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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.

Differential Synthetic Aperture Radar Interferometry (DInSAR) represents by now an established tool for the remote monitoring of the ground displacements occurring on our planet. In addition, this technique is benefiting from the recent advancements in radar, navigation and aeronautical technologies. These indeed allow us on one side to avail of wide-coverage SAR satellites to observe larger and larger areas of the Earth’s surface. On the other side, they make it possible to profit of cost-efficient aerial SAR systems, whose operative flexibility can play a crucial role to observe phenomena possibly hidden to satellite sensors and for the prompt monitoring in emergency scenarios. In this work, we provide the results of a ground deformation analysis performed over the municipality of Vazante, Brazil, based on the DInSAR processing of the data acquired by both the space-borne C-band Sentinel-1A and the drone-borne multi-frequency (P/L/C-bands) DBSS SAR systems.

We present the implementation of a global archive of Differential Synthetic Aperture Radar Interferometry (DInSAR) co-seismic deformation maps. The archive has been generated by automatically processing all the Copernicus Sentinel-1 data spanning about 300 significant (at least Mw > 5.5) earthquakes all over the Earth. An empirical relation between magnitude and epicenter depth was considered to limit the study to those earthquakes that can likely induce ground deformation. DInSAR processing has been carried out within a Cloud-Computing (CC) environment, specifically the Amazon Web Services, to benefit of high processing capacity. The generated DInSAR results are then made freely and openly available to the Solid Earth scientific community through the European Planet Observing System (EPOS) Research Infrastructure.

In this work, we present the ground deformation analysis of the Italian Peninsula carried out via the Sentinel-1 (S-1) Parallel Small BAseline Subset (P-SBAS) approach. In particular, we generate surface deformation time-series and the corresponding mean deformation velocity maps by considering the overall archive of S-1 data acquired from both ascending and descending orbits during the March 2015 - December 2018 period. Moreover, we perform a large-scale comparison of the retrieved results with the deformation measurements of the available GPS stations deployed on the Italian territory and provided by the Nevada Geodetic Laboratory at the University of Nevada, Reno, USA (UNR-NGL). Finally, we properly combine the ascending and descending deformation time-series in order to compute the vertical and east-west components of the retrieved surface displacements. The achieved results demonstrate the capability of the P-SBAS processing chain to efficiently process large S-1 datasets to investigate ground deformation dynamics of large portions of the Earth surface.

A synthetic aperture radar can offer not only an accurate monitoring of the earth surface deformation, but also information on the troposphere, such as the total path delay or the columnar water vapor at high horizontal resolution. This can be achieved by proper interferometric processing and postprocessing of the radar interferograms. The fine and unprecedented horizontal resolution of the tropospheric products can offer otherwise unattainable information to be assimilated into numerical weather prediction models, which are progressively increasing their resolving capabilities. A number of tricks on the most effective processing approaches, as well as a novel method to pass from multipass differential interferometry products to absolute tropospheric columnar quantities are discussed. The proposed products and methods are assessed using real Sentinel-1 data. The experiment aims at evaluating the accuracy of the derived information and its impact on the weather prediction skill for two meteorological events in Italy. The main perspective of the study is linked to the possibility of exploiting interferometric products from a geosynchronous platform, thus complementing the inherent high resolution of SAR sensors with the required frequent revisit needed for meteorological applications.

We present in this work an advanced processing pipeline for continental scale differential synthetic aperture radar (DInSAR) deformation time series generation, which is based on the parallel small baseline subset (P-SBAS) approach and on the joint exploitation of Sentinel-1 (S-1) interferometric wide swath (IWS) SAR data, continuous global navigation satellite system (GNSS) position time-series, and cloud computing (CC) resources. We first briefly describe the basic rationale of the adopted P-SBAS processing approach, tailored to deal with S-1 IWS SAR data and to be implemented in a CC environment, highlighting the innovative solutions that have been introduced in the processing chain we present. They mainly consist in a series of procedures that properly exploit the available GNSS time series with the aim of identifying and filtering out possible residual atmospheric artifacts that may affect the DInSAR measurements. Moreover, significant efforts have been carried out to improve the P-SBAS processing pipeline automation and robustness, which represent crucial issues for interferometric continental scale analysis. Then, a massive experimental analysis is presented. In this case, we exploit: (i) the whole archive of S-1 IWS SAR images acquired over a large portion of Europe, from descending orbits, (ii) the continuous GNSS position time series provided by the Nevada Geodetic Laboratory at the University of Nevada, Reno, USA (UNR-NGL) available for the investigated area, and (iii) the ONDA platform, one of the Copernicus Data and Information Access Services (DIAS). The achieved results demonstrate the capability of the proposed solution to successfully retrieve the DInSAR time series relevant to such a huge area, opening new scenarios for the analysis and interpretation of these ground deformation measurements.

We investigate the deformation of Mt. Etna volcano (Italy) by exploiting the 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 twenty-five years. To achieve this task, we exploit different set of SAR data collected by ERS-1/2, ENVISAT, COSMO-SkyMed and Sentinel-1 radar sensors in the 1992-2018 time interval. We, also, show the deformation pattern induced by the recent seismo-volcanic crisis occurring from 24 to 27 December 2018. The main results show that the East-West displacement map highlights the most significant entities, whose maximum values exceed 30 cm towards the West and 40 towards the East on the summit of the volcano. In this scenario, the measurements permit to model the geometry and characteristics of the causative deformation sources; preliminary results suggest the presence of two different sources: a shallow dyke feeding the eruptive activity at summit craters and a major strike-slip fault/s on the southeastern flank nucleating the 26 th mainshock.

We present an unsupervised tool for the automatic generation of co-seismic displacement maps by using satellite Differential Synthetic Aperture Radar Interferometry (DInSAR) technique. The tool relies on the use of Sentinel-1 SLC Interferometric Wide Swath (IWS) data and main earthquake information, the latter retrieved from on-line global catalogs. In particular, the tool collects location, depth and magnitude of a seismic event and immediately triggers the data download and the interferometric process over the area affected by the earthquake. The generated DInSAR results (mainly interferograms and displacement maps) are then made available to the Solid Earth scientific community through the EPOS Research Infrastructure. Moreover, the implemented system is also used to serve the Italian Department of Civil Protection in case of main seismic events in Italy. Finally, due to the Sentinel-1 characteristics, the obtained results can contribute to the generation of a global database of DInSAR co-seismic displacement maps.

In this work we implement a completely automatic interferometric processing chain, based on the well-known advanced DInSAR algorithm referred to as Parallel Small BAseline Subset (P-SBAS), for the generation of Sentinel-l (S-1) Interferometric Wide Swath (IWS) deformation mean velocity maps and time-series of very wide areas, implemented within the Amazon Web Services (AWS) Elastic Cloud Compute environment. Our processing chain consists of the initial data query to the S-1 archive that we created on the AWS S3 storage, then the data transfer to the AWS computing nodes, the data processing and, finally, the transfer of the obtained interferometric results back to the original S3 storage. In order to demonstrate the capability of the implemented Cloud-based processing chain to deal with massive amount of data, we focus our analysis on the whole Italian territory by processing all the available data acquired both from ascending and descending orbits within the October 2014 - March 2017 time interval. As final result we combine the retrieved LOS displacements in order to compute the mean velocity maps and time-series of the vertical and East-West surface deformation components.

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 an automatic pipeline implemented within the Amazon Web Services (AWS) Cloud Computing platform for the interferometric processing of large Sentinel-1 (S1) multi-temporal SAR datasets, aimed at analyzing Earth surface deformation phenomena at wide spatial scale. The developed processing chain is based on the advanced DInSAR approach referred to as Small BAseline Subset (SBAS) technique, which allows producing, with centimeter to millimeter accuracy, surface deformation time series and the corresponding mean velocity maps from a temporal sequence of SAR images. The implemented solution addresses the aspects relevant to i) S1 input data archiving; ii) interferometric processing of S1 data sequences, performed in parallel on the AWS computing nodes through both multi-node and multi-core programming techniques; iii) storage of the generated interferometric products. The experimental results are focused on a national scale DInSAR analysis performed over the whole Italian territory by processing 18 S1 slices acquired from descending orbits between March 2015 and April 2017, corresponding to 2612 S1 acquisitions. Our analysis clearly shows that an effective integration of advanced remote sensing methods and new ICT technologies can successfully contribute to deeply investigate the Earth System processes and to address new challenges within the Big Data EO scenario.

In recent years, a second generation of Synthetic Aperture Radar (SAR) satellite sensor has been designed and, partially, put into operation, leading to an important breakthrough in Earth Science studies. The common characteristics of such new systems are, indeed, a reduced revisit time (as short as a few days) and, in most cases, an improved spatial resolution (as small as a few meters), providing scientists with unprecedented data for the mapping and monitoring of natural and human-induced hazards. This paper provides an overview on the new observational capability offered by the second generation of SAR sensors, especially in the field of ground deformation analysis for mitigating the risk associated with natural and human-induced hazards. In particular, we exploit the high resolution X-band data acquired by the COSMO-SkyMed (CSK) constellation to show how deformation phenomena characterized by limited spatial extent and extremely fast dynamics can be detected and investigated in details. Whenever possible, we compare the achieved results with those obtained by using data collected by the first generation ERS-1/2 and ENVISAT systems. A comparison with one ALOS satellite dataset is also included. Most of the results, based on the application of Differential SAR Interferometry (DInSAR) techniques, highlight how this technology is not anymore just a sophisticated tool for remotely studying surface deformation phenomena, but it is becoming an operational system for near-real time deformation monitoring. Moreover, we also show how the improved spatial resolution extends the possibility to exploit SAR image amplitude, instead of phase, for direct comparison with optical data and for imaging large deformation episodes, typically associated with strong seismic events, for which DInSAR may fail.

We present a simple and effective filtering algorithm to mitigate noise effects in a time-redundant sequence of multi-look small baseline (SB) differential synthetic aperture radar (SAR) interferograms by exploiting the temporal relationships among the selected interferometric data pairs. The proposed method relies on the estimation of the (wrapped) filtered phase terms associated to each SAR acquisition; this result is achieved via a non-linear minimization procedure which is applied to the phase signal of conventional multi-look interferograms without any pixel selection process, and with no a-priori information on the statistics of the involved complex-valued SAR images. Following their estimation, the phase images are paired to reconstruct a new sequence of filtered SB differential interferograms, which are used to generate surface deformation products, such as deformation velocity maps and displacement time-series. The filtering algorithm effectiveness is demonstrated by analysing a set of SAR images...

Detection and monitoring of deformations affecting cultural heritage sites and their surroundings represent a key issue for developing strategies for their preservation, particularly in the case of extended archaeological areas. In this chapter, we first introduce the differential SAR interferometry (DInSAR) techniques that, thanks to their capability of performing noninvasive deformation analyses, provide valuable information about the spatial and the temporal evolution of the detected displacements. Subsequently, we present the DInSAR results achieved over the whole archaeological site of the ancient Roman city of Pompeii (Italy), and focus on some historical buildings where small displacements, involving portions or the whole complex structure, have been detected.

In this paper we develop a model of the ground deformation behaviour occurred at Ischia Island (Southern Italy) in the 1992–2010 time period. The model is employed to investigate the forces and physical parameters of the crust controlling the subsidence of the Island. To this aim, we integrate and homogenize in a Finite Element (FE) environment a large amount of data derived from several and different observation techniques (i.e., geological, geophysical and remote sensing). In detail, the main steps of the multiphysics model are: (i) the generation of a 3D geological model of the crust beneath the Island by merging the available geological and geophysical information; (ii) the optimization of a 3D thermal model by exploiting the thermal measurements available in literature; (iii) the definition of the 3D Brittle/Ductile transition by using the temperature distribution of the crust and the physical information of the rocks; (iv) the optimization of the ground deformation velocity model (that takes into account the rheological stratification) by considering the spatial and temporal information detected via satellite multi-orbit C-Band SAR (Synthetic Aperture Radar) measurements acquired during the 1992–2010 time period. The achieved results allow investigating the physical process responsible for the observed ground deformation pattern. In particular, they reveal how the rheology modulates the spatial and temporal evolution of the long-term subsidence phenomenon, highlighting a coupling effect of the viscosities of the rocks and the gravitational loading of the volcano edifice. Moreover, the achieved results provide a very detailed and realistic velocity field image of the subsurface crust of the Ischia Island Volcano.

We present an overview of the Differential SAR Interferometry algorithm referred to as Small BAseline Subset (SBAS) technique, that allows us to detect surface deformation and to analyze their space-time characteristics. Following the description of the main theoretical aspects of the algorithm, we present several results obtained by applying the SBAS approach in selected case studies relevant to phenomena affecting volcanic areas (Campi Flegrei caldera and Somma-Vesuvio complex, Italy), aquifers (Santa Clara area within the San Francisco bay, California) and landslides (Maratea Valley, Italy). The overall analysis is carried out by using multilook DInSAR interferograms with a spatial resolution of the order of 100 × 100 m, computed from SAR data acquired by the ERS-1 and ERS-2 sensors. In particular, we highlight the peculiarities of the SBAS technique and its surface deformation retrieval capability for what concerns both large-scale deformation phenomena and more localized displacement effects.

The island of Ischia, located at the northwestern end of the Gulf of Napoli (Italy), is a volcanic area that is historically active (the Arso eruption, in 1302 and the Casamicciola earthquake, in 1883) and has diffuse hydrothermal phenomena. We present in this work a study of the surface deformation occurring in the island, which is based on applying the Differential Synthetic Aperture Radar Interferometry (DInSAR) algorithm referred to as Small BAseline Subset (SBAS) technique. This study is focused on the 1992–2003 time interval and SAR data acquired by the European Remote Sensing (ERS) satellites from ascending and descending orbits have been used, thus allowing us to discriminate the vertical and east–west components of the displacements. A validation of the DInSAR results has been carried out first by comparing the vertical deformations estimated from the SAR data with those measured from the spirit leveling network that is present in the area. In particular, we computed the difference between the mean vertical deformation velocities estimated from the SAR and the corresponding geodetic measurements along three main leveling lines; the maximum value of the root mean square difference is of about 1 mm/yr. The final discussion is dedicated to the interpretation of the detected displacements, benefiting from the overall information extracted from the ascending and descending DInSAR measurements. In particular, DInSAR data relative to the vertical deformation component show that the present-day subsidence of Ischia mainly develops in areas characterized by active landsliding and along faults; moreover, the deflation of the island, which is recorded by the horizontal displacement component, is probably related to the de-pressurization of the hydrothermal system.

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 an enhanced version of the SBAS-DInSAR processing chain, which complements the conventional SBAS codes with a simple noise-filtering procedure that allows us to mitigate noise artifacts affecting the sequence of multi-look (multi-temporal) small baseline interferograms used within the SBAS inversion. We demonstrate that the use of such a noise-filtering algorithm permits to significantly improve the quality of the mean deformation velocity maps and displacement time-series retrieved via the SBAS-DInSAR processing chain, thus promoting more detailed analyses of the detected deformation phenomena. The overall effectiveness of the enhanced SBAS-DInSAR approach is confirmed by the experimental results achieved by applying the proposed method to two sets of SAR data collected by the ERS-1/2 and ENVISAT sensors over the Mt. Etna volcano (Southern Italy) and Yellowstone caldera (Wyoming, U.S.).

We present an efficient solution to mitigate phase unwrapping (PhU) errors that can affect a sequence of multi-temporal differential synthetic aperture radar (SAR) interferograms. To this aim, we propose a strategy that, starting from a properly chosen network of differential interferograms, complements PhU operations with an advanced multi-temporal region-growing (RG) procedure that exploits the space-time relationships among the computed interferograms. In particular, the proposed method implements an iterative procedure that, at each step, allows correcting a sequence of previously unwrapped interferograms at one selected pixel, namely candidate pixel, by exploiting the (unwrapped) phase values at its neighbouring 'seed' pixels (i.e. the ones already correctly unwrapped). Following their estimation, the unwrapped phases are then used to retrieve surface deformation products, such as mean deformation velocity maps and displacement time series, through (advanced) small baseline differential SAR interferometry (DInSAR) techniques. The effectiveness of the presented RG PhU algorithm is demonstrated by analysing a data set of SAR images acquired by the European Remote Sensing (ERS)-1/2 sensors over the megacity area of Istanbul, Turkey.

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 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 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 propose advances on the generation of deformation time series in areas affected by large deformation dynamics, where the exploitation of the differential SAR phase can be strongly limited by severe misregistration errors or by very high fringe rates. First, to overcome the former issue, we present an extension of the amplitude-based Pixel-Offset (PO) analyses by applying the Small BAseline Subset (SBAS) strategy, in order to move from the investigation of single (large) deformation events to that of dynamic phenomena. Secondly, to handle the high fringe rate interferograms, we subtract from them properly generated synthetic deformation models allowing us to reduce the fringe rate, thus helping the phase unwrapping step. The proposed approaches have been tested on ASAR-ENVISAT data acquired on Galapagos Islands and validated via continuous GPS measurements.

[1] This work is focused on advanced differential SAR interferometry (DInSAR) techniques for the generation of deformation time series from sequences of SAR images. We first present the basic rationale of these techniques providing some details of the most well known algorithms. Subsequently, through the analysis of selected case studies focused on the available C-band SAR data archives, we show the relevance of the retrieved spatially dense deformation time series for the comprehension of several geophysical phenomena. We finally introduce, again via a real case study, the advances brought in by the new generation X-band space-borne SAR sensors, highlighting new investigation possibilities for fast varying deformation phenomena.

[1] Campi Flegrei caldera, located near the highly populated city of Naples, southern Italy, is characterized by long-term subsidence punctuated by fast uplift phases. Most of the interpretations of the ground deformation are still based on standard models that assume the lithosphere to behave as a homogeneous half-space. However, several geophysical investigations show the presence of vertical and lateral heterogeneities, especially in the shallow subsurface, which might have an effect on the interpretation of the surface displacements. Our 3-D finite element models, constrained by seismic tomography to take into account the realistic distribution of mechanical heterogeneities, demonstrate that at Campi Flegrei the assessment of the source location is independent of the consideration of 3-D heterogeneities, while the evaluation of its strength is overestimated. Thus, we propose an approach that still allows use of standard homogeneous half-space models but accounts for 3-D heterogeneity effects. This procedure, applied to the deformation field revealed by Differential Synthetic Aperture Radar Interferometry (DInSAR) over the past 16 years, provides new insights for the understanding of the ground displacements observed at Campi Flegrei caldera. This work provides an approach for a quantitative evaluation of the effects of mechanical heterogeneities on surface deformation. Analogous procedures can be also applied in other volcanic areas where, similar to Campi Flegrei caldera, a priori information on the mechanical heterogeneities distribution is available.

We study the state of deformation of Tenerife (Canary Islands) using Differential Synthetic Aperture Radar Interferometry (DInSAR). We apply the Small BAseline Subset (SBAS) DInSAR algorithm to radar images acquired from 1992 to 2005 by the ERS sensors to determine the deformation rate distribution and the time series for the coherent pixels identified in the island. Our analysis reveals that the summit area of the volcanic edifice is characterized by a rather continuous subsidence extending well beyond Las Cañadas caldera rim and corresponding to the dense core of the island. These results, coupled with GPS ones, structural and geological information and deformation modeling, suggest an interpretation based on the gravitational sinking of the dense core of the island into a weak lithosphere and that the volcanic edifice is in a state of compression. We also detect more localized deformation patterns correlated with water table changes and variations in the deformation time series associated with the seismic crisis in 2004.

[1] We investigate the 2004–2006 uplift phase of Campi Flegrei caldera (Italy) by exploiting the archive of ascending and descending ENVISAT SAR data acquired from November 2002 to November 2006. The SBAS-DInSAR technique is applied to generate displacement mean velocity maps and time series. An appropriate post-processing step is subsequently applied to map the areas whose temporal deformation behavior is correlated with that of the maximum uplift zone. Our results show that the deformation also extends outside the volcanological limits of the Neapolitan Yellow Tuff caldera, without significant discontinuities. The DInSAR data are inverted by considering a finite spheroid and an isotropic point-source. The inversion results suggest that the new uplift is characterized by a source location similar to the previous small uplift event of 2000 and to the long term subsidence of the 1990's. In particular, the source is located at a depth of about 3.2 km and very close to the city of Pozzuoli (about 800 m offshore, to the SW); the associated volume variation is about 1.1 106 m3/year.

We present the results of the first experiment to survey the temporal evolution of the deformation affecting very large areas using the small baseline subset (SBAS) differential synthetic aperture radar interferometry (DInSAR) algorithm. In particular, we have analyzed a set of 264 descending European Remote Sensing (ERS) SAR data frames from 1992 to 2000; these data are relevant to an area in central Nevada (U.S.) that extends for about 600times100 km. The starting point of our study has been the generation of an appropriate set of small baseline multilook interferograms computed from long SAR image strips, which were obtained by jointly focusing six contiguous raw data frames. Following their generation, the selected interferograms, which are computed on a spatial grid of 160times160 m, have been inverted via the SBAS technique to retrieve, for each coherent pixel, the displacement time series and the corresponding mean deformation velocity. The presented results are, to our knowledge, the first ones with such an extended multitemporal SAR data set, and they demonstrate the effectiveness of the approach to analyze the deformation of the investigated zone.

[1] We use the Small BAseline Subset (SBAS) InSAR algorithm to obtain radar line-of-sight deformation velocities for two adjacent SAR swaths and invert the data for the 2-D velocity field in vertical and ground range direction. The analysis reveals areas of rapid deformation caused by mining and agricultural activities in the Crescent Valley, Nevada, USA. The LOS displacements of up to 25 centimeters during the 1992–2002 period are caused by vertical and horizontal deformation. About 8 mm/yr horizontal velocity is detected 10 km from the BARGEN GPS site LEWI suggesting that the GPS station may be moving in response to the water pumping. In the Basin and Range anthropogenic ground deformation can extend several tens of kilometers from the basins into the bedrock of the Ranges.

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.

We investigate in this work the performance of the Small BAseline Subset (SBAS) approach that is a Differential Synthetic Aperture Radar Interferometry (DInSAR) algorithm allowing the generation of mean deformation velocity maps and displacement time series from a data set of subsequently acquired SAR images. In particular, we have carried out a quantitative assessment of the SBAS procedure performance by processing SAR data acquired by the European Remote Sensing Satellite (ERS) sensors and comparing the achieved results with geodetic measurements that are assumed as reference. The analysis has been focused on the Napoli bay (Italy) and Los Angeles (California) test areas where different deformation phenomena are present and, at the same time, a large amount of ERS SAR data is available as well as geometric leveling (in the Napoli zone) and continuous GPS (in the Los Angeles zone) measurements, to be used for our performance analysis. Moreover, due to the presence of large urbanized zones, the selected test sites are also characterized by extended, highly coherent areas in the DInSAR maps. The presented study shows that the SBAS technique provides an estimate of the mean deformation velocity with a standard deviation of about 1 mm/year for a typical ERS data set including between 40 and 60 images. Moreover, the single displacement measurements, computed with respect to a reference point of known motion, show a sub-centimetric accuracy with a standard deviation of about 5 mm, consistently in both the SAR/leveling and SAR/GPS comparisons; we also show that there is an increase of this standard deviation value as we move away from the reference SAR pixel, with an estimated spatial variation value of about 0.05 mm/km.

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

[1] The Los Angeles, California, metropolitan area is a tectonically active region with surface deformation that is a combination of fault related tectonics plus a variety of natural and anthropogenic signals. We apply the small baseline subset (SBAS) algorithm to produce an interferometric synthetic aperture radar (InSAR) time series analysis for the Los Angeles area using data acquired by the ERS satellites from late 1995 into 2002. The result is a space-time deformation product that can be exploited to view not only the smoothly varying long-term surface motion, but also its time varying patterns. Large seasonal oscillations of the Santa Ana aquifer observed in Southern California Integrated GPS Network (SCIGN) data are accurately matched in the InSAR time series, moreover, correlations of the InSAR time series with an annual sinusoid allows us to investigate the dynamics of the hydrologic system. INDEX TERMS: 1243 Geodesy and Gravity: Space geodetic surveys; 1294 Geodesy and Gravity: Instruments and techniques; 1803 Hydrology: Anthropogenic effects. Citation: Lanari, R., P. Lundgren, M. Manzo, and F. Casu (2004), Satellite radar interferometry time series analysis of surface deformation for Los Angeles, California, Geophys. Res. Lett., 31, L23613, doi:10.1029/2004GL021294.

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.

About 54% of world population nowadays lives in urban areas and this percentage is expected to increase up to 66% by 2050. Therefore, it is crucial to manage this social and cultural change by collecting, integrating and sharing reliable and open spatial information concerning the urban environments where we leave in. The present availability of huge archives of synthetic aperture radar (SAR) data collected since 1992 by ESA, in conjunction with the available Earth-Observation (EO) optical data, represents a unique possibility to derive valuable information for the understanding of the ongoing urban processes. In this framework, the three-year project financed by the Italian Ministry of Instruction, Research and University, entitled "URBAN GEOmatics for bulk information generation, data assessment and technology awareness" may play a role for the assessment and the development of new replicable methodologies for the study of soil consumption and mobility in urban zones. The paper aims to present some preliminary results achieved during the project, clarifying how the new emerging technologies for managing big EO data are proficient for the investigation of urban processes.