Mario Costantini

Use of differential SAR interferometry in monitoring and modelling large slope instability at Maratea (Basilicata, Italy)

Abstract Differential Synthetic Aperture Radar (SAR) interferometry (DiffSAR) allows, in principle, to measure very small movements of the ground and to cover in continuity large areas, so that it can be considered as a potentially ideal tool to investigate landslides and other slope instability. In this paper, we explore the use of this technique to improve our knowledge of the slope instability of a well-investigated area (the Maratea Valley), affected by continuous slow movements, producing an impressive “Sackung”-type phenomenon, which poses several unanswered questions. In particular, by using this technique, we analyse the time evolution of ground movements from 1997 to 2000. The slope movements during this same time interval have also been monitored in the past by using other techniques, such as electronic distance-meter (EDM) and GPS measurements: GPS and DiffSAR results are here compared. In our implementation of the DiffSAR technique, the problem of decorrelation noise is faced by using a phase unwrapping approach that allows to process sparse data, and the impact of atmospheric artefacts is reduced by performing a temporal analysis of the deformations observed in successive interferograms. In this study, we also show that it is possible to perform a temporal analysis of continuous slow landslide movements by using a limited number of ERS SAR data sets and low-precision topographic information. All the acquired data (EDM, GPS and DiffSAR) are consistent and allow a kinematic model of instability within the investigated time interval to be proposed. A map of slopes subject to different velocities of vertical displacements was delineated, modifying previous knowledge. Within the valley, progressive and almost linear displacements over time were confirmed.

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.

Monitoring terrain movements by means of sparse SAR differential interferometric measurements

Synthetic aperture radar differential interferometry is a powerful technique that allows, in principle, the measurement of very small movements of the terrain over time. Unfortunately, SAR differential interferograms are often rather noisy. A recently proposed phase unwrapping approach allows sparse data to be processed, and therefore extraction of the available information from noisy data sets. The authors test the potential of this method on several SAR differential interferometric data sets. In particular, the subsidence phenomena happening in Bologna (Italy) and in the surrounding area from 1993 to 1999 are analyzed. Unwrapped phases corresponding to different pairs are finally combined to perform a full space-time analysis of the considered phenomena.

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.

SAR and Optical Data Fusion for Change Detection

In this work, we devise a change detection technique for urban areas based on the fusion of temporal series of SAR images with a single multi-band optical image. The proposed technique aims at exploiting both the high repetition observation rate available with the new generation of SAR systems and the high level of details available even in a single multiband optical image. The approach has been validated by using a multitemporal set of ENVISAT SAR images and a couple of Quick Bird optical images, that are also used to provide evidence on the changes by visual inspection at high resolution. The preliminary results shown in the paper show the potentiality of the joint processing of SAR and optical images.

SAR tomography for scene elevation and deformation reconstruction: Algorithms and potentialities

Multi-Dimensional (MultiD) SAR imaging is a recent technique, based on coherent SAR data combination, aimed to space (full-3D) and space deformation-velocity (4D) analysis. It is an extension of the concepts of SAR Interferometry and Differential Interferometry and offers new options for the analysis and monitoring of ground scenes. In this work, we discuss the current status and the results obtained by processing ERS real satellite urban data, we investigate perspectives related to the next generation multi-static satellite formations, and we show some sample results regarding 3D and 4D theoretical performance bounds. First space-time 4D analysis results obtained by processing real airborne forest data are also reported.

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.