COSMO-SkyMed Synthetic Aperture Radar Data Research Articles

SAR Imaging Distortions Induced by Topography: A Compact Analytical Formulation for Radiometric Calibration

Modeling of synthetic aperture radar (SAR) imaging distortions induced by topography is addressed and a novel radiometric calibration method is proposed in this paper. An analytical formulation of the problem is primarily provided in purely geometrical terms, by adopting the theoretical notions of the differential geometry of surfaces. The novel and conceptually simple formulation relies on a cylindrical coordinate system, whose longitudinal axis corresponds to the sensor flight direction. A 3D representation of the terrain shape is then incorporated into the SAR imaging model by resorting to a suitable parametrization of the observed ground surface. Within this analytical framework, the area-stretching function quantitatively expresses in geometrical terms the inherent local radiometric distortions. This paper establishes its analytical expression in terms of the magnitude of the gradient of the look-angle function uniquely defined in the image domain, thus resulting in being mathematically concise and amenable to a straightforward implementation. The practical relevance of the formulation is also illustrated from a computational perspective, by elucidating its effective discrete implementation. In particular, an inverse cylindrical mapping approach is adopted, thus avoiding the drawback of pixel area fragmentation and integration required in forward-mapping-based approaches. The effectiveness of the proposed SAR radiometric calibration method is experimentally demonstrated by using COSMO-SkyMed SAR data acquired over a mountainous area in Italy.

Multithreading Based Parallel Processing for Image Geometric Coregistration in SAR Interferometry

Within the framework of multi-temporal Synthetic Aperture Radar (SAR) interferometric processing, image coregistration is a fundamental operation that might be extremely time-consuming. This paper explores the possibility of addressing fast and accurate SAR image geometric coregistration, with sub-pixel accuracy and in the presence of a complex 3-D object scene, by exploiting the parallelism offered by shared-memory architectures. An efficient and scalable processor is proposed by designing a parallel algorithm incorporating thread-level parallelism for solving the inherent computationally intensive problem. The adopted functional scheme is first mathematically framed and then investigated in detail in terms of its computational structures. Subsequently, a parallel version of the algorithm is designed, according to a fork-join model, by suitably taking into account the granularity of the decomposition, load-balancing, and different scheduling strategies. The developed parallel algorithm implements parallelism at the thread-level by using OpenMP (Open Multi-Processing) and it is specifically targeted at shared-memory multiprocessors. The parallel performance of the implemented multithreading-based SAR image coregistration prototype processor is experimentally investigated and quantitatively assessed by processing high-resolution X-band COSMO-SkyMed SAR data and using two different multicore architectures. The effectiveness of the developed multithreaded prototype solution in fully benefitting from the computing power offered by multicore processors has successfully been demonstrated via a suitable experimental performance analysis conducted in terms of parallel speedup and efficiency. The demonstrated scalable performance and portability of the developed parallel processor confirm its potential for operational use in the interferometric SAR data processing at large scales.

Land Subsidence in Wuhan Revealed Using a Non-Linear PSInSAR Approach with Long Time Series of COSMO-SkyMed SAR Data

Wuhan is an important city in central China, with a rapid development that has led to increasingly serious land subsidence over the last decades. Most of the existing Interferometric Synthetic Aperture Radar (InSAR) subsidence monitoring studies in Wuhan are either short-term investigations—and thus can only detect this process within limited time periods—or combinations of different Synthetic Aperture Radar (SAR) datasets with temporal gaps in between. To overcome these constraints, we exploited nearly 300 high-resolution COSMO-SkyMed StripMap HIMAGE scenes acquired between 2012 and 2019 to monitor the long-term subsidence process affecting Wuhan and to reveal its spatiotemporal variations. The results from the Persistent Scatterer Interferometric SAR (PSInSAR) processing highlight several clearly observable subsidence zones. Three of them (i.e., Houhu, Xinrong, and Guanggu) are affected by serious subsidence rates and non-linear temporal behavior, and are investigated in this paper in more detail. The subsidence in Houhu is caused by soft soil consolidation and compression. Soil mechanics are therefore used to estimate when the subsidence is expected to finish and to calculate the degree of consolidation for each year. The COSMO-SkyMed PSInSAR results indicate that the area has entered the late stage of consolidation and compression and is gradually stabilizing. The subsidence curve found for the area around Xinrong shows that the construction of an underground tract of the subway Line 21 caused large-scale settlement in this area. The temporal granularity of the PSInSAR time series also allows precise detection of a rebound phase following a major flooding event in 2016. In the southern industrial park of Guanggu, newly detected subsidence was found. The combination of the subsidence curve with an optical time-series image analysis indicates that urban construction is the main trigger of deformation in this area. While this study unveils previously unknown characters of land subsidence in Wuhan and clarifies the relationship with the urban causative factors, it also proves the benefits of non-linear PSInSAR in the analysis of the temporal evolution of such processes in dynamic and expanding cities.

Satellite X-band SAR data exploitation trends in the framework of ASI’s COSMO-SkyMed Open Call initiative

Abstract COSMO-SkyMed (Constellation of Small satellites for Mediterranean basin Observation) is an Italian Earth Observation (EO) and Dual-Use (Civilian and Defense) Space System conceived with the aim to establish a worldwide service providing Synthetic Aperture Radar (SAR) data, products and services compliant with well-established international standards and relevant to a wide range of applications, such as emergency and risk management, scientific and commercial applications and defense Applications. Starting from 2007, the Italian Space Agency (ASI) has promoted the COSMO-SkyMed SAR data exploitation through several initiatives such as “Announcement of Opportunity”, “Open Call for Science” and “Open Call for National Small and Medium Enterprises (SMEs)”. This paper is focused on the trends and results observed in the context of the “Open Call for Science”, an initiative completely addressed to the national and international scientific community since 2015. In particular, in this framework, the observed trend and advances in science and applications of SAR imagery and Interferometric SAR (InSAR) are summarized and assessed, also in light of the scientific evidence published in the recent literature by scientific users of ASI’s “Open Call for Science”.

Mapping impact of urbanization in Shahat-Cyrene (Libya) using a big SAR data approach of change detection with COSMO-SkyMed time series

Uncontrolled and unregulated urbanization around the modern town of Shahat, Libya, has been reported by several studies as a pressing issue for the conservation of archaeological heritage in the cultural landscape south of Cyrene UNESCO World Heritage Site (WHS). In this paper, we implemented a big Synthetic Aperture Radar (SAR) data analysis approach on a selection of more than 180 StripMap images that the Italian Space Agency (ASI)’s COSMO-SkyMed constellation has consistently collected at 3-m resolution over Cyrene since 2011, as part of its background acquisition scenario. We prove the accuracy of the method to map the spatial and temporal spread of new building and road blocks using COSMO-SkyMed SAR data, and its complementarity with the mapping based on the full archive of cloud-free Copernicus Sentinel-2 multi-spectral imagery at 10-m resolution (2015-2017). Owing to the higher spatial resolution and half-month frequency of observation of COSMO-SkyMed, we better delineated the new urban features and estimated more precisely when these were developed across the landscape.

Micro-Motion Estimation of Maritime Targets Using Pixel Tracking in Cosmo-Skymed Synthetic Aperture Radar Data—An Operative Assessment

In this paper, we propose a novel strategy to estimate the micro-motion (m-m) of ships from synthetic aperture radar (SAR) images. To this end, observe that the problem of motion and m-m detection of targets is usually solved using synthetic aperture radar (SAR) along-track interferometry through two radars spatially separated by a baseline along the azimuth direction. The approach proposed in this paper for m-m estimation of ships, occupying thousands of pixels, processes the information generated during the coregistration of several re-synthesized time-domain and not overlapped Doppler sub-apertures. Specifically, the SAR products are generated by splitting the raw data according to a temporally small baseline using one single wide-band staring spotlight (ST) SAR image. The predominant vibrational modes of different ships are then estimated. The performance analysis is conducted on one ST SAR image recorded by COSMO-SkyMed satellite system. Finally, the newly proposed approach paves the way for application to the surveillance of land-based industry activities.

COSMO–SkyMed Synthetic Aperture Radar Data to Observe the Deepwater Horizon Oil Spill

Oil spills are adverse events that may be very harmful to ecosystems and the food chain. In particular, large sea oil spills are very dramatic occurrences that may affect sea and coastal areas. Hence, the sustainability of oil rig infrastructures and oil transportation via oil tankers is linked to law enforcement based on proper monitoring techniques, which are also fundamental to mitigate the impact of such pollution. In this study, a showcase referring to the Deepwater Horizon (DWH) oil incident, one of the world’s largest incidental oil pollution event that occurred in the Gulf of Mexico in 2010 affecting a sea area larger than 10,000 km 2 , is analyzed using remotely-sensed information collected by Synthetic Aperture Radar (SAR). Although, operationally, SAR sea oil slick observation is typically accomplished using C-band VV-polarized SAR imagery, during the DWH oil incident, because of their very dense revisit time, even single-polarization X-band COSMO-SkyMed (CSK) SAR measurements were collected. In this study, we exploit, for the first time, incoherent dual co-polarization SAR data collected by the Italian CSK X-band SAR constellation showing the key benefits of HH-VV SAR measurements in observing such a huge oil pollution event, especially in terms of the very dense revisit time offered by the CSK constellation.

Radargrammetric approaches to the flat relief of the amazon coast using COSMO-SkyMed and TerraSAR-X datasets

The Amazonian coast consists of extensive flood plains and plateaus characterized by a high discharge of water and sediment from the Amazon River. This wide landscape occurs under a tropical climate with heavy rains and high cloud cover, making it unsuitable for conventional mapping based on optical images. Additionally, the flat relief and vegetation structure of the Brazilian Amazon coast define an incoherent to partially coherent behavior for the microwave signal, rendering radargrammetric models more suitable for the three-dimensional mapping of its surface. This study aimed to assess the digital surface models (DSMs) provided by Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) Stripmap datasets throughout the radargrammetric models from SARscape and Toutin. The DSMs were generated from SAR (synthetic aperture radar) data with an acquisition geometry that addressed the need for a compromise between the intersection angles and low temporal decorrelation. The radargrammetric SARscape and Toutin’s models were developed from different amounts of stereo ground control points (SGCP). The generated DSMs were evaluated considering a set of 40 independent checkpoints (ICP) measured by GNSS in the field, in their entirety and disaggregated by coastal environment. The vertical accuracy was based on the estimation of the discrepancies, bias and precision (standard deviation and root mean square error – RMSE), and the Taylor and Target diagrams were used for a more comprehensive comparison. In the vertical accuracy analysis using all ICPs measured in situ, the DSM obtained by the SARscape’s model from the CSK SAR data resulted in the lowest RMSE (4.34 m) and mean discrepancy (0.05 m), but Toutin’s model had the lowest standard deviation (2.58 m) of the discrepancies. The Taylor and Target diagrams showed fluctuations in accuracy that alternated the DSMs generated from the two types of SAR data, indicating that TSX produced more stable models and CSK produced better vertical accuracy. The Amazon Coastal Plateau and Fluvial Marine Terrace environments defined three-dimensional representations with lower RMSEs (better than 7.8 and 8.9 m, respectively), regardless of the type of SAR data or the radargrammetric model used. The worst performance, which was for the Fluvial Marine Plain, was influenced by the specific characteristics of this coastal environment, such as the structure of the mangrove vegetation and the shoreline. In general, the high resolution and good ability to revisit the SAR data used, together with the radargrammetric models, allowed for the accurate mapping of the flat relief of the Amazon coastal environments, providing detailed spatial information that can be acquired in severe rainfall conditions in a region of intense morphological dynamics.

The use of COSMO-SkyMed© SAR data for coastal management

In this paper, high spatial resolution wind fields retrieved by the synthetic aperture radar (SAR) remotely sensed images are first analyzed to force coastal wind–wave oceanographic models. A very effective technique is here proposed to retrieve wind field by SAR images collected by the Italian Cosmo-SkyMed (CSK) constellation. The technique is first calibrated using a large data set of CSK SAR data and then applied to a meaningful set of CSK SAR data collected during three storms occurred in the Southern Thyrrenian Sea area during the winter season of 2010. CSK SAR winds are used to force SWAN wave numerical simulations to retrieve meaningful wave parameters (e.g., significant wave height, wave directions and periods) as physical descriptors of storm events. Experimental results, undertaken using both CSK and conventional ECMWF wind forcing, buoys and scatterometer winds, demonstrate that CSK winds can be successfully used to predict wave parameters during storm events. The best results are obtained when CSK winds are merged with ECMWF ones to generate a new “blended” wind product.

Performance Analysis and Validation of Waterline Extraction Approaches Using Single- and Dual-Polarimetric SAR Data

In this study, the performance of two waterline extraction approaches is analyzed using dual-polarization Cosmo-SkyMed (CSK) Synthetic Aperture Radar (SAR) data and ancillary ground truth information. The single-polarization approach is based on multiscale normalized cuts segmentation; while, the dual-polarization one exploits the inherent peculiarities of the CSK PING PONG incoherent dual-polarimetric imaging mode together with a tailored scattering model to perform land/sea discrimination. The two approaches are applied to the actual CSK SAR data collected over the coastal area of Shanghai, China. To provide a detailed and complete validation of the two approaches, we carried out several field surveys collecting in situ ancillary information including Global Positioning System (GPS) data and tidal information. Experimental results show that 1) both approaches provide satisfactory results in extracting waterline from CSK SAR data in the intertidal flat under low-to-moderate wind conditions and under a very broad range of incidence angles; 2) the accuracy of the waterline extracted by both approaches decreases in case of water within the intertidal flat; 3) the single-polarization approach is unsupervised when the land/sea contrast ratio is high. However, it needs manual supervision to correct the extracted waterline when the land/sea contrast is low or in complex areas. A typical CSK scene is processed in about 25 min; 4) the dual-polarization approach is unsupervised and very effective: a typical CSK SAR scene is processed in seconds.

A Multipolarization Analysis of Coastline Extraction Using X-Band COSMO-SkyMed SAR Data

In this study, COSMO-SkyMed (CSK) Synthetic Aperture Radar (SAR) data, collected by the single-polarization stripmap Himage mode, are exploited for coastline extraction purposes. First, a multipolarization analysis of sea surface backscattering is undertaken using the Improved Integral Equation Method (IIEM). Then, a simple two-step approach is proposed to extract the continuous coastline from co- and cross-polarized Himage CSK SAR data. The approach is framed into two steps: 1) obtaining a binary output from the SAR image using a global threshold Constant False Alarm Rate (CFAR) detector; and 2) extracting the continuous one-pixel coastline from the binary output with a conventional Sobel edge detector. The proposed approach is verified against actual CSK SAR data and it is shown to be both effective and accurate when low-to-moderate wind conditions apply.

Sea wave numerical simulations with COSMO-SkyMed© SAR data

ABSTRACT Benassai G, Migliaccio M., Montuori A., 2013. Sea wave numerical simulations with Cosmo-SkyMed SAR data. In this paper, X-band COSMO-SkyMed© Synthetic Aperture Radar (SAR) data are first experimented as wind field forcing of coastal wind-wave oceanographic modeling for sea-wave numerical simulation. The SWAN wave numerical simulations run with Cosmo-SkyMed SAR wind data were performed with respect to some relevant wave storms in the Southern Thyrrenian Sea area during the winter season of 2010. The wind forcing is provided by X-band COSMO-SkyMed© SAR-based wind field estimations which are properly blended with both buoys wave data and ECMWF model winds to retrieve meaningful wave parameters (e.g. significant wave height, wave directions and periods) as physical descriptors of storm events. Experimental results accomplished with X-band COSMO-SkyMed© SAR-based wind field forcing are successfully compared with the ones gathered by using both buoys wave field data and ECMWF model winds, only. The res...

Single-Look Complex COSMO-SkyMed SAR Data to Observe Metallic Targets at Sea

In this paper, a physically based approach, which takes full benefits of speckle noise as source of information, is first applied over X-band full-resolution single-look complex slant (SCS) COSMO-SkyMed synthetic aperture radar (SAR) data to observe metallic targets at sea. A constant false alarm rate (CFAR) filter based on the coherent-to-incoherent field ratio is developed, which: 1) is very effective in terms of processing time, 2) is able to provide logical true-and-false outputs characterized by a very low false alarm rate; and 3) can operate in a wide range of incidence angles. Experimental results, obtained by processing a wide data set of full-resolution SCS X-band COSMO-SkyMed SAR data, show the effectiveness of the proposed approach. Part of this data set regards the challenging operational case related to the Air France Flight 447 accident occurred on June 1, 2009, off the Brazilian coasts. It is shown how COSMO-SkyMed SAR data can assist the search of aircraft debris at sea. Moreover, the proposed approach is of great applicative relevance even because of the high revisit time of COSMO-SkyMed constellation.

Earthquake Damage Assessment of Buildings Using VHR Optical and SAR Imagery

Rapid damage assessment after natural disasters (e.g., earthquakes) and violent conflicts (e.g., war-related destruction) is crucial for initiating effective emergency response actions. Remote-sensing satellites equipped with very high spatial resolution (VHR) multispectral and synthetic aperture radar (SAR) imaging sensors can provide vital information due to their ability to map the affected areas with high geometric precision and in an uncensored manner. In this paper, we present a novel method that detects buildings destroyed in an earthquake using pre-event VHR optical and post-event detected VHR SAR imagery. The method operates at the level of individual buildings and assumes that they have a rectangular footprint and are isolated. First, the 3-D parameters of a building are estimated from the pre-event optical imagery. Second, the building information and the acquisition parameters of the VHR SAR scene are used to predict the expected signature of the building in the post-event SAR scene assuming that it is not affected by the event. Third, the similarity between the predicted image and the actual SAR image is analyzed. If the similarity is high, the building is likely to be still intact, whereas a low similarity indicates that the building is destroyed. A similarity threshold is used to classify the buildings. We demonstrate the feasibility and the effectiveness of the method for a subset of the town of Yingxiu, China, which was heavily damaged in the Sichuan earthquake of May 12, 2008. For the experiment, we use QuickBird and WorldView-1 optical imagery, and TerraSAR-X and COSMO-SkyMed SAR data.