The IRIDE constellation is an ambitious Italian space program that will support the national authorities in their analyses and monitoring activities, with a focus on Italian territory mapping. It will comprise a series of small satellite subconstellations exploiting a wide range of remote sensing technologies. This article analyses the NIMBUS X-Band synthetic aperture radar (SAR) IRIDE subconstellation, exploring potential orbital configurations beyond the more conventional and widespread dawn-dusk sun-synchronous orbit (SSO) one. In particular, starting from the mission target, we show that a 49° mid-inclination orbit (MIO) in a right-looking StripMap acquisition mode represents a highly effective choice for NIMBUS. We demonstrate that this configuration enhances the systematic coverage of the Italian territory with six nodal days of interferometric revisit time and high spatial resolution, thereby facilitating detailed observations of both natural phenomena and anthropic activities. In terms of differential SAR interferometry (DInSAR) performance, we prove that MIOs do not show significant limitations for what attains the critical baseline and geometric distortions. In addition, MIOs may lead to future advances in creating 3-D displacement maps because they allow for the recovery of the North-South deformation component that, conversely, cannot be precisely measured with DInSAR systems operating in SSO.

In this work, we investigate potential orbital configurations of NIMBUS, one of the Synthetic Aperture Radar (SAR) components of the Italian constellation IRIDE, which will be completed by 2026 under the management of the European Space Agency (ESA), with the support of the Italian Space Agency (ASI). IRIDE is conceptualized as a "constellation of constellations", comprising multiple sub-constellations of satellites positioned in Low Earth Orbit (LEO) and equipped with various sensing technologies, including SAR and optical sensors with medium- and high-resolution capability, operating at different frequency ranges. Given both institutional and commercial users the constellation is expected to fulfill, this work introduces a methodology to compare different orbital configurations and finally identify the optimal orbital arrangement that maximizes the Italian national coverage within the shortest revisit time possible, considering both the capabilities and imaging performance of a SAR system planned for deployment in orbit.

This work describes the airborne Synthetic Aperture Radar (SAR) infrastructure developed at the Institute for Electromagnetic Sensing of the Environment (IREA) - National Research Council of Italy (CNR), Naples, Italy.The current infrastructure consists of a flight and a ground segment, including: a multi-frequency airborne SAR sensor operating at X- and L-band, owned by IREA-CNR; an IT platform for data storage and processing, located at the laboratories of IREA-CNR; an airborne SAR data processing chain, completely developed at IREA-CNR and University Parthenope, Naples, Italy.To show the current capabilities of this infrastructure in terms of characteristics of the final products as well as of quick response in emergency cases, a real world application scenario, namely, the monitoring of the volcanic area of Stromboli, Italy, in the frame of an agreement between IREA-CNR and the Department of Civil Protection of the Italian Presidency of the Council of Ministers, is presented.The short-term future perspectives related to the exploitation of this airborne SAR infrastructure are finally drawn, according to ongoing strengthening actions supported by already assigned fundings.

In this work we focus on the estimation of the soil permittivity from L-band polarimetric Synthetic Aperture Radar (SAR) data. To this aim, we consider SAOCOM-1 data collected in December 2021, over the province of La Pampa, in Argentina. The soil permittivity estimates, obtained through the Polarimetric Two-Scale Model (PTSM), are compared with the in-situ measurements collected at the same time of the SAR acquisition. Our results of the dielectric constant retrieved for the full scene are in accordance with a semi-arid landscape where the mode of the retrieved estimates is around εr~4 and a 2.41% relative error was found for ground data.

The problem of the identification of Radio Frequency Interferences (RFI) that corrupt Synthetic Aperture Radar (SAR) data is addressed in this work.In particular, we propose a new approach based on the minimization of the Bayesian Information Criterion (BIC) able to detect, on a pixel-by-pixel basis, the RFI signals within the considered SAR data.The performance of the proposed approach is assessed by means of both simulated and real-world airborne L-band SAR data corrupted by RFI signals.

The retrieval of the topographic changes induced by the eruptive activity of the Stromboli volcano, located in the Tyrrhenian Sea off Sicily (Italy), is the main topic of this contribution. In particular, we focus on the Stromboli activity during the July 2019 - October 2022 time period that was characterized by two violent explosions and months of lava emission inducing topography changes. These variations have been measured through the comparison of the generated airborne single-pass interferometric Synthetic Aperture Radar Digital Elevation Models.

We investigate in this work the soil moisture retrieval from P-band polarimetric Synthetic Aperture Radar (SAR) data. In particular, the analyzed SAR data were collected during a helicopter-borne campaign conducted over the Apulian Tavoliere plain, Southern Italy, on July 2021. The soil moisture estimates, obtained through the Polarimetric Two-Scale Model (PTSM), are then synthetically compared with in-situ measurements collected at the same time of the radar survey.

It is widely recognized that SAR images can suffer from the presence of RFI, especially at the low frequencies of the microwave spectrum. Such nuisance signals can significantly impair the quality of the SAR data with unwanted effects on the final products. This paper describes a processing strategy for the detection and cancellation of RFI signals corrupting airborne SAR raw-data. In addition, the performance of the proposed strategy is assessed by exploiting airborne L-band FMCW-SAR data.

Airborne synthetic aperture radar (SAR) data focusing in presence of highly variable squint angles is addressed in this work. To do this, a time-domain SAR focusing algorithm has been developed to account for the target-dependent nature of the acquisition squint angle. For comparison purposes, we have considered also a SAR processor based on the use of an azimuth-invariant processing squint angle. Moreover, real data acquired by two different X-band airborne SAR systems have been analyzed. The aims of the work are twofold. First, we show that the adoption of an azimuth-invariant processing squint angle, typically pursued by computationally efficient focusing strategies, may become inappropriate in several airborne missions, which are typically corrupted by motion errors induced by atmospheric turbulence. On the contrary, these problems are circumvented through the developed time-domain focusing strategy, which exploits a target-dependent processing squint angle that is coincident with the acquisition one. Second, we show that the proposed focusing strategy must be properly revised in the case of interferometric processing. In particular, we show that if the (target-dependent) acquisition squint angle is different for the two interferometric channels used, we have to move toward a different focusing paradigm, say, an interferometric focusing solution. This is again based on considering a target-dependent processing squint angle, but for each target, this processing angle should be equal neither to the acquisition squint angle of the “master” acquisition nor to that of the “slave” one: it must instead lie halfway between them. We prove that this approach is appropriate to obtain high interferometric coherence, and it is sub-optimal to separately focus the interferometric channels.

In recent years, airborne Synthetic Aperture Radar (SAR) remote sensing is becoming more and more attractive, thanks to the operational flexibility and observation capabilities provided by aerial SAR systems, and also due to the comparatively low-cost of these radar devices. In this work, we show the preliminary results relevant to the first acquisition campaign of the new Italian airborne Multiband Interferometric and Polarimetric SAR (MIPS) system, which is based on the Frequency Modulated Continuous Wave (FMCW) technology, and is able to operate at both X- and L-band.

In recent years, airborne Synthetic Aperture Radar (SAR) systems based on the Frequency Modulated Continuous Wave (FMCW) technology are becoming very popular thanks to their simple architecture and low cost. When FMCW SAR data are processed, it is essential to accurately know the electronic parameters of the system. In particular, the use of an incorrect value of the Frequency Sweep Rate (FSR) introduces geometric distortions in the focused images. In this work we provide the assessment of the performances of the FSRETC algorithm, recently proposed with the aim of estimating the correct FSR from the radar data. The presented analysis is conducted through the use of real data acquired by an airborne FMCW SAR system.

In this work, a time-domain procedure is presented to focus airborne Synthetic Aperture Radar (SAR) data collected in the presence of strong variations of the squint angle during the radar acquisition. The approach is tested on two datasets acquired by two different X-band airborne SAR systems.

In this work, we present some results of the flight-test campaign carried out with the AXIS system, which is an Italian single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR) based on the frequency modulated continuous wave technology. The system has recently been developed in the frame of a cooperation between a public research institute (IREA-CNR) and a private company (Elettra Microwave). The campaign was performed in 2018 over the Salerno area, South of Italy, and some corner reflectors (CRs) were deployed over the illuminated area with the aim of verifying the system performances in terms of geometric resolution and target location.

The retrieval of soil moisture and surface roughness from P-Band Synthetic Aperture Radar (SAR) data is here addressed. In particular, the presented methodology is based on the Polarimetric Two Scale Model (PTSM) recently proposed in the literature, and exploits the combination of SAR data collected along two antiparallel flight-tracks flown on the same area with a very short revisit time. Some considerations about the effects of the SAR acquisition geometry on the retrieval results are also provided. The used dataset is relevant to a desert campaign carried out in 2018 with the helicopter-borne P-band SAR system owned by the Italian Space Agency.

The Italian Space Agency (ASI) has recently entrusted CO.RI.S.T.A. with the development of a radar system that can be mounted onboard small airplanes or helicopters and may operate, at different frequencies belonging to the P-Band, either as Synthetic Aperture Radar (SAR) or as Sounder. In this work, we present preliminary results of the helicopter-borne desert campaign carried out with this system in 2018 over the Erfoud area, Morocco, in the frame of a project that has involved different public Italian Research Institutes and Universities.

We present an advanced differential synthetic aperture radar (SAR) interferometry (DInSAR) processing chain, based on the Parallel Small BAseline Subset (P-SBAS) technique, for the efficient generation of deformation time series from Sentinel-1 (S-1) interferometric wide (IW) swath SAR data sets. We first discuss an effective solution for the generation of high-quality interferograms, which properly accounts for the peculiarities of the terrain observation with progressive scans (TOPS) acquisition mode used to collect S-1 IW SAR data. These data characteristics are also properly accounted within the developed processing chain, taking full advantage from the burst partitioning. Indeed, such data structure represents a key element in the proposed P-SBAS implementation of the S-1 IW processing chain, whose migration into a cloud computing (CC) environment is also envisaged. An extensive experimental analysis, which allows us to assess the quality of the obtained interferometric products, is presented. To do this, we apply the developed S-1 IW P-SBAS processing chain to the overall archive acquired from descending orbits during the March 2015-April 2017 time span over the whole Italian territory, consisting in 2740 S-1 slices. In particular, the quality of the final results is assessed through a large-scale comparison with the GPS measurements relevant to nearly 500 stations. The mean standard deviation value of the differences between the DInSAR and the GPS time series (projected in the radar line of sight) is less than 0.5 cm, thus confirming the effectiveness of the implemented solution. Finally, a discussion about the performance achieved by migrating the developed processing chain within the Amazon Web Services CC environment is addressed, highlighting that a two-year data set relevant to a standard S-1 IW slice can be reliably processed in about 30 h.The presented results demonstrate the capability of the implemented P-SBAS approach to efficiently and effectively process large S-1 IW data sets relevant to extended portions of the earth surface, paving the way to the systematic generation of advanced DInSAR products to monitor ground displacements at a very wide spatial scale.

This paper shows the design parameters and specifications of the AXIS system, which is an Italian single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR) based on the frequency modulated continuous wave technology. The activity is framed within a cooperation agreement signed between Elettra Microwave S.r.l and the Institute for Electromagnetic Sensing of the Environment (IREA) of the Italian National Research Council (CNR).

In this work we present a fully parallel SBAS-DInSAR processing chain for the effective and massive generation of Sentinel-1 (S-1) Interferometric Wide Swath (IWS) deformation time-series. The pursued strategy to develop such a parallel processing chain fully benefits from the data acquisition characteristics of the TOPS mode, consisting of a series of bursts that can be considered as separate images to be independently processed. Such a data structure fosters the intrinsic parallelization of the S-1 IWS interferometric data processing, which can automatically be carried out through the exploitation of high-performance distributed computing infrastructures, and of efficient algorithms for tackling the huge data flow provided by the S-1 constellation. In order to demonstrate the capability of the presented S-1 P-SBAS processing chain to deal with the huge amount of data acquired by the S-1 constellation, we process a very extended dataset acquired over Italy from which we compute the mean velocity maps and corresponding deformation time-series.

We present a solution for simplifying a recently proposed two-step processing technique that allows to retrieve the constant phase offset present in the unwrapped synthetic aperture radar (SAR) interferograms by exploiting an external, even low-accuracy, digital elevation model (DEM) of the illuminated area and without using corner reflectors. In particular, we show in this letter that the second processing step, namely, the slope-topography-based estimate, can be avoided without impairing the accuracy of the final phase offset estimate. To this aim, we introduce a simple modification to the first step, referred to as phase-based estimate, by considering the vertical bias of the available external DEM as the second unknown parameter in the carried out estimation. The simplified algorithm is very easy to implement and is particularly suitable for airborne SAR interferometry. It has been tested on real airborne SAR data and the obtained results show that the achieved accuracy is the same or better than that achieved through the original two-step approach.

This work aims to describe the characteristics and the status of development, including the results of a first preliminary testing campaign, of a low frequency airborne imaging radar developed in Italy for the Italian Space Agency.

A general-purpose parallel scheme for efficiently focusing synthetic aperture radar (SAR) data on multicore-based shared-memory architectures is presented. The proposed parallel solution is based on a canonical processing pattern that exploit a segmented-block-based approach, and it works successfully on data acquired by different SAR platforms. Insofar as significant portion of the focusing algorithm is amenable to tiling, our approach decomposes the problem into simpler subproblems of the same type, also providing a suitable mechanism to explicitly control the granularity of computation through the proper specification of the tiling. Relevant implementation makes use of multithreading and high-performance libraries. Achievable performances are then experimentally investigated by quantifying the benefit of the parallelism incorporated into the prototype solution, thus demonstrating the validity of our approach.

In order to retrieve information about the sea surface velocity in coastal Mediterranean regions from Synthetic Aperture Radar (SAR) data, in this work we exploit spaceborne as well as airborne data. In particular, we apply two different processing techniques. The first one exploits a single SAR image, whereas the second one, referred to as Along-Track SAR Interferometry, exploits SAR data pairs. The first technique has been applied to spaceborne ENVISAT-1 SAR data, whereas the second one has been applied to airborne data acquired by the Italian InSAeS4 X-band SAR system.

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.

InSAeS4 is an Italian X band airborne SAR system, recently upgraded to a multi-antenna interferometric configuration. The system is able to acquire single pass across-track and along-track multi-baseline data with different acquisition modes characterized by different geometric resolutions and across-track swaths. In recent work we have analyzed the high resolution InSAeS4 products (obtained by transmitting 400 MHz bandwidth pulses), characterized by the narrowest across-track swath (1.5 Km wide). In this work, we focus on the InSAeS4 products characterized by the widest across-track swath, at expenses of the lowest geometric resolution. To this aim we show some results achieved with an interferometric dataset acquired by the system in 2013 over the Napoli area, Italy.

Digital elevation model (DEM) generation through interferometric processing of synthetic aperture radar (SAR) data requires the calculation of a constant phase offset present in the unwrapped interferograms. This operation is usually carried out by exploiting the external information provided by GPS measurements in correspondence of corner reflectors (CRs) properly deployed over the illuminated area. This is, however, expensive in terms of cost and time. Moreover, deployment of CRs along with the corresponding in situ GPS measurements can be difficult (if not impossible) in unfriendly areas or in natural disaster scenarios. To circumvent these limitations, we address in this work the estimation of the required phase offset by exploiting a low-accuracy external DEM, without using CRs. More specifically, a two-step approach is proposed. The first step exploits the synthetic phase computed by means of the external DEM and represents a straightforward extension of the procedure that is usually applied in the presence of CRs. Subsequently, in order to refine the achieved solution, a second step is introduced. It is based on a least squares approach that properly exploits the difference between the available low-accuracy DEM and the interferometric DEM generated by means of the phase offset value roughly estimated through the first step. The presented approach is very easy to implement and allows us to achieve an accurate and fast estimate of the needed phase offset, even in the presence of an external DEM affected by a vertical bias and/or a planar shift. The algorithm performances improve in the presence of a large variation of the look angle, as it generally happens in airborne systems. On the other side, the effectiveness of the algorithm may be impaired by the possible presence of artifacts in the unwrapped interferograms, such as those due to the residual motion errors typical of repeat-pass airborne SAR scenarios. Accordingly, the proposed solution is particularly suitable for single-pass interferometric airborne SAR systems, as demonstrated through the presented experimental results achieved on real data.

TELAER is an Italian airborne X-Band Synthetic Aperture Radar (SAR) system recently upgraded to the interferometric mode thanks to an Italian National Research Council (CNR) funding. This system upgrading has been completed at the beginning of 2013 with a flight-test campaign carried out over the Napoli area, Italy. In this paper we present some results relevant to a single-pass interferometric dataset acquired during these flight-tests.

Synthetic Aperture Radar Interferometry (InSAR) allows the generation of Digital Elevation Models (DEMs) exploiting the phase difference (interferogram) of SAR data pairs relevant to the same illuminated area and received by slightly different look angles. Within the processing chain leading from the acquired SAR data pair to the final InSAR DEM, it is necessary to calculate a proper phase offset value to add to the unwrapped SAR interferogram. Moreover, in the airborne case, it can be necessary also the compensation of the residual motion errors not perfectly removed by the exploited Motion Compensation (MOCO) procedures during the focusing step. In this paper we present a novel algorithm for joint InSAR phase offset calculation and residual motion error compensation based on the use of an external low accuracy DEM. The effectiveness of the proposed algorithm is assessed on real data acquired by the multi-antena airborne OrbiSAR and TELAER system, both operating at X-band.

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 work we focus on the Precise Topography- and Aperture-dependent algorithm, briefly PTA, proposed in the recent literature to remove the residual errors still affecting airborne SAR data focused with standard two-step Motion Compensation algorithms. More specifically, we first show that the azimuth-to-frequency mapping used by the PTA procedure is not fully appropriate, because it does not account for the presence of the residual motion errors themselves. Then, we show how to calculate the correct azimuth-to-frequency mapping able to fully account for the presence of the residual motion errors. Finally, we show how to modify the original PTA in such a way to properly exploit the correct azimuth-to-frequency mapping previously discussed.

Synthetic Aperture Radar Interferometry (InSAR) allows the generation of Digital Elevation Models (DEMs) exploiting the phase difference (interferogram) of SAR data pairs relevant to the same illuminated area and received by slightly different look angles. Within the processing chain leading from the acquired SAR data pair to the final InSAR DEM, it is necessary to calculate a proper phase offset value to add to the unwrapped SAR interferogram. To this aim, different algorithms have been proposed in the literature: most of them make use of very accurate information on the position of Ground Control Points (GCPs), such as Comer Reflectors (CRs), properly deployed over the observed scene. In this paper we present a novel algorithm for InSAR phase offset calculation without using CRs. The effectiveness of the proposed algorithm is assessed on real data acquired by the multi-antenna airborne OrbiSAR system operating at X-Band.

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.

This paper describes the capabilities of the TELAER X-Band airborne SAR system, which has been upgrading according to a Italian National Research Council (CNR) funding. Such a system upgrading consists first of all in the realization of a multi-antenna system able to carry out, simultaneously, Across-Track (XT) and Along-Track (AT) SAR Interferometry (InSAR). Moreover, the system upgrading is also aimed at improving the performances achievable in repeat-pass applications, such as Differential SAR Interferometry, (DInSAR), which require very precise measurement of the tracks described during the flight by the SAR antennas.

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.

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.

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.

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 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.

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 this paper we explore the use of differential synthetic aperture radar interferometry to improve our knowledge of the slope instability of a well investigated area (the Maratea Valley) affected by continuous slow movements. In particular, by using this technique we analyse the time evolution of terrain movements from 1997 to 2000, a time interval already explored using distancemeter (EDM) and GPS measurements. Results obtained by means of different techniques have been compared, and all the acquired data turn out to be consistent.

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.