This PDF file contains the front matter associated with SPIE Proceedings Volume 9243, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

The COSMO-SkyMed (CSK) constellation acquires data from its four SAR X-band satellites in several imaging modes, providing in particular different view angles. The present work investigates the potential of CSK constellation for ground elevation measurement through SAR radargrammetry. We selected an area around Parkfield (California), where several CSK acquisitions are available. We used for radargrammetric processing 2 CSK spotlight image pairs acquired at 1 day of separation, in Same Side Viewing configuration, with baselines of 350 km. Furthermore, a dataset of 33 spotlight images were selected to derive height measurements through both persistent scatterers interferometry(PSI) and interferometric processing of 5 1-day separated pairs included in the dataset. We first predict how the errors in the geometrical parameters and the correlation level between the images impact on the height accuracy. Then, two DEMs were derived by processing the radargrammetric CSK pairs. According to the outcomes of the feasibility analysis, processing parameters were chosen in order to guarantee nominal values of height accuracy within the HRTI Level 3 specifications. The products have a final resolution of 3 m. In order to assess the accuracy of these radargrammetric DEMs, we used the height values provided by the PSI, and an interferometric DEM derived from the CSK tandem-like pairs.

State of the art simulations are of great interest when designing a new instrument, studying the imaging mechanisms due to a given scenario or for inversion algorithm design as they allow to analyze and understand the effects of different instrument configurations and targets compositions. In the framework of the studies about a new instruments devoted to the estimation of the ocean surface movements using Synthetic Aperture Radar along-track interferometry (SAR-ATI) an End-to-End simulator has been developed. The simulator, built in a high modular way to allow easy integration of different processing-features, deals with all the basic operations involved in an end to end scenario. This includes the computation of the position and velocity of the platform (airborne/spaceborne) and the geometric parameters defining the SAR scene, the surface definition, the backscattering computation, the atmospheric attenuation, the instrument configuration, and the simulation of the transmission/reception chains and the raw data. In addition, the simulator provides a inSAR processing suit and a sea surface movement retrieval module. Up to four beams (each one composed by a monostatic and a bistatic channel) can be activated. Each channel provides raw data and SLC images with the possibility of choosing between Strip-map and Scansar modes. Moreover, the software offers the possibility of radiometric sensitivity analysis and error analysis due atmospheric disturbances, instrument-noise, interferogram phase-noise, platform velocity and attitude variations. In this paper, the architecture and the capabilities of this simulator will be presented. Meaningful simulation examples will be shown.

Spaceborne synthetic aperture radars (SARs) operating at X-band and above allow observations of Earth surface at very high spatial resolution. Moreover, recent polarimetric SARs enable the complete characterization of target scattering and extinction properties. Nowadays several spaceborne X-band SAR systems are operative, and plans exist for systems operating at higher frequency bands (i.e. Ku, Ka and W). Although higher frequencies may have interesting and distinctive applications, atmospheric effects, especially in precipitating conditions, may affect the surface SAR response in both the signal amplitude and its phase, as assessed by numerous works in the last years. A valid tool to analyze and characterize the SAR response in these conditions is represented by forward modeling, where a known synthetic scenario, which is described by user-selected surface and atmospheric conditions, is considered. Thus, the SAR echoes corresponding to the synthetic scenarios are simulated using electromagnetic models. In this work a 3-D realistic polarimetric SAR response numerical simulator is presented. The proposed model framework accounts for the SAR slant observing geometry and it is able to characterize the polarimetric response both in amplitude and phase. In this work we have considered both X and Ka bands, thus exploring the atmospheric effects for the present and future polarimetric systems. The atmospheric conditions are simulated using the System for Atmospheric Modeling (SAM) which is an high-resolution mesoscale model. SAM is used to define the three-dimensional distribution of hydrometeors which are among the inputs used in the Hydrometeor Ensemble Scattering Simulator (HESS) T-Matrix which allow simulating the SAR signal due to the atmospheric component. The SAR surface component is, instead, simulated by a Semi Empirical Model (SEM) for bare-soils conditions and SEAWIND2 two-scale model for ocean surfaces. The proposed methodology has been applied in this work to assess the sensitivity of the considered frequency bands to different hydrometeor spatial distributions above some examples surface backgrounds.

This paper provides a proof-of-concept for the use of the new Intermittent Small Baseline Subset (ISBAS) approach to study ground elevation changes in areas of peat and organic soils in north Wales, which are generally, unfavourable for conventional C-band interferometric applications. A stack of 53 ERS-1/2 C-band SAR scenes acquired between 1993 and 2000 in descending mode was processed with both the standard low-pass SBAS method and ISBAS. The latter revealed exceptional improvements in the coverage of ground motion solutions with respect to the standard approach. The number of identified coherent and intermittently coherent pixels increased by a factor of 26 with respect to the SBAS solution, and extended the coverage of results across unfavourable land covers, particularly for coniferous woodland, bog, acid grassland and heather. The greatest increase was achieved over coniferous woodland, which showed ISBAS/SBAS pixel density ratios above 300. Despite the intermittent nature of the ISBAS solutions, ISBAS provided velocity standard errors generally below 1-1.5 mm/yr, thus preserving good quality of the estimated ground motion rates.

This second part of the paper about the creation and compilation of the Christchurch, New Zealand, dataset for the detection of earthquake damages in urban areas deals with the extraction of additional information from the 3D model that can aid in the detection of destructions. This includes the creation of a height image of the scene, shadow and layover masks and using a modified version of the SAR simulator CohRaS® to simulate masks of the expected location of specular reflections in the real TerraSAR-X scene after the earthquake. The algorithms used for the extraction of these data sets and some ideas for their application for the damage detection task are discussed and first preliminary results are shown.

Nowadays, space-borne Synthetic Aperture Radar (SAR) sensors, can achieve spatial resolutions in the order of 1 m. However, the exploitation of SAR at very high resolution (VHR) for detecting sparse and isolated damages in urban areas, caused by earthquakes, is still a challenging task. Within urban settlements, the scattering mechanisms are extremely complex and simple change detection analyses or classification procedures can hardly be performed. In this work the 2009, L’Aquila (Italy), earthquake has been considered as case study. Despite about 300 people were killed by the earthquake, few buildings were completely collapsed, and many others were heavily/partially damaged, resulting in a quite sparse damage distribution. We have visually analyzed pairs of VHR SAR data acquired by COSMO-SkyMed satellites, in SPOTLIGHT mode, before and after the earthquake. Such analyses were performed to understand the SAR response of damaged structures surrounded by unaffected buildings, with the aim to identify possible strategies to map the damaged buildings by using an automatic classification procedure. The preliminary analyses based on RGB images, generated by combining pre- and post-event backscattering images, allowed us to figure out how the completely collapsed and the partially damaged buildings are characterized in the SAR response. These outcomes have been taken into account to set up a decision tree algorithm (DTA). Decision rules and related thresholds were identified by statistically analyzing the values of backscattering and derived features. This study point out that many pieces of information and discrimination rules must be exploited to obtain reliable results when dealing with non-extensive and sparse damage within a dense urban settlement.

Advanced remote sensing techniques based on space-borne Synthetic Aperture Radar (SAR) have been developed during the last decade showing their applicability for the monitoring of surface displacements in landslide areas. This paper presents an advanced Persistent Scatterer Interferometry (PSI) processing based on the Stable Point Network (SPN) technique, developed by the company Altamira-Information, for the monitoring of an active slowmoving landslide in the mountainous environment of El Portalet, Central Spanish Pyrenees. For this purpose, two TerraSAR-X data sets acquired in ascending mode corresponding to the period from April to November 2011, and from August to November 2013, respectively, are employed. The objective of this work is twofold. On the one hand, the benefits of employing Nonlocal Interferomtric SAR (NL-InSAR) adaptive filtering techniques over vegetated scenarios to maximize the chances of detecting natural distributed scatterers, such as bare or rocky areas, and deterministic point-like scatterers, such as man-made structures or poles, is put forward. In this context, the final PSI displacement maps retrieved with the proposed filtering technique are compared in terms of pixels' density and quality with classical PSI, showing a significant improvement. On the other hand, since SAR systems are only sensitive to detect displacements in the line-of-sight (LOS) direction, the importance of projecting the PSI displacement results retrieved along the steepest gradient of the terrain slope is discussed. The improvements presented in this paper are particularly interesting in these type of applications since they clearly allow to better determine the extension and dynamics of complex landslide phenomena.

This paper examines target models that might be used in simulations of Synthetic Aperture Radar imagery. We examine the basis for scattering phenomena in SAR, and briefly review the Swerling target model set, before considering extensions to this set discussed in the literature. Methods for simulating and extracting parameters for the extended Swerling models are presented. It is shown that in many cases the more elaborate extended Swerling models can be represented, to a high degree of fidelity, by simpler members of the model set. Further, it is shown that it is quite unlikely that these extended models would be selected when fitting models to typical data samples.

The suggested wavelet-based despeckling method for multi-look SAR images does not use any thresholding and window processing to avoid ringing artifacts, blurring, fusion of edges, etc. Instead, the logical operation of comparison is applied to wavelet coefficients which are presented in spatial oriented trees (SOTs) of wavelet decomposition calculated for one and the same region of the earth surface during SAR spacecraft flight. Fusion of SAR images is decided by keeping the smallest wavelet coefficients from different SOTs in high frequency subbands (details). The wavelet coefficients related to the low frequency subband (approximation) are processed by another special logical operation providing with a good smoothing. It is because the described procedure depends on properties of the chosen wavelet basis then the library of wavelet bases is applied. The procedure is repeated for each wavelet basis. To select the best SOTs (and hence, the best wavelet basis) there is the special cost function which considers the SOTs as so-called coherent structures and shows which of wavelet bases brings the maximum entropy. The results of computer modeling and comparison with few well-known despeckling procedures have shown the superb quality of the proposed method in the sense of different criteria as PSNR, SSIM, etc.

In this work we explored a dataset made by more than 100 images acquired by COSMO-SkyMed (CSK) constellation over the Port-au-Prince (Haiti) metropolitan and surrounding areas that were severely hit by the January 12th, 2010 earthquake. The images were acquired along ascending pass by all the four sensors of the constellation with a mean rate of 1 acquisition/week. This consistent CSK dataset was fully exploited by using the Persistent Scatterer Interferometry algorithm SPINUA with the aim of: i) providing a displacement map of the area; ii) assessing the use of CSK and PSI for ground elevation measurements; iii) exploring the CSK satellite orbital tube in terms of both precision and size. In particular, significant subsidence phenomena were detected affecting river deltas and coastal areas of the Port-au-Prince and Carrefour region, as well as very slow slope movements and local ground instabilities. Ground elevation was also measured on PS targets with resolution of 3m. The density of these measurable targets depends on the ground coverage, and reaches values higher than 4000 PS/km² over urban areas, while it drops over vegetated areas or along slopes affected by layover and shadow. Heights values were compared with LIDAR data at 1m of resolution collected soon after the 2010 earthquake. Furthermore, by using geocoding procedures and the precise LIDAR data as reference, the orbital errors affecting CSK records were investigated. The results are in line with other recent studies.

In this paper, the authors have investigated whether the noise whitening procedure developed as a preprocessing step before despeckling of detected images may be useful also in contexts where phase information is exploited. In a preliminary test set, an interferometric pair of COSMO-SkyMed StripMap images, featuring industrial buildings and vegetated areas, has been: 1) focused without Hamming window (aimed at improving the focusing of targets at the cost of introducing a spatial correlation of background noise), starting from raw data. 2) focused with Hamming window, starting from raw data; 3) preprocessed for complex noise whitening, starting from data at point 2). From the complex interferograms, coherence and interferometric phase maps have been calculated for the three cases by means of boxcar filtering. In case 1) coherence is low on vegetation and also suffers from spreading of areas characterized by strong backscattering because of the presence of high sidelobes. In case 2) points targets and buildings in general are much more defined, thanks to the sidelobe suppression achieved by Hamming filtering, but the background coherence is abnormally increased, due to the introduction of a spatial correlation. Case 3) is the most favorable because whitening operation carries out low coherence on vegetation and high coherence on buildings, where the effects of Hamming filtering are retained. An analysis of the phase field reveals that case 3) should be expedited also in terms of phase unwrapping. Thus, the whitening procedure, devised as a blind preprocessing patch of SLC data, with the goal of a better despeckling, is useful also for SAR interferometry, in which the tradeoff, dictated by the coefficient of the Hamming window, between the ideal situations of focused targets and uncorrelated speckle may be relaxed.

A multitemporal algorithm (MLTA) to retrieve soil moisture from radar data, already developed and preliminarily validated for Sentinel 1¹, has been modified/updated in order to ingest data provided by the future SMAP (Soil Moisture Active and Passive) mission. Moreover, the MLTA has been tested using actual EO data at C-band and in situ data considering a sort of worst case i.e., under well-developed vegetation conditions. The implemented MLT approach consists of integrating a dense time series of radar backscatter measurements within a multitemporal inversion scheme based on the Bayesian Maximum A Posteriori (MAP) criterion. The MAP estimator maximizes the probability density function of the vector of soil parameters (soil moisture and roughness) conditioned to the measurement vector. To correct the vegetation effects, the water cloud model has been modified in order to better account for the effect of the volume scattering. Preliminary results have assessed the potential of the algorithm at L-band, whilst the SAR C-band data turned out to be sensitive to soil moisture even when vegetation was developed.

Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all applications related to the environmental disciplines, such as climatology, meteorology, hydrology and agriculture. Satellite sensors operating in the low part of microwave spectrum are very suitable for this purpose, and their signals can be directly related to the moisture content of the observed surfaces, provided that all the contributions from soil and vegetation to the measured signal are properly accounted for. Among the algorithms used for the retrieval of SMC from both active (i.e. Synthetic Aperture Radar, SAR or real aperture radars) and passive (radiometers) microwave sensors, the artificial neural networks (ANN) represent the best compromise between accuracy and computation speed. ANN based algorithms have been developed at IFAC, and adapted to several radar and radiometric satellite sensors, in order to generate SMC products at different spatial resolutions, varying from hundreds of meters to tens of kilometers. These algorithms, which use the ANN techniques for inverting theoretical and semi-empirical models, such as Advanced Integral Equation (AIEM), Oh models, and Radiative transfer Theory (RTT), have been adapted to the C-band acquisitions from SAR (Envisat/ASAR) and real aperture radar (ASCAT) and to the X-band SAR acquisitions of Cosmo-SkyMed and TerraSAR-X. Moreover, a specific ANN algorithm has also been implemented for the L-band active and passive acquisitions of the incoming SMAP mission. The latter satellite will carry onboard simultaneously one radar and one radiometer operating at the same frequency, but with different spatial resolutions (3 and 40 km, respectively). Large datasets of co-located satellite acquisitions and direct SMC measurements on several test sites located worldwide have been used along with simulations derived from forward electromagnetic models for setting up, training and validating these algorithms. An overall quality assessment of the obtained results in terms of accuracy and computational cost was carried out, and the main advantages and limitations for an operational use of these algorithms have been evaluated.

The goal of this study was to assess the applicability of medium resolution SAR time-series, in combination with in-situ point measurements and machine learning, for the estimation of soil moisture content (SMC). One of the main challenges was the combination of SMC point measurements and satellite data. Due to the high spatial variability of soil moisture a direct linkage can be inappropriate. Data used in this study were a combination of in-situ data, satellite data and modelled SMC from the hydrological model GEOtop. To relate the point measurements with the satellite pixel footprint resolution, a spatial upscaling method was developed. It was found that both temporal and spatial SMC patterns obtained from various data sources (ASAR WS, GEOtop and meteorological stations) show similar behaviors. Furthermore, it was possible to increase the absolute accuracy of the estimated SMC through spatial upscaling of the obtained in-situ data. Introducing information on the temporal behavior of the SAR signal proves to be a promising method to increase the confidence and accuracy of SMC estimations. Following steps were identified as critical for the retrieval process: the topographic correction and geocoding of SAR data, the calibration of the meteorological stations and the spatial upscaling.

The application of Persistent Scatterer Interferometry (PSI) to slope instability monitoring poses challenges related to the complex kinematics of the phenomenon, as well as to the unfavourable settings of the area affected by landslides, often occurring on sites of limited extension, characterized by steep topography and variable vegetation cover. New-generation SAR sensors, such as TerraSAR-X (TSX) thanks to their higher spatial resolution, make PSI applications very promising for monitoring areas with low density man-made. Nevertheless, the application of techniques still remains problematic or impossible in rural and mountainous areas. This is the case, for instance, for the Municipality of Carlantino, in Southern Italy. Both C-band medium resolution SAR data from ESA satellites, and X-band high resolution SAR data from the TSX satellite, were processed through the PSI algorithm SPINUA. Despite the higher spatial density of PS from TSX, the landslide body is lacking coherent targets, due to vegetation and variable land cover. To allow stability monitoring, a network of six CRs was designed and deployed over the landslide test site. Twenty-six TSX stripmap images were processed by using both PSI and an ad hoc procedure based on double-difference analysis of DInSAR phase values on the CR pixels, constrained by the accurate CR height measurements provided by DGPS. Despite the residual noise due to the sub-optimal CR network and the strong atmospheric signal, displacement estimation on the CRs allows to propagate the PSI results downslope, proving the stability of the landslide area subjected to consolidation works.

SAR systems are recently used to generate robust and projectable information about maritime traffic, ice extent and geohazards. By utilising multiple SAR satellites dynamic information can be derived at variable temporal scales. Therefore acquisition systems and processing techniques become a key issue which is requested to work in a robust and efficient way. This paper will present generalized concepts for a monitoring approach that address unmatched or interferometric acquisitions. Its goal is to show the potential of increasing the acquisition rate but also to illustrate limitations resulting from the specific monitoring schemes and their combination. The paper will visualise practical examples derived from realized studies and projects. Finally we can conclude that an agile multi satellite and multi-mode SAR system, such as COSMO-SkyMed, is well suited to monitor to dynamic phenomena on the earth’s surface. The practicability needs to be discussed in detail case by case related to the real world requirements.

The PSIG procedure is a new approach to Persistent Scatterer Interferometry (PSI), which is implemented in the in-house PSI chain of the Geomatics Division of the CTTC. The PSIG procedure has been successfully tested over urban, rural and vegetated areas using X-band SAR data. This paper briefly describes the main steps of the procedure, mainly focusing on the two key processing steps of the approach. The first one is a selection of Persistent Scatterers (PS) consisting in a candidate Cousin PS (CPS) selection based on a phase similitude criteria that allows a correct phase unwrapping and a phase unwrapping consistency check. The second key element is a 2+1D phase unwrapping algorithm, which consists in a 2D phase unwrapping followed by a 1D phase unwrapping that allows the detection and correction of unwrapping errors. The results of the CPS selection and the 2+1D phase unwrapping obtained using a stack of 28 TerraSAR-X StripMap images over the metropolitan area of Barcelona are shown.

A Ground-Based Synthetic Aperture Radar (GB-SAR) is nowadays employed in several applications. The processing of ground-based, space and airborne SAR data relies on the same physical principles. Nevertheless specific algorithms for the focusing of data acquired by GB-SAR system have been proposed in literature. In this work the impact of the main focusing methods on the interferometric phase dispersion and on the coherence has been studied by employing a real dataset obtained by carrying out an experiment. Several acquisitions of a scene with a corner reflector mounted on a micrometric screw have been made; before some acquisitions the micrometric screw has been displaced of few millimetres in the Line-of-Sight direction. The images have been first focused by using two different algorithms and correspondently, two different sets of interferograms have been generated. The mean and standard deviation of the phase values in correspondence of the corner reflector have been compared to those obtained by knowing the real displacement of the micrometric screw. The mean phase and its dispersion and the coherence values for each focusing algorithm have been quantified and both the precision and the accuracy of the interferometic phase measurements obtained by using the two different focusing methods have been assessed.

Digital Elevation Model (DEM) is a key input for the development of risk management systems. Main limitation of the current available DEM is the low level of resolution. DEMs such as STRM 90m or ASTER are globally available free of charge, but offer limited use, for example, to flood modelers in most geographic areas. TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement), the first bistatic SAR can fulfil this gap. The mission objective is the generation of a consistent global digital elevation model with an unprecedented accuracy according to the HRTI-3 (High Resolution Terrain Information) specifications. The mission opens a new era in risk assessment. In the framework of ALTAMIRA INFORMATION research activities, the DIAPASON (Differential Interferometric Automated Process Applied to Survey Of Nature) processing chain has been successfully adapted to TanDEM-X CoSSC (Coregistered Slant Range Single Look Complex) data processing. In this study the capability of CoSSC data for DEM generation is investigated. Within the on-going FP7 RASOR project (Rapid Analysis and Spatialisation and Of Risk), the generated DEM are compared with Intermediate DEM derived from the TanDEM-X first global coverage. The results are presented and discussed.

Within the Copernicus programme there is much interest in the ability of remote sensing technology to deliver operational solutions to many areas of life including environmental management. This paper describes research focused on the application of Earth Observation for Integrated Coastal Zone Management. The main topic of this research is to explore to which extent salt marsh vegetation habitats can be identified from polarimetric SAR remotely sensed data. Multi-frequency, multi-polarimetric SAR images from airborne (S- and X-Band quad-polarimetric from the Astrium airborne SAR Demonstrator) is used to examine salt marsh habitat classification potential in the Llanrhidian salt marshes in South Wales, UK. This is achieved by (1) using both supervised and unsupervised classification routines, using several polarimetric SAR data layers as backscatter intensity, band ratios and polarimetric decomposition products, and by (2) statistical analysis by regression of these different SAR data layers and botanical parameters acquired from recent ecological fieldwork.

This work aims at investigating the capability of COSMO-SkyMed® (CSK®) constellation of Synthetic Aperture Radar (SAR) system to monitor the Leaf Area Index (LAI) of different crops. The experiment was conducted in the Marchfeld Region, an agricultural Austrian area, and focused on five crop species: sugar beet, soybean, potato, pea and corn. A linear regression analysis was carried out to assess the sensitivity of CSK® backscattering coefficients to crops changes base on LAI values. CSK® backscattering coefficients were averaged at a field scale (<σ°dB>) and were compared to the DEIMOS-1 derived values of estimated LAI. LAI were as well averaged over the corresponding fields (<LAIest>). CSK® data acquired at three polarizations (HH, VV and VH), four incidence angles (23°, 33°, 40° and 57°) and at different pixel spacings (2.5 m and 10 m) were tested to assess whether spatial resolution may influence results at a field scale and to find the best combination of polarizations and CSK® acquisition beams which indicate the highest sensitivity to crop LAI values. The preliminary results show that sugar beet can be well monitored (r = 0.72 - 0.80) by CSK® by using any of the polarization acquisition modes, at moderate to shallow incidence angles (33° - 57°). Slightly weaker correlations were found, at VH polarization only, between CSK® < σ°dB> and <LAIest> for potato (r = 0.65), pea (r = 0.65) and soybean (r = -0.83). Shallower view incidence angles seem to be preferable to steep ones in most cases. CSK® backscattering coefficients were no sensitive at all to LAI changes for already developed corn fields.

In this work we address the synergy of optical, SAR (Synthetic Aperture Radar) and topographic data in soil moisture retrieval over an Alpine area. As estimation technique, we consider Gaussian Process Regression (GPR). The test area is located in South Tyrol, Italy where the main land types are meadows and pastures. Time series of ASAR Wide Swath - SAR, optical, topographic and ancillary data (meteorological information and snow cover maps) acquired repetitively in 2010 were examined. Regarding optical data, we used both, daily MODIS reflectances, and daily NDVI, interpolated from the 16-day MODIS composite. Slope, elevation and aspect were extracted from a 2.5 m DEM (Digital Elevation Model) and resampled to 10 m. Daily soil moisture measurements were collected in the three fixed stations (two located in meadows and one located in pasture). The snow maps were used to mask the points covered by snow. The best performance was obtained by adding MODIS band 6 at 1640 nm to SAR and DEM features. The corresponding coefficient of determination, R2, was equal to 0.848, and the root mean square error, RMSE, to 5.4 % Vol. Compared to the case when no optical data were considered, there was an increase of ca. 0.05 in R2 and a decrease in RMSE of ca. 0.7 % Vol. This work showed that the joint use of NDVI or water absorption reflectance with SAR and topographic data can improve the estimation of soil moisture in specific Alpine area and that GPR is an effective method for estimation.

SAR instruments with polarimetric capabilities, high resolution and short revisit time can provide powerful support in oil spill monitoring and different techniques of analysis have been developed for this purpose [1][2]. An oil film on the sea surface results in darker areas in SAR images, but careful interpretation is required because dark spots can also be caused by natural phenomena. In view of the very low backscatter from slicks, the Noise Equivalent Sigma Zero (NESZ) is a primary sensor parameter to be considered when using a sensor for slick analysis. Among the existing full polarimetric sensors, the high resolution and very low NESZ values of UAVSAR (L-band) and RADARSAT-2 (C-band) make them preferable for oil spill analysis compared to the last generation SAR instruments. The Deepwater Horizon disaster that occurred in the Gulf of Mexico in 2010 represents a unique and extensive test site where large amounts of SAR imagery and ground validation data are available. By applying the Cloude-Pottier decomposition method to full polarimetric UAVSAR (L-band) and RADARSAT-2 (C-band), it is possible to extract parameters that describe the scattering mechanism of the target. By comparing quasi-simultaneous acquisitions and exploiting the different penetration capabilities of the sensors, we investigate the potential of full polarimetric SAR to discriminate oil on the sea surface from look-alike phenomena covering the full range of backscattering values down to those at the instrument noise floor.

This paper presents a novel algorithm for wake detection in Synthetic Aperture Radar images of the sea. The algorithm has been conceived as part of a ship traffic monitoring system, in charge of ship detection validation and to estimate ship route features, such as heading and ground speed. In addition, it has been intended to be adequate for inclusion in an automatic procedure without human operator supervision. The algorithm exploits the Radon transform to identify the images ship wake on the basis of the well known theoretical characteristics of the wakes’ geometry and components, that are the turbulent wake, the narrow-V wakes, and the Kelvin arms, as well as the typical appearance of such components in Synthetic Aperture Radar images of the sea as bright or dark linear feature. Examples of application to high-resolution X-band Synthetic Aperture Radar products (COSMOSkymed and TerraSAR-X) are reported, both for wake detection and ship route estimation, showing the achieved quality and reliability of wake detection, adequacy to automatic procedures, as well as speed measure accuracy.

Ka-band RADAR frequency range has not yet been used for Synthetic Aperture Radar (SAR) from space so far, although this technology may lead to important applications for the next generation of SAR space sensors. Therefore, feasibility studies regarding a Ka-band SAR instrument have been started [1][2], for the next generation of SAR space sensors. In spite of this, the lack of trusted references on backscatter at Ka-band revealed to be the main limitation for the investigation of the potentialities of this technology. In the framework of the ESA project “Ka-band SAR backscatter analysis in support of future applications”, this paper is aimed at the study of wave interaction at Ka-band for a wide range of targets in order to define a set of well calibrated and reliable Ka-band backscatter coefficients for different kinds of targets. We propose several examples of backscatter data resulting from a critical survey of available datasets at Ka-band, focusing on the most interesting cases and addressing both correspondences and differences. The reliability of the results will be assessed via a preliminary comparison with ElectroMagnetic (EM) theoretical models. Furthermore, in support of future technological applications, we have designed a prototypal software acting as a “library” of earth surface radar response. In our intention, the output of the study shall contribute to answer to the need of a trustworthy Ka-Band backscatter reference. It will be of great value for future technological applications, such as support to instrument analysis, design and requirements’ definition (e.g.: Signal to Noise Ratio, Noise Equivalent Sigma Zero).

An interferometric performance analysis for repeat-pass geosynchronous circular SAR (GEOCSAR) is presented. The analysis mainly includes the errors caused by the following sources: radar thermal noise, spatial baseline decorrelation, images’ misregistration and the atmospheric effects. For circular SAR (CSAR) imaging on the geosynchronous orbit, the altitude is very high, the atmospheric effect is severe and the high sidelobe is existed in the focused GEOCSAR signal, the characteristics of the various error sources of GEOCSAR interferometry will behave differently from the conventional interferometric SAR.

As the introducing first part of this paper, the data set of Christchurch, New Zealand, is outlined with regard to its purpose: the detection of earthquake damages. The aim is to produce simulated SAR images that are realistic enough to function successfully as pre-event images in a change detection effort. To this end, some modifications to the input 3D city model are introduced and discussed. This includes the use of a GIS map, for a realistic modelling of the radiometric variety, and the insertion of high vegetation to the model, so as to achieve a realistic occlusion of building corners. A detailed description of the impact, these modifications have on the simulation, is given and a comparison between the simulations and corresponding real data is drawn.

SAR Tomography is the extension of the conventional interferometric radar signal processing, extended in the height dimension. In order to improve the vertical resolution with respect to the classical Fourier methods, high resolution approaches, based on the Convex Optimization (CVX), has been implemented. This methods recast in the Compressed Sensing (CS) framework that optimize tomographic smooth profiles via atomic decomposition, in order to obtain sparsity. The optimum solution has been estimated by Interior Point Methods (IPM). The problem for such kind of signal processing is that the tomographic phase information may be suppressed and only the optimized energy information is available. In this paper we propose a method in order to estimate an optimized spectra and phase information projecting each vector components of each tomographic resolution cell spanned in the real and the imaginary component. The tomographic solutions has been performed by processing multi-baseline SAR datasets, in a full polarimetric mode, acquired by a portable small Continuous Wave (CW) radar in the X band.

Defence Research and Development Canada has been investigating 3-D through wall synthetic aperture radar (SAR) imaging from an experimental L-band through-wall SAR prototype. Tools and algorithms for 3-D visualization are being developed to exploit the resulting imagery. In this paper, a comprehensive study of the characteristics of human target signatures in free space and behind two different wall structures is presented using 3-D SAR data. The aim of this investigation is to gain a better appreciation of the signatures of targets when placed behind different wall materials. An analysis of the human target signature in different poses is provided. There was very close agreement between the measured physical dimensions of the targets and those obtained from the strong returns in the SAR imagery. Viewing of the SAR data as 2-D slices provides a qualitative means of discriminating between different target signatures. A more useful approach to discrimination is to quantify these differences. The next phase of this investigation will look at different quantitative features as potential discriminants.

A study was conducted for developing an automatic sub-pixel matching methodology and applying on the imageries of one of the high-resolution SAR satellites, TerraSAR-X. The results indicated the accuracy of about 0.2 m in X direction, and better than 0.1 m in Y direction by comparing with the referenced GNSS observation data. This study was aimed to show the accuracy and feature of the displacement depending on the land cover types of the objects of the selected matching points using the three pairs of TerraSAR-X images of Tohoku region acquired pre- and post-earthquake in 2011. The developed methodology is focused on the spatial texture around the point, and there is some possibility that different kinds of objects except man-made buildings are utilized to calculate the displacement. Selected point of each sub-area was classified into several objects firstly, and the correlation coefficient and the amplitude for the selected points were analyzed subsequently. Finally the statistical analysis was conducted, and showed the errors of the displacement quantitatively for each object. This paper describes the knowledge for the applied methodology to highresolution SAR satellite imageries in detail, and also implies the key points for the improvement.

We present an investigation of surface deformation using Differential SAR Interferometry (DInSAR) time-series carried out in an active open pit iron mine, the N5W, located in the Carajás Mineral Province (Brazilian Amazon region), using 33 TerraSAR-X (TSX-1) scenes. This mine has presented a historical of instability and surface monitoring measurements over sectors of the mine (pit walls) have been done based on ground based radar. Two complementary approaches were used: the standard DInSAR configuration, as an early warning of the slope instability conditions, and the DInSAR timeseries analysis. In order to decrease the topographic phase error a high resolution DEM was generated based on a stereo GeoEye-1 pair. Despite the fact that a DinSAR contains atmospheric and topographic phase artifacts and noise, it was possible to detect deformation in some interferometric pairs, covering pit benches, road ramps and waste piles. The timeseries analysis was performed using the 31 interferometric pairs, which were selected based on the highest mean coherence of a stack of 107 interferograms, presenting less phase unwrapping errors. The time-series deformation was retrieved by the Least-Squares (LS) solution using an extension of the Singular Value Decomposition (SVD), with a set of additional weighted constrain on the acceleration deformation. The atmospheric phase artifacts were filtered in the space–time domain and the DEM height errors were estimated based on the normal baseline diversity. The DInSAR time-series investigation showed good results for monitoring surface displacement in the N5W mine located in a tropical rainforest environment, providing very useful information about the ground movement for alarm, planning and risk assessment.

In this paper, a novel three-dimensional imaging algorithm of downward-looking linear array SAR is presented. To improve the resolution, multiple signal classification (MUSIC) algorithm has been used. However, since the scattering centers are always correlated in real SAR system, the estimated covariance matrix becomes singular. To address the problem, a three-dimensional spatial smoothing method is proposed in this paper to restore the singular covariance matrix to a full-rank one. The three-dimensional signal matrix can be divided into a set of orthogonal three-dimensional subspaces. The main idea of the method is based on extracting the array correlation matrix as the average of all correlation matrices from the subspaces. In addition, the spectral height of the peaks contains no information with regard to the scattering intensity of the different scattering centers, thus it is difficulty to reconstruct the backscattering information. The least square strategy is used to estimate the amplitude of the scattering center in this paper. The above results of the theoretical analysis are verified by 3-D scene simulations and experiments on real data.

Synthetic aperture radar tomography (TomoSAR) is typically used to retrieve elevation, deformation, and other key information by separating scatters of the same slant range in multiple baseline SAR images. In this paper, we investigate two kinds of ambiguities for TomoSAR. Rank-1 ambiguity, as the first one we concerned, is due to the baseline distribution of the SAR image dataset which makes the steering matrix out of full rank. It will result in false alarms appearing in a permanent distance. However, an example using the TomoSAR imaging parameters shows this ambiguity makes no sense in most cases. The second ambiguity refers to the coherence of scatters contained in one pixel. In simulation experiment, the coherence will enhance the side lobes of the spectrum, even make the real peaks fused.

Ship detection is a significant application of maritime monitoring and security. To fully explore the potential of wide coverage of synthetic aperture radar (SAR) image, the ScanSAR Wide image for ship detection is investigated in this paper. The Radarsat-2 ScanSAR Wide mode image is used as the image source due to its huge coverage and constant false alarm rate (CFAR) with Gamma distribution is selected as the core detector. Two problems of ScanSAR ship detection, the unbalanced phenomenon and false alarms of islands, are investigated and solved by a compensation step and Hessian matrix respectively. For more aspects, the detector also concerns the polarization channel selection and distribution fitting. Finally, a whole flow chart of ScanSAR ship detection is presented. As test cases, the experimental image is used to show the efficiency of our method.

Excessive pumping of groundwater in the Metro Manila district, the Philippines, has occurred huge land subsidence. The purpose of this study is to investigate the distribution of spatial and temporal change on the earth surface in this area. We measured long-term ground subsidence by InSAR using JERS-1/SAR, ENVISAT/ASAR, Fine-beam, polarimetry and ScanSAR mode of ALOS/PALSAR, and TerraSAR-X data. As a result, we detected apparent subsidence and uplift patterns at eight locations. They have been found to correlate with up-down motion of groundwater level. The largest amount of ground subsidence was measured approximately 600 mm over 6 years (100mm/year).

In studying image formation methods of the spaceborne synthetic aperture radar (SAR), we utilize its modeling and simulation (M&S) to generate its realistic simulated rawdata. Especially, for the spaceborne spotlight SAR, we perform M&S that reflects its real characteristics, and get rawdata that are almost identical to one acquired by the real SAR sensor. Particularly, operations of the spaceborne spotlight SAR are simulated based on models of its dynamics and geometry related to timeline, orbital state vector, antenna beam pattern, azimuth beam steering, and etc. In addition, the target observation of it is modeled as evaluating observation angles related to point targets within the acquisition time. Finally, based on the received echo signal model, rawdata are simulated for point targets taking into account its real operation. For the high resolution SAR image formation, simulated rawdata are focused with the extended chirp scaling algorithm. Especially, its range cell migration (RCM) factor is the key one for the exact range cell migration correction. In order to do it accurately, the Doppler frequency and the effective velocity have to be calculated correctly for all range sample bins. For precise processing, we suggest the method to analyze them using orbital state vectors and scene coordinates based on two way slant range model. In experiments, system parameters and imaging scenarios to simulate rawdata acquisition of the spaceborne spotlight SAR system are defined. The processing results for realistic simulated rawdata of it are presented to evaluate the performance and the effectiveness of proposed methods. Its results show that suggested methods are applicable to form the high resolution spaceborne spotlight SAR image.

The frequency and impact of natural disasters worldwide is constantly highlighting the need for quick and appropriate decisions from civil protection, always supported by the increasing availability of higher resolution, better accuracy, better revisit and response time data. With COSMO-SkyMed Italy has offered, and still offers today, an efficient response to actual needs of environment management during a high number of real emergency events, such as earthquakes. COSMO-SkyMed (Constellation of Small Satellites for Mediterranean basin observation) is the largest investment of the Italian Space Agency (ASI) for Earth Observation (EO), completely commissioned and funded by the Italian Ministry of Research and the Ministry of Defense. It is a Dual-Use (Civilian and Defense) system aimed at establishing a global service supplying provision of data and services relevant to a wide range of applications, such as Risk and Emergency Management. The COSMO-SkyMed constellation is providing a significant contribution to Emergency Management providing timely and accurate radar images used in a wide variety of applications such as earthquake damage assessment. In this paper the analysis related to the application of COSMO-SkyMed data supporting emergency response operations in case of earthquakes as well as the description of some real use cases occurred in the last years will be presented.

The continuous monitoring of ground deformation and structural movement has become an important task in engineering. MetaSensing introduces a novel sensor system, the Fast Ground Based Synthetic Aperture Radar (FastGBSAR), based on innovative technologies that have already been successfully applied to airborne SAR applications. The FastGBSAR allows the remote sensing of deformations of a slope or infrastructure from up to a distance of 4 km. The FastGBSAR can be setup in two different configurations: in Real Aperture Radar (RAR) mode it is capable of accurately measuring displacements along a linear range profile, ideal for monitoring vibrations of structures like bridges and towers (displacement accuracy up to 0.01 mm). Modal parameters can be determined within half an hour. Alternatively, in Synthetic Aperture Radar (SAR) configuration it produces two-dimensional displacement images with an acquisition time of less than 5 seconds, ideal for monitoring areal structures like dams, landslides and open pit mines (displacement accuracy up to 0.1 mm). The MetaSensing FastGBSAR is the first ground based SAR instrument on the market able to produce two-dimensional deformation maps with this high acquisition rate. By that, deformation time series with a high temporal and spatial resolution can be generated, giving detailed information useful to determine the deformation mechanisms involved and eventually to predict an incoming failure. The system is fully portable and can be quickly installed on bedrock or a basement. The data acquisition and processing can be fully automated leading to a low effort in instrument operation and maintenance. Due to the short acquisition time of FastGBSAR, the coherence between two acquisitions is very high and the phase unwrapping is simplified enormously. This yields a high density of resolution cells with good quality and high reliability of the acquired deformations. The deformation maps can directly be used as input into an Early Warning system, to determine the state and danger of a slope or structure. In this paper, the technical principles of the instrument are described and case studies of different monitoring tasks are presented.

Remote sensing is one of the most important tools for monitoring and assisting to estimate and predict Water Quality parameters (WQPs). The traditional methods used for monitoring pollutants are generally relied on optical images. In this paper, we present a new approach based on the Synthetic Aperture Radar (SAR) images which we used to map the region of interest and to estimate the WQPs. To achieve this estimation quality, the texture analysis is exploited to improve the regression models. These models are established and developed to estimate six common concerned water quality parameters from texture parameters extracted from Terra SAR-X data. In this purpose, the Gray Level Cooccurrence Matrix (GLCM) is used to estimate several regression models using six texture parameters such as contrast, correlation, energy, homogeneity, entropy and variance. For each predicted model, an accuracy value is computed from the probability value given by the regression analysis model of each parameter. In order to validate our approach, we have used tow dataset of water region for training and test process. To evaluate and validate the proposed model, we applied it on the training set. In the last stage, we used the fuzzy K-means clustering to generalize the water quality estimation on the whole of water region extracted from segmented Terra SAR-X image. Also, the obtained results showed that there are a good statistical correlation between the in situ water quality and Terra SAR-X data, and also demonstrated that the characteristics obtained by texture analysis are able to monitor and predicate the distribution of WQPs in large rivers with high accuracy.

The problems of simulation of bistatic SAR raw data and focusing are studied. A discrete target simulator is described. The simulator introduces the scene topography and compute the integration time of general bistatic configurations providing a means to derived maps of the range and azimuth spatial resolutions. The problem of focusing of bistatic SAR data acquired in a translational-invariant bistatic configuration is studied by deriving the bistatic Point Target Reference spectrum and presenting an analytical solution for its stationary points.

In the context of recent advances in InSAR processing techniques to retrieve higher persistent scatterer and coherent target densities over unfavourable land cover classes, this study tests the Intermittent Small Baseline Subset (ISBAS) approach to update the landslide inventory around the town of Piana degli Albanesi (Italy), an area where only 2% of the land appears suitable to generate radar scatterers based on a pre-survey feasibility assessment. ISBAS processing of 38 ascending mode and 36 descending mode COSMO-SkyMed StripMap HIMAGE SAR scenes at 3m resolution allows identification of ~726,000 and ~893,000 coherent and intermittently coherent pixels for the ascending and descending data stacks respectively. Observed improvements in the number of ISBAS solutions for the ascending mode are greater than 40 times compared to the conventional SBAS approach, not only for urban and rocky terrains, but also rural and vegetated land covers. Line of sight ground motion rates range between -6.4 and +5.5 mm/yr in 2008-2011, although the majority of the processed area shows general stability, with average rates of -0.6 mm/yr in the ascending and -0.1 mm/yr in the descending mode results. Interpretation of the ISBAS deformation rates, integrated with targeted field surveys and aerial photo-interpretation, provides a new and more complete picture of landslide distribution, state of activity and intensity in the test area, and allows depiction of very slow and extremely slow landslide processes even in areas difficult to access, with unprecedented coverage of results.

The availability of the data provided by present and future constellations of Synthetic Aperture Radar (SAR) sensors and the development of reliable flood mapping algorithms allows producing frequent flood maps characterized by high spatial resolution. Progresses have been also achieved in flood modeling, so that a joint use of SAR-derived and modelderived inundation maps seems to be very promising. This paper presents the major outcomes of a combined use of a multi-temporal series of COSMO-SkyMed observations and of a hydrodynamic model, accomplished within the framework of an activity aiming at the interpretation of the dynamics of the flood that hit Albania in January 2010. By calibrating the model with the COSMO-SkyMed derived maps, a number of products such as water depths, and flow directions were generated. Results show a good agreement between SAR-derived and model-derived flood extents. Moreover, the maximum water depths were found in the areas where floodwater was present for the longest period of time, according to COSMO-SkyMed observations.