The development of SAR Interferometry for ground displacement monitoring has led to the implementation of operative services dedicated to the systematic delivery of archives of measurements. The exploitation of such data archives at regional/national scale requires frequently a proper post-processing of the measurements for their correct interpretation. Measurements are in fact provided in the radar line of sight and can be acquired by different angles, recently also with medium inclination orbits. In this work we consider the problem of projecting Differential Interferometric SAR measurements to the ground. We specifically develop a general methodology for linear (i.e., directional) and a planar projection of multi-orbit interferometric measurements, including its particularization to sloping terrains. Presented results highlight that the proposed projection methodology can provide useful and further options for the interpretation of the SAR displacement measurements with reference to the application to landslide monitoring.

SAR interferometry is a well-established ground deformation monitoring technology that has recently enabled the implementation of projects dedicated to the systematic delivery of archives of deformation time series, even at the continental scale. The use of such archives of data for the management of the regional or national territory presumes the implementation of procedures aimed at converting the measurements products useful for the risk assessment. In this work we discuss preliminary results derived by trans-regional archives of deformation measurements for the characterization of slow-moving landslides. We specifically address the problem of implementing procedures aimed at filtering the data and estimating deformation components along the steepest slope direction.

In the last two decades, satellite Multi-Temporal Differential Interferometric SAR (DInSAR) techniques have become consolidated tools for studying slow-moving landslides. Moreover, the availability of sensors using different band frequencies and the development of advanced processing algorithms have constantly improved. In this work we discuss the first results of an experimental analysis carried out on multi-temporal multi-baseline L-Band data acquired by the newly launched SAOCOM satellites in the framework of the MEFISTO project founded by the Italian Space Agency (ASI), one of the main aims of which was to test the potentiality of multi-frequency (X, C and L bands) DInSAR data processed with different methodologies applied to a multi-scale slow-landslide analysis.

Among the several applications of multipass InSAR, monitoring of landslides represents one of the most challenging case because of the topographic characteristics, the heterogeneous displacement rates and the frequent presence of vegetation. In this study, we consider the use of multi-frequency InSAR data for the application to case studies located in the North and South Italy.

We exploit large DInSAR and GPS datasets to create a 4D image of the magma transfer processes at Mauna Loa volcano from 2005 to 2015. The datasets consists of 23 continuous GPS time series and 307 SAR images acquired from ascending and descending orbits by ENVISAT and COSMO-SkyMed satellites. The joint use of SAR data acquired from different orbits together with deformation data from GPS networks and geological information can significantly improve the constraints on the geometry and location of the sources responsible for the observed deformation. The analysis of these datasets has been realized using an innovative method that allows to image a complex configuration of different type of sources. The results suggest that the deformation pattern observed from 2005 to 2015 has been controlled by three deformation sources: the ascent of magma along a conduit, the opening of a dike and the slip along the basal decollement.

This work investigates the capability of Interferometric SAR (InSAR) technique to monitor the atmosphere. Changes in the Atmospheric Phase Screen (APS) derived by InSAR are strictly related to changes in the atmosphere stratification and to the 2-D distribution of the water vapor columnar content. High spatial/temporal resolution APS maps provide by a SAR geosynchronous satellite (GEO-SAR) can be assimilated into limited area models (LAMs) for a better characterization of the local scale phenomena. As the observation of GEO-SAR are taken with high incidence angles, the path delay is measured along the slant direction (STD) and thus both the observation operator and the Global Navigation Satellite System (GNSS) products used for calibrating the APS must be considered along that direction. In this work, we compare the STD predicted by the Weather Research and Forecasting Model (WRF), and retrieved by a network of GNSS stations with the APS derived from Sentinel-1.

This work is aimed at describing the development of an efficient interferometric processing chain, based on the well-known advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) algorithm referred to as Small BAseline Subset (SBAS) technique, for the generation of Sentinel-1A (S1-A) Interferometric Wide Swath (IWS) deformation time-series. Due to the TOPS mode characterizing the IWS acquisitions, the existing SBAS processing chains was properly adapted with new procedures for efficiently handling the S1-A data. The developed SBAS-DInSAR chain has been tested on both S1-A and TOPS RadarSAT-2 interferometric dataset, clearly demonstrating the capability of the developed SBAS-DInSAR processing chain to effectively investigate land subsidence phenomena affecting large areas.

In this work we present a detailed analysis of the co-seismic deformation signals associated with the 2012 Emilia (Northern Italy) seismic crises through spaceborne Differential Synthetic Aperture Radar (SAR) Interferometry. In particular, we provide a general picture of the ground deformation fields relevant to the Ml 5.9 and Ml 5.8 main shocks, by generating four co-seismic displacement maps from X-band COSMO-SkyMed and C-band RADARSAT-1/2 SAR data, collected by descending orbits over the investigated area. Subsequently, we perform an analytical modelling of the seismic events by exploiting the RADARSAT-2 displacement map through a finite dislocation fault, in order to get more information about the earthquake source locations and their geometries.

We have investigated the recent deformation affecting the Messina Strait area in South Italy, across the Calabria and the Sicilia Regions. Messina Strait is an extensional tectonic feature that separates peninsular Italy from Sicily, and it is also one of the most seismically active and deforming area of the Mediterranean. It is located between the Neogene Tyrrhenian backarc basin, developed in the hanging wall of the Apennines, and the Mesozoic-Paleogene Ionian basin, which is the foreland and the area of propagation of the Neogene to present Apennines accretionary prism. We have exploited Synthetic Aperture Radar (SAR) data along the time period between 2002 and 2010 by applying the advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) technique referred to as Small BAseline Subset (SBAS) algorithm. GPS data relative to permanent stations within the study area have been also used.

We carry out a quantitative assessment of the accuracy of the advanced Differential SAR Interferometry (DInSAR) approach referred to as Small BAseline Subset (SBAS) in mapping deformation phenomena affecting active volcanic areas, by exploiting SAR data acquired by the “first” and “second” generation SAR sensors, and by comparing the achieved results with independent geodetic measurements, the latter assumed as reference. In particular, we analyze the impact that the different wavelengths and looking geometries may have in the SBAS-DInSAR measurement retrieval depending on the radar system. To this aim, we consider SAR images acquired by the ERS-1/2 and ENVISAT (C-band) as well as COSMO-SkyMed (X-band) sensors (i.e., by the “first” and “second” generation SAR sensors, respectively) over the Campi Flegrei caldera (Southern Italy) and the in-situ displacement measurements provided by the continuous GPS stations deployed in the area. The performed comparative analysis reveals a general good agreement between DInSAR and geodetic data; it also shows that the single displacement measurements have a sub-centimetric accuracy with a standard deviation of about 0.5 cm.

In this paper the analysis of time series of fractal dimension maps generated from multi-pass SAR images is dealt with. The objective is twofold: on the one hand such an analysis is addressed to assess the performance of the algorithm for the fractal dimension estimation from a single SAR image, i.e., to verify the fractal estimation efficiency on natural scenes within the multiple sensor passes. On the other hand, by exploiting the statistics evaluated starting from the fractal time series, a final fractal dimension map, including only the areas in which the fractal estimation is efficient and strongly denoised from the speckle effect, is obtained. The analysis has been performed on a Cosmo-SkyMed data-set of 42 stripmap images spanning the time period from October 2009 to December 2012, acquired over the Somma-Vesuvius volcanic complex (South Italy), which is in a quiescent stage since the last eruption occurred in 1944.

We present some of the main advances on long term deformation time series analysis achieved thanks to the 10 years of operation of ENVISAT ASAR sensor. This is done by considering a number of selected case studies, which are mostly based on the use of the Small BAseline Subset (SBAS) technique. In particular, we show how we benefit from the ENVISAT data availability to extend the ERS time series, thus allowing us to obtain almost 20 years of deformation history. Moreover, we demonstrate how the multi-mode capability of ENVISAT permits improving the temporal sampling in SBAS time series. Finally, we introduce a novel technique, tested on ENVISAT data, to generate displacement time series in areas affected by large deformation phenomena.

We perform a quantitative assessment of the accuracy of Differential SAR Interferometry (DInSAR) time series in volcanic areas, retrieved through “first” and “second generation” SAR data. In particular, we analyze the impact that the wavelengths and looking geometries may have in the DInSAR measurement retrieval depending on the radar system. To this aim, we focus on the DInSAR algorithm referred to as Small BAseline Subset (SBAS) to generate mean deformation velocity maps and corresponding time series starting from sequences of SAR images. Moreover, we consider collections of SAR data acquired by the ERS-1/2 and ENVISAT (C-band), and COSMO-SkyMed (Xband) sensors over the volcanic area of the Campi Flegrei caldera, Southern Italy. We invert these SAR data sequences through the SBAS-DInSAR technique, thus obtaining C- and X- band deformation time series that we compare to continuous GPS measurements, the latter assumed as reference. The achieved results provide, in addition to a clear picture of the surface deformation phenomena already occurred and occurring in the selected case study, relevant indications for the analysis of the SBAS-DInSAR time series accuracies in volcanic areas passing from the first to second generation SAR sensors.

In this paper the analysis of fractal dimension maps extracted from Cosmo-SkyMed amplitude-only SAR data is considered. The focus is on the Somma-Vesuvius volcanic complex, whose study allows to draw significant comments on the behavior of the fractal maps. In particular, the dependence of the fractal maps on geometrical and geomorphologic characteristics of the imaged surface is investigated. Preliminary results regarding the different behavior of the fractal dimension evaluated on the Gran Cono and on the Mt. Somma are presented.

We investigate the deformation of Mt. Etna volcano (Italy) by exploiting the advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) technique referred to as the Small BAseline Subset (SBAS) algorithm. In particular, we take advantage of the multi-sensor data processing capability of the SBAS algorithm which allows us to generate Mt. Etna mean deformation velocity maps and the corresponding time series in the last eighteen years. To achieve this task we exploit different set of SAR data collected by the European (ERS-1/2, ENVISAT) satellites in the 1992-2010 time interval, and by the Italian COSMO-SkyMed constellation during 2009-2010 period. We also benefit from the availability of ERS-ENVISAT multi-orbit (ascending and descending) data in order to discriminate the vertical and East-West components of the volcano edifice displacements and generate the relevant time series. Finally, we evidence how the higher spatial resolution and denser temporal sampling of the COSMO-SkyMed data, with respect to the European satellites, permit to follow with more details the complex deformative pattern which has characterized the volcano in the last two years.

We present an algorithm aimed at correcting satellite orbit information for the generation of differential SAR interferometry (DInSAR) deformation time-series. Our approach exploits small baseline differential interferograms, to preserve their spatial coherence, and is directly compatible with the Small BAseline Subset (SBAS) DInSAR technique. In particular, the algorithm investigates the differential phase gradient directly computed from the wrapped interferograms, and is focused on the estimation of the perpendicular baseline and of the parallel baseline azimuth rate components, separately performed along the range and azimuth directions, respectively. Starting from the estimations carried out on the interferograms, we then retrieve the orbit correction associated with each SAR acquisition of our time-series by solving a system of linear equations via the SVD method, extending the SBAS inversion concept also to the orbit estimation problem. Key application of this technique is the generation of deformation time-series from interferometric sequences of RADARSAT-1 SAR acquisitions which are available for several areas in the world, but are characterized by significantly low accuracy of the or bit information. The presented results, obtained by processing a data set consisting of 33 RADARSAT-1 images of Big Island at Hawaii, show that we may retrieve DInSAR time-series with sub centimeter accuracy, thus confirming the effectiveness of the pro posed technique.

We perform a full exploitation of the Differential SAR Interferometry (DInSAR) algorithm referred to as Small BAseline Subset (SBAS) technique to investigate long term surface deformation occurring in extended, seismogenetic areas. To this aim we benefit of the SBAS technique capability to work in multi-frame and multi-sensor scenarios in order to improve the spatial and temporal coverage, as well as to employ new generation SAR sensors to increase the temporal sampling of the retrieved time series. In this work we apply the SBAS algorithm to analyze the temporal evolution of the detected displacements affecting three different seismogenetic scenarios by means of deformation time series retrieved through data acquired by European (ERS-1/2, ENVISAT) and Italian (COSMO-SkyMed) satellites. In particular, we focus on the analysis of the deformation patterns associated with the activity of the San Andreas (SAF, California, USA), the North Anatolian (NAF, Turkey) and the Paganica (PF, Abruzzo, Central Italy) Faults. The achieved results provide a clear idea of the surface deformation retrieval capability of the SBAS procedure.

We extend the Small BAseline Subset (SBAS) algorithm to generate deformation time-series from SAR data acquired by the Canadian Space Agency (CSA) RADARSAT-1 sensor. The proposed approach is mostly oriented to the investigation of large scale deformation events with relatively low spatial resolutions (of about 100 × 100 m), and is based on the use of conventional multi-look interferograms with small temporal and spatial baseline separations. With respect to the original SBAS approach, several improvements are required to take into account the inaccuracies on the knowledge of the RADARSAT-1 orbital parameters, and of the significant fluctuations of the dop-pler centroid values over each single SAR scene. This work is aimed to present the first results achieved by applying the implemented RADARSAT-1 SBAS processing chain to an archive of SAR scenes, acquired in the time interval from 2000 to 2003 over, and relevant to the Hawaii Island area. The presented results markedly confirm the effectiveness of the implemented RADARSAT-1 SBAS processing chain.

We present the results of the first experiment to ¿plug¿ the Small BAseline Subset (SBAS) DInSAR algorithm into a GRID-based system; the key idea is to combine the robustness of the exploited advanced interferometric SAR approach with the high computing capability provided by a GRID environment. In particular, we have exploited the low-resolution SBAS algorithm and we benefited of the availability of the ESA Grid Processing-on-demand environment. The presented results, carried out on ENVISAT data, provide a overview of the main characteristics of the implemented SBAS-GRID processing solution.

We investigate the deformation of Mauna Loa and Kllauea volcanoes, Hawai'i, by exploiting the advanced differential Synthetic Aperture Radar Interferometry (InSAR) technique referred to as the Small BAseline Subset (SBAS) algorithm. In particular, we present time series of line-of-sight (LOS) displacements derived from SAR data acquired by the ASAR instrument, on board the ENVISAT satellite, from the ascending (track 93) and descending (track 429) orbits between 2003 and 2008. For each coherent pixel of the radar images we compute time-dependent surface displacements as well as the average LOS deformation rate. Our results quantify, in space and time, the complex deformation of Mauna Loa and Kllauea volcanoes. The derived InSAR measurements are compared to continuous GPS data to asses the quality of the SBAS-InSAR products.

The ASI-SRV (Sistema Rischio Vulcanico) project is devoted to the development of an integrated system based on EO and Non EO data to respond to specific needs of the Italian Civil Protection Department (DPC). ASI-SRV provides the capability to import many different EO and Non EO data into the system, it maintains a repository where the acquired data have to be stored and generates selected products which will be functional to the different volcanic activity phases. The processing modules for Radar and EO Optical sensors data allow to estimate a number of parameters which include: surface thermal proprieties, gas, aerosol and ash emissions and to characterize the volcanic products in terms of composition and geometry, surface deformations in terms of displacements and velocity. All the generated products are related to Italian actives volcanoes and three test sites have been chosen to demonstrate the capability of this integrated system: Vesuvio, Campi Flegrei (Campania region) and Etna (Sicilia region). In this paper the first results obtained by means of modules developed within the ASI-SRV project and dedicated to the processing of EO historical series are presented.

In this work we describe the application of the basic small BAseline subset (SBAS) technique, which exploits multilook interferograms, to a number of active volcanic areas. The use of such a technique reduces the amount of data to be processed and simplifies the analysis of geophysical phenomena occurring in extended areas (up to 100 km by 100 km). Moreover, it can be trivially extended in order to combine data acquired by different sensors with similar geometrical and electromagnetic characteristics, i.e., ERS and ENVISAT IS-2 mode, thus allowing an easy extension of the temporal observation window. The selected test sites for this study are Long Valley caldera, Mt. Etna and the Neapolitan Volcanic district (Mt. Vesuvio and Campi Flegrei caldera). Finally, we shortly analyze the implications of the use of forthcoming SAR sensors that operates in L-and X-bands.

We have investigated the deformation affecting the Campi Flegrei caldera (Italy), from 2002 to the end of 2006, by analyzing ENVISAT ASAR IS-2 data. This study has been performed by exploiting the SBAS-DInSAR algorithm that allows us to detect earth surface displacements and to investigate their temporal evolution via the generation of deformation time series. The presented analysis highlighted the renewed volcanic activity that started on mid-2005; moreover, we have combined the ascending and descending data in order to separate the vertical and east-west components of the detected displacements. The obtained results have been confirmed by the leveling data collected by the Osservatorio Vesuviano.

Accurate subpixel registration of synthetic aperture radar (SAR) images is an issue that is again growing interest since its initial developments related to two-pass interferometry. Recent progress in coherent (multichannel) SAR processing raises the need for accurate registration of data takes acquired with large baseline spans, high temporal coverage, and with different frequency and/or operational modes. In this paper, we discuss a SAR image-registration procedure, based on the use of external measures which allows obtaining a very accurate alignment of SAR images. The presented technique makes use of a digital elevation model and of the precise information about the acquisition flight tracks, to compute the warping functions that map the position of each pixel in the different takes, thus avoiding any approximation. The resulting algorithm is simple, robust, precise, and very efficient; as a matter of fact, it may achieve high accuracy even in critical areas, such as steep topography regions. Moreover, the availability of an analytical and exact model allows performing a detailed sensitivity analysis that can be useful in evaluating the applicability of this technique even to future high-precision satellite systems. Extensive testing, carried out on several real European Remote Sensing and ENVISAT datasets, clearly shows the effectiveness of such algorithm in registering critical SAR images

We exploit the small baseline subset (SBAS) algorithm for generating deformation time-series from SAR data acquired by sensors with different characteristics but with the same illumination geometry. In particular, our approach is focused on the use of European Remote Sensing (ERS) and ENVISAT satellite data, the latter acquired by the Advanced Synthetic Aperture Radar sensor on the IS2 swath. The proposed solution is oriented to investigate large-scale displacements with a relatively low spatial resolution (about 100/spl times/100 m) and implements an easy but effective combination of ERS and ENVISAT multilook interferograms which benefits of the temporal overlap between the acquisitions of the two sensors. Moreover, the algorithm does not rely on specific hypothesis on the spatial or temporal characteristics of the investigated deformations. Presented results, achieved on a synthetic aperture radar dataset relevant to the Napoli city area (Italy), confirm the validity of the approach.

This work addresses the derivation of the phase difference-based maximum likelihood (ML) phase unwrapping algorithm. To this end, we derive the joint statistics of the phase differences on a two-dimensional grid for the multichannel case, where several scaled wrapped phase values are available. Subsequently, we determine and study the structure of the phase difference-based ML estimator and compare it to known phase unwrapping techniques. This work allows us to frame single and multichannel algorithms in a common formulation. Moreover, among the known single-channel phase difference-based procedures, we identify those attaining an ML solution. We also show that multichannel phase difference-based and, recently proposed, phase-based ML algorithms achieve equivalent solutions.

The Small BAseline Subset (SBAS) approach is a differential synthetic aperture radar interferometry (DIFSAR) technique that allows analyzing deformation phenomena affecting both extended area and localized structures, by exploiting the phase difference of SAR image pairs characterized by small baselines. In this work we process a large set of ERS-1/2 data, acquired from ascending and descending orbits, at both small and large scale resolution and extend the obtained time series with available ENVISAT acquisitions. The results, relevant to the Napoli Bay area (Italy), are compared with geodetic and GPS data in order to achieve a quantitative analysis of the SABS algorithm performances

We present a differential synthetic aperture radar interferometry (DIFSAR) technique for generating displacement maps and deformation time-series by exploiting data acquired by the ERS and ENVISAT/ASAR systems. The proposed solution is focused on investigating large scale displacements with a relatively low spatial resolution (of about 100 /spl times/ 100 m). Since the two radar sensors operate at different carrier radar frequencies, the easy computation of cross-platform interferograms is prevented, thus leading to independent subsets of interferograms. An easy and efficient way to combine ERS/ERS and ENVISAT/ENVISAT multilook interferograms is represented by the application of the Small BAseline Subset (SBAS) strategy. This solution guarantees the continuity in the monitoring of the Earth's surface by benefiting of the present and future availability of ASAR data, preserving the archived ERS data. The presented results, obtained on a descending ERS and ENVISAT SAR data set, spanning the time interval from 1992 until October 2003, are relevant to the Napoli Bay area (Italy) and clearly demonstrate the effectiveness of the proposed extension of the SBAS technique.

In this work we present the results of an airborne differential interferometry experiment carried out by using the ORBISAR X-band system. Use of a high track measurement accuracy allowed us to fulfill the requirements of Fornaro et al. (2003), where repeat pass phase accuracy has been quantified in terms of position measurement errors. The presented experiment can be considered a first step towards the development of operative airborne differential interferometry for accurate ground deformation monitoring.

This paper presents a differential synthetic aperture radar (SAR) interferometry (DIFSAR) approach for investigating deformation phenomena on full-resolution DIFSAR interferograms. In particular, our algorithm extends the capability of the small-baseline subset (SBAS) technique that relies on small-baseline DIFSAR interferograms only and is mainly focused on investigating large-scale deformations with spatial resolutions of about 100/spl times/100 m. The proposed technique is implemented by using two different sets of data generated at low (multilook data) and full (single-look data) spatial resolution, respectively. The former is used to identify and estimate, via the conventional SBAS technique, large spatial scale deformation patterns, topographic errors in the available digital elevation model, and possible atmospheric phase artifacts; the latter allows us to detect, on the full-resolution residual phase components, structures highly coherent over time (buildings, rocks, lava, structures, etc.), as well as their height and displacements. In particular, the estimation of the temporal evolution of these local deformations is easily implemented by applying the singular value decomposition technique. The proposed algorithm has been tested with data acquired by the European Remote Sensing satellites relative to the Campania area (Italy) and validated by using geodetic measurements.

This paper provides a closed-form solution to the geolocation problem arising in the generation of digital elevation models (DEMs) via both stereo and interferometric synthetic aperture radar techniques. The proposed solution is found with no approximations in an arbitrary Cartesian reference system, thus efficiently allowing the generation of DEMs in a chosen cartographic projection. Moreover, it is amenable of an easy and precise sensitivity analysis that exploits the full three-dimensional nature of the problem, thus being particularly useful when high-squinted and/or crossed-track acquisitions are considered.

This paper presents a DIFSAR approach that allows us to detect and follow the temporal evolution of surface deformations at different spatial scales. In particular, our solution extends the capability of the algorithm referred to as small baseline subsets (SBAS) technique (Berardino et al., 2002), and allows us to investigate large scale deformation phenomena as well as displacements of single buildings or structures. The proposed technique relies on small baseline DIFSAR interferograms only, in order to mitigate the decorrelation phenomena, and requires two different sets of data generated at low (multi-look) and high (single-look) spatial resolution, respectively. The algorithm has been tested with the data acquired by the European Remote Sensing (ERS) satellites which are relative to the city of Napoli (Italy) and surroundings; the results have been validated by using geodetic data.

We propose a new approach for monitoring the evolution of Earth surface deformations via differential SAR interferometry. It allows us to overcome the limitations of standard techniques by incorporating the knowledge of the deformations associated to tie points and available spatial deformation models.

This work addresses the derivation of a phase-difference (gradient) based maximum likelihood (ML) phase unwrapping algorithm. In particular, we determine and study the structure of the ML phase unwrapping on a 2D grid in the multi-channel case and compare it with existing phase unwrapping algorithms. This allows us first to frame single-channel, phase based phase unwrapping algorithm in a general formulation. Second, among the known single-channel, phase-difference based phase unwrapping algorithms we identify those achieving a ML solution. Although achieving results similar to existing phase-based ML phase unwrapping algorithm in the multi-channel case, our approach allows to easily incorporate possible a priori knowledge about the absolute phase variation dynamics.

We study the effects of residual uncompensated trajectory deviations on the phase accuracy of motion compensated SAR images. We show that linear and quadratic deviations interact with the SAR processing and generate additional phase artifacts with respect to what is expected by simple geometric considerations.

MINERVA (Monitoring by Interferometric SAR of Environmental Risk in Volcanic Areas) is a small scale service demonstration project financed by ESA in the Data User Programme framework. The objective of the project is the design, development and assessment of a demonstrative information service based on the interferometric processing of images from the ASAR instruments on board ERS1/2 and ENVISAT-I. The system is based on a new approach for the processing of INSAR data, which allows to optimize the quality of interferograms spanning from 35 days up to several years, and to merge them to generate a single solution describing the temporal evolution of the ground deformations in the examined risk area. The system allows to update this solution each time a new SAR image is available, and constitutes therefore an innovative tool for monitoring of the ground displacements in risk areas.

We present results obtained via an innovative spaceborne SAR interferometry algorithm showing that, despite its quiescent stage, the Somma-Vesuvius volcanic complex is subject to a particular deformation process. This is characterized by a rather continuous subsidence effect, revealed by both ERS satellite data and levelling surveys, between 1992 and 2000. These deformations are mainly localized in two zones involving the Vesuvius cone and a narrow discontinuous annular area that extends around the base of the Somma edifice. A likely explanation of subsidence at both sites involves the joint effect of gravitational sliding and extensional tectonic stress occurring at the contact between different lithological units.

In the area of tomographic synthetic aperture radar processing we present a new technique that makes use of the singular value decomposition method to improve the resolution limits by including a-priori information about the radiation penetration depth.

This paper presents a new solution for detecting and following the temporal evolution of small scale deformation phenomena; in particular our approach extends the capability of the SBAS technique, presented in P. Berardino et al. (2001), which is mainly focused on investigating large scale deformations with spatial resolutions of about 100 m/spl times/100 m. The proposed technique relies on small baseline differential SAR (DIFSAR) interferograms only, but it is implemented by using two different sets of data generated at low (multi-look data) and high spatial resolution (single-look data), respectively. The former are used to identify and estimate, via the SBAS technique or O. Mora et al. (2001, 2002), possible atmospheric phase artifacts and large scale deformation patterns; the latter to detect, on the high resolution residual phase components, structures highly coherent in time (buildings, rocks, lava structures, etc.), identified jointly to their heights and displacements. In particular the estimation of the temporal evolution of these local deformations is easily implemented by applying the SVD technique. The presented algorithm has been tested with data acquired by the European Remote Sensing (ERS) satellites relative to the Campania area (Italy).

We present a new differential synthetic aperture radar (SAR) interferometry algorithm for monitoring the temporal evolution of surface deformations. The presented technique is based on an appropriate combination of differential interferograms produced by data pairs characterized by a small orbital separation (baseline) in order to limit the spatial decorrelation phenomena. The application of the singular value decomposition method allows us to easily "link" independent SAR acquisition datasets, separated by large baselines, thus increasing the observation temporal sampling rate. The availability of both spatial and temporal information in the processed data is used to identify and filter out atmospheric phase artifacts. We present results obtained on the data acquired from 1992 to 2000 by the European Remote Sensing satellites and relative to the Campi Flegrei caldera and to the city of Naples, Italy, that demonstrate the capability of the proposed approach to follow the dynamics of the detected deformations.

The authors present a new spotlight SAR data-focusing algorithm based on a two-step processing strategy that combines the advantages of two commonly adopted processing approaches: the efficiency of SPECAN algorithms and the precision of stripmap focusing techniques. The first step of the proposed algorithm implements a linear and space-invariant azimuth filtering that is carried out via a deramping-based technique representing a simplified version of the SPECAN approach. This operation allows the authors to perform a bulk azimuth raw data compression and to achieve a pixel spacing smaller than (or equal to) the expected azimuth resolution of the fully focused image. Thus, the azimuth spectral folding phenomenon, typically affecting the spotlight data, is overcome, and the space-variant characteristics of the stripmap system transfer function are preserved. Accordingly, the residual and precise focusing of the SAR data is achieved by applying a conventional stripmap processing procedure requiring a minor modification and implemented in the frequency domain. The extension of the proposed technique to the case of high bandwidth transmitted chirp signals is also discussed. Experiments carried out on real and simulated data confirm the validity of the presented approach, which is mainly focused on spaceborne systems.

This paper presents a new two-dimensional (2-D) phase unwrapping (PhU) algorithm based on a least squares (LS) region growing strategy: the wrapped phase image is partitioned in different regions that are sequentially unwrapped via a LS algorithm. Reliable regions are dealt with at the beginning of the procedure, while critical areas are unwrapped in the final steps, thus avoiding error propagation from critical to reliable areas. A conditioned least squares formulation of the phase unwrapping problem is the core of the proposed procedure: this allows the solution to be tied to "some" known boundary phase values, thus guaranteeing the correct joining of the reconstructed phase in between the different regions and preventing them from being independently unwrapped. The application of the finite element method allows a straightforward implementation of the algorithm in the discrete domain case. Experimental results, carried out on simulated and real interferometric SAR data, show the effectiveness of the proposed algorithm and the improved performances with respect to existing unwrapping procedures.