or distributed as in the case of natural terrains. In all cases, the measurements keep the full resolution of the input SAR images. In this work, the qualifying characteristics of the PSP technique are described, and several application examples and validation tests based on COSMO-SkyMed data are reported, which demonstrate the validity of the proposed approach.

Multi-scale and block decomposition methods for finite difference integration and phase unwrapping of very large datasets in high resolution SAR interferometry

In the last few years high and very high resolution SAR data have become available, opening new possibilities in the field of SAR interferometry. However, the huge amount of data poses new challenges in terms of computational and memory requirements, in particular to those processing steps that require a global approach to obtain good results, such as elevation or velocity finite difference integration and phase unwrapping. In this paper we propose two approaches to overcome this problem. In the first approach the data to be processed are divided in blocks of smaller size, and different strategies are suggested to make the solutions of the different blocks consistent. The second approach is based on a decomposition of the problem at different scales according to a pyramidal scheme, which makes possible to exploit the available information at a global level (thus guaranteeing optimal quality results) with scalable computational demand. The proposed approaches were successfully tested on high resolution COSMO-SkyMed full frame data.

Gravity-driven postseismic deformation following the Mw 6.3 2009 L’Aquila (Italy) earthquake

The present work focuses on the postseismic deformation observed in the region of L’Aquila (central Italy) following the Mw 6.3 earthquake that occurred on April 6, 2009. A new, 16-month-long dataset of COSMO-SkyMed SAR images was analysed using the Persistent Scatterer Pairs interferometric technique. The analysis revealed the existence of postseismic ground subsidence in the mountainous rocky area of Mt Ocre ridge, contiguous to the sedimentary plain that experienced coseismic subsidence. The postseismic subsidence was characterized by displacements of 10 to 35 mm along the SAR line of sight. In the Mt Ocre ridge, widespread morphological elements associated with gravitational spreading have been previously mapped. We tested the hypothesis that the postseismic subsidence of the Mt Ocre ridge compensates the loss of equilibrium induced by the nearby coseismic subsidence. Therefore, we simulated the coseismic and postseismic displacement fields via the finite element method. We included the gravitational load and fault slip and accounted for the geometrical and rheological characteristics of the area. We found that the elastoplastic behaviour of the material under gravitational loading best explains the observed postseismic displacement. These findings emphasize the role of gravity in the postseismic processes at the fault scale.

Analysis and correction of artifacts on differential SAR interferometry for the study of subsidence phenomena

This paper deals with the analysis and correction of artifacts on differential synthetic aperture radar (SAR) interferometry. Particularly, we concentrate on those artifacts arising from the use in interferometric processing of low accuracy acquisition geometry data. To remove these artifacts, we propose a new algorithm able to estimate the acquisition geometry parameters with high accuracy directly from the SAR data. The application of the proposed technique to the study of the subsidence phenomena in Bologna (Italy) and the surrounding area is also presented to validate the new algorithm.

Method of persistent scatterer pairs (PSP) and high resolution SAR interferometry

Synthetic aperture radar (SAR) interferometry is an effective technology for detection and monitoring of slow terrain movements with millimetric resolution. This information is extracted by means of complex techniques from the phase of the signal, which is wrapped modulo 2π and affected by noise and systematic terms. We have recently proposed a new method, named persistent scatterer pairs (PSP), aimed at overcoming some limitations of standard persistent scatter interferometry (PSI) techniques. The method is characterized in that it works only with pairs of nearby pixels both for selecting and analyzing the persistent scatterers (PS), thus being intrinsically not affected by artifacts slowly variable in space, like those depending on atmosphere or orbits. Moreover, the method does not require an initial selection of PS based on the radar backscattered amplitude. In this work, after resuming the main ideas of the PSP method, we show some results obtained in extensive applications with ERS/ENVISAT data, and the first results obtained with high resolution COSMO-SkyMed images.

New insights into earthquake precursors from InSAR

We measured ground displacements before and after the 2009 L’Aquila earthquake using multi-temporal InSAR techniques to identify seismic precursor signals. We estimated the ground deformation and its temporal evolution by exploiting a large dataset of SAR imagery that spans seventy-two months before and sixteen months after the mainshock. These satellite data show that up to 15 mm of subsidence occurred beginning three years before the mainshock. This deformation occurred within two Quaternary basins that are located close to the epicentral area and are filled with sediments hosting multi-layer aquifers. After the earthquake, the same basins experienced up to 12 mm of uplift over approximately nine months. Before the earthquake, the rocks at depth dilated, and fractures opened. Consequently, fluids migrated into the dilated volume, thereby lowering the groundwater table in the carbonate hydrostructures and in the hydrologically connected multi-layer aquifers within the basins. This process caused the elastic consolidation of the fine-grained sediments within the basins, resulting in the detected subsidence. After the earthquake, the fractures closed, and the deep fluids were squeezed out. The pre-seismic ground displacements were then recovered because the groundwater table rose and natural recharge of the shallow multi-layer aquifers occurred, which caused the observed uplift.

A novel approach for redundant integration of finite differences and phase unwrapping on a sparse multidimensional domain

Phase unwrapping and integration of finite differences are key problems in several technical fields, among which SAR interferometry. In this paper we propose a general formulation for robust and efficient integration of finite differences and for phase unwrapping, which includes standard techniques methods as sub-cases. The proposed approach allows obtaining more reliable and accurate solutions by exploiting redundant differential estimates (not only between nearest neighboring points) and multi-dimensional information (e.g. multitemporal, multi-frequency, multi-baseline), or external data (e.g. GPS measurements). The method requires the solution of linear or quadratic programming problems, for which computationally efficient algorithms exist. The validation tests performed confirm the validity of the technique.