Towards a 20 m Global Building Map from Sentinel-1 SAR Data

This study introduces a technique for automatically mapping built-up areas using synthetic aperture radar (SAR) backscattering intensity and interferometric multi-temporal coherence generated from Sentinel-1 data in the framework of the Copernicus program. The underlying hypothesis is that, in SAR images, built-up areas exhibit very high backscattering values that are coherent in time. Several particular characteristics of the Sentinel-1 satellite mission are put to good use, such as its high revisit time, the availability of dual-polarized data, and its small orbital tube. The newly developed algorithm is based on an adaptive parametric thresholding that first identifies pixels with high backscattering values in both VV and VH polarimetric channels. The interferometric SAR coherence is then used to reduce false alarms. These are caused by land cover classes (other than buildings) that are characterized by high backscattering values that are not coherent in time (e.g., certain types of vegetated areas). The algorithm was tested on Sentinel-1 Interferometric Wide Swath data from five different test sites located in semiarid and arid regions in the Mediterranean region and Northern Africa. The resulting building maps were compared with the Global Urban Footprint (GUF) derived from the TerraSAR-X mission data and, on average, a 92% agreement was obtained.

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Realizing Target Detection in SAR Images Based on Multiscale Superpixel Fusion

Sensors ◽

10.3390/s21051643 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1643

Author(s):

Ming Liu ◽

Shichao Chen ◽

Fugang Lu ◽

Mengdao Xing ◽

Jingbiao Wei

Keyword(s):

Synthetic Aperture Radar ◽

False Alarm ◽

False Alarm Rate ◽

Target Detection ◽

Synthetic Aperture ◽

False Alarms ◽

Sar Image ◽

Constant False Alarm Rate ◽

Sar Images ◽

Complex Scenes

For target detection in complex scenes of synthetic aperture radar (SAR) images, the false alarms in the land areas are hard to eliminate, especially for the ones near the coastline. Focusing on the problem, an algorithm based on the fusion of multiscale superpixel segmentations is proposed in this paper. Firstly, the SAR images are partitioned by using different scales of superpixel segmentation. For the superpixels in each scale, the land-sea segmentation is achieved by judging their statistical properties. Then, the land-sea segmentation results obtained in each scale are combined with the result of the constant false alarm rate (CFAR) detector to eliminate the false alarms located on the land areas of the SAR image. In the end, to enhance the robustness of the proposed algorithm, the detection results obtained in different scales are fused together to realize the final target detection. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

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A Novel Orthogonal Waveform Separation Scheme for Airborne MIMO-SAR Systems

Sensors ◽

10.3390/s18103580 ◽

2018 ◽

Vol 18 (10) ◽

pp. 3580 ◽

Cited By ~ 1

Author(s):

Jie Wang ◽

Ke-Hong Zhu ◽

Li-Na Wang ◽

Xing-Dong Liang ◽

Long-Yong Chen

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Synthetic Aperture Radar ◽

3D Imaging ◽

Synthetic Aperture ◽

Separation Scheme ◽

Sar Images ◽

Wide Swath ◽

Aperture Radar

In recent years, multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems, which can promote the performance of 3D imaging, high-resolution wide-swath remote sensing, and multi-baseline interferometry, have received considerable attention. Several papers on MIMO-SAR have been published, but the research of such systems is seriously limited. This is mainly because the superposed echoes of the multiple transmitted orthogonal waveforms cannot be separated perfectly. The imperfect separation will introduce ambiguous energy and degrade SAR images dramatically. In this paper, a novel orthogonal waveform separation scheme based on echo-compression is proposed for airborne MIMO-SAR systems. Specifically, apart from the simultaneous transmissions, the transmitters are required to radiate several times alone in a synthetic aperture to sense their private inner-aperture channels. Since the channel responses at the neighboring azimuth positions are relevant, the energy of the solely radiated orthogonal waveforms in the superposed echoes will be concentrated. To this end, the echoes of the multiple transmitted orthogonal waveforms can be separated by cancelling the peaks. In addition, the cleaned echoes, along with original superposed one, can be used to reconstruct the unambiguous echoes. The proposed scheme is validated by simulations.

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Automatic Detection of Small Icebergs in Fast Ice Using Satellite Wide-Swath SAR Images

Remote Sensing ◽

10.3390/rs11070806 ◽

2019 ◽

Vol 11 (7) ◽

pp. 806 ◽

Cited By ~ 4

Author(s):

Ingri Soldal ◽

Wolfgang Dierking ◽

Anton Korosov ◽

Armando Marino

Keyword(s):

Spatial Resolution ◽

Barents Sea ◽

Computation Time ◽

Automatic Detection ◽

False Alarms ◽

Constant False Alarm Rate ◽

Sar Images ◽

Detection Scheme ◽

Fast Ice ◽

Wide Swath

Automatic detection of icebergs in satellite images is regarded a useful tool to provide information necessary for safety in Arctic shipping or operations over large ocean areas in near-real time. In this work, we investigated the feasibility of automatic iceberg detection in Sentinel-1 Extra Wide Swath (EWS) SAR images which follow the preferred image mode in operational ice charting. As test region, we selected the Barents Sea where the size of many icebergs is on the order of the spatial resolution of the EWS-mode. We tested a new approach for a detection scheme. It is based on a combination of a filter for enhancing the contrast between icebergs and background, subsequent blob detection, and final application of a Constant False Alarm Rate (CFAR) algorithm. The filter relies mainly on the HV-polarized intensity which often reveals a larger difference between icebergs and sea ice or open water. The blob detector identifies locations of potential icebergs and thus shortens computation time. The final detection is performed on the identified blobs using the CFAR algorithm. About 2000 icebergs captured in fast ice were visually identified in Sentinel-2 Multi Spectral Imager (MSI) data and exploited for an assessment of the detection scheme performance using confusion matrices. For our performance tests, we used four Sentinel-1 EWS images. For judging the effect of spatial resolution, we carried out an additional test with one Sentinel-1 Interferometric Wide Swath (IWS) mode image. Our results show that only 8–22 percent of the icebergs could be detected in the EWS images, and over 90 percent of all detections were false alarms. In IWS mode, the number of correctly identified icebergs increased to 38 percent. However, we obtained a larger number of false alarms in the IWS image than in the corresponding EWS image. We identified two problems for iceberg detection: 1) with the given frequency–polarization combination, not all icebergs are strong scatterers at HV-polarization, and (2) icebergs and deformation structures present on fast ice can often not be distinguished since both may reveal equally strong responses at HV-polarization.

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Patterns of wind-drifted snow on the Alaskan arctic slope, detected with ERS-1 interferometric SAR

Journal of Glaciology ◽

10.3189/172756502781831151 ◽

2002 ◽

Vol 48 (163) ◽

pp. 495-504 ◽

Cited By ~ 16

Author(s):

Shusun Li ◽

Matthew Sturm

Keyword(s):

Large Scale ◽

Geometric Model ◽

Synthetic Aperture ◽

Interferometric Synthetic Aperture Radar ◽

Mountain Ridge ◽

Arctic Alaska ◽

Wind Event ◽

Interferometric Sar ◽

Lateral Variations ◽

Very High

AbstractWe tested whether spaceborne interferometric synthetic aperture radar (InSAR) could be used to reveal patterns of redistribution of wind-drifted snow in arctic Alaska. Based on a simple geometric model, we found that lateral variations in new-snow (assuming a density of 0.3 g cm−3) accumulation of > 11 cm, or redistribution of the existing snow into dunes of half this height, could produce decorrelation of C-band interferograms. Comparison of interferograms with field observations for two periods from winter 1993/94, one with wind but little new snow, and the second with wind and new snow, indicates the interferograms delineated areas where the snow depth had changed due to drifting. Striking patterns of windward scouring and leeward deposition were revealed. The interferograms also showed that during one high-wind event, conspicuous interferometric bands a few kilometers wide and 30 km long were formed downwind of a mountain ridge. We speculate that these bands were caused by large-scale alterations in the concentrations of moving snow particles, a finding consistent with ground observations of alternating bands of clear air and blizzard for the same area and similar to phenomena observed with the Advanced Very High Resolution Radiometer and the Geodetic Earth Observing Satellite during blizzards in North Dakota and Iowa, U.S.A.

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The Evolution of Wide-Area DInSAR: From Regional and National Services to the European Ground Motion Service

Remote Sensing ◽

10.3390/rs12122043 ◽

2020 ◽

Vol 12 (12) ◽

pp. 2043 ◽

Cited By ~ 3

Author(s):

Michele Crosetto ◽

Lorenzo Solari ◽

Marek Mróz ◽

Joanna Balasis-Levinsen ◽

Nicola Casagli ◽

...

Keyword(s):

Synthetic Aperture Radar ◽

Ground Motion ◽

Deformation Monitoring ◽

Synthetic Aperture ◽

Wide Area ◽

Sar Images ◽

Technical Aspects ◽

Large Sets ◽

Interferometric Sar ◽

Monitoring Service

This study is focused on wide-area deformation monitoring initiatives based on the differential interferometric SAR technique (DInSAR). In particular, it addresses the use of advanced DInSAR (A-DInSAR) techniques, which are based on large sets of synthetic aperture radar (SAR) and Copernicus Sentinel-1 images. Such techniques have undergone a dramatic development in the last twenty years: they are now capable to process big sets of SAR images and can be exploited to realize a wide-area A-DInSAR monitoring. The study describes several initiatives to establish wide-area ground motion services (GMS), both at county- and region-level. In the second part of the study, some of the key technical aspects related to wide-area A-DInSAR monitoring are discussed. Finally, the last part of the study is devoted to the European ground motion service (EGMS), which is part of the Copernicus land monitoring service. It represents the most important wide-area A-DInSAR deformation monitoring system ever developed. The study describes its main characteristics and its main products. The end of the production of the first EGMS baseline product is foreseen for the last quarter of 2021.

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Deceptive Targets Generation Simulation Against Multichannel SAR

Electronics ◽

10.3390/electronics9040597 ◽

2020 ◽

Vol 9 (4) ◽

pp. 597

Author(s):

Penghui Ji ◽

Shiqi Xing ◽

Dahai Dai ◽

Bo Pang

Keyword(s):

Synthetic Aperture ◽

Minimum Condition ◽

Complex Coefficient ◽

Sar Images ◽

Digital Elevation ◽

Deceptive Jamming ◽

Elevation Model ◽

Interferometric Sar ◽

General Architecture ◽

Ground Moving Target Indication

Traditional synthetic aperture radar (SAR) deceptive jamming can effectively generate deceptive scenes or false targets in SAR images. However, these false targets or scenes can be easily distinguished or eliminated by the multichannel SAR system. To interfere with the multichannel SAR, we first analyzed the results of SAR deceptive jamming generated by one transponder and two transponders against three-channel SAR- ground moving target indication (GMTI). Then, we propose a new deceptive jamming method against three-channel SAR-GMTI by using three synergetic transponders. By modulating each transponder with a complex coefficient, three synergetic transponders can generate false moving targets with the controllable radial velocity and located azimuth position in three-channel SAR-GMTI. Besides, in this paper, we also introduce an algorithm to deploy three transponders reasonably by utilizing the minimum condition number. In the end, a general architecture of multiple transponders deceiving multichannel SAR is given. The proposed method can not only generate deceptive false targets against multichannel SAR-GMTI, but also guide the production of a deceptive digital elevation model (DEM) against multichannel interferometric SAR (InSAR). Simulations verify the effectiveness of the proposed method.

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Incidence angle normalization of Wide Swath SAR data for oceanographic applications

Open Geosciences ◽

10.1515/geo-2016-0029 ◽

2016 ◽

Vol 8 (1) ◽

Cited By ~ 20

Author(s):

Konstantinos Topouzelis ◽

Suman Singha ◽

Dimitra Kitsiou

Keyword(s):

Synthetic Aperture Radar ◽

Cross Section ◽

Incidence Angle ◽

Radar Cross Section ◽

Sea Surface ◽

Synthetic Aperture ◽

Progressive Reduction ◽

Sar Images ◽

Wide Swath

AbstractA backscattering trend in the range direction of the signal received by Synthetic Aperture Radar (SAR) in Wide Swath (WS) mode results in a progressive reduction of brightness over images from near to far range, which affects the detection and classification of sea surface features on wide swath SAR images. The aim of the present paper is to investigate methods for limiting the issue of Normalized Radar Cross-Section (NRCS or

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A Sensitivity Analysis on the Spectral Signatures of Low-Backscattering Sea Areas in Sentinel-1 SAR Images

Remote Sensing ◽

10.3390/rs13061183 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1183 ◽

Cited By ~ 1

Author(s):

Valeria Corcione ◽

Andrea Buono ◽

Ferdinando Nunziata ◽

Maurizio Migliaccio

Keyword(s):

Oil Pollution ◽

Sea Surface ◽

Synthetic Aperture ◽

Sar Images ◽

Spectral Signatures ◽

Objective Metrics ◽

Wide Range ◽

Imaging Mode ◽

Physical Phenomena ◽

Wide Swath

Satellite synthetic aperture radar (SAR) is a unique tool to collect measurements over sea surface but the physical interpretation of such data is not always straightforward. Among the different sea targets of interest, low-backscattering areas are often associated to marine oil pollution even if several physical phenomena may also result in low-backscattering patches at sea. In this study, the effects of low-backscattering areas of anthropogenic and natural origin on the azimuth autocorrelation function (AACF) are analyzed using VV-polarized SAR measurements. Two objective metrics are introduced to quantify the deviation of the AACF evaluated over low-backscattering areas with reference to slick-free sea surface. Experiments, undertaken on six Sentinel-1 SAR scenes, collected in Interferometric Wide Swath VV+VH imaging mode over large low-backscattering areas of different origin under low-to-moderate wind conditions (speed ≤ 7 m/s), spanning a wide range of incidence angles (from about 30° up to 46°), demonstrated that the AACF evaluated within low-backscattering sea areas remarkably deviates from the slick-free sea surface one and the largest deviation is observed over oil slicks.

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Joint Sparsity for TomoSAR Imaging in Urban Areas Using Building POI and TerraSAR-X Staring Spotlight Data

Sensors ◽

10.3390/s21206888 ◽

2021 ◽

Vol 21 (20) ◽

pp. 6888

Author(s):

Lei Pang ◽

Yanfeng Gai ◽

Tian Zhang

Keyword(s):

Urban Areas ◽

Super Resolution ◽

Likelihood Estimation ◽

Satellite Orbit ◽

Synthetic Aperture ◽

Estimation Methods ◽

Spectrum Estimation ◽

Sar Images ◽

Dense Point ◽

Very High

Synthetic aperture radar (SAR) tomography (TomoSAR) can obtain 3D imaging models of observed urban areas and can also discriminate different scatters in an azimuth–range pixel unit. Recently, compressive sensing (CS) has been applied to TomoSAR imaging with the use of very-high-resolution (VHR) SAR images delivered by modern SAR systems, such as TerraSAR-X and TanDEM-X. Compared with the traditional Fourier transform and spectrum estimation methods, using sparse information for TomoSAR imaging can obtain super-resolution power and robustness and is only minorly impacted by the sidelobe effect. However, due to the tight control of SAR satellite orbit, the number of acquisitions is usually too low to form a synthetic aperture in the elevation direction, and the baseline distribution of acquisitions is also uneven. In addition, artificial outliers may easily be generated in later TomoSAR processing, leading to a poor mapping product. Focusing on these problems, by synthesizing the opinions of various experts and scholarly works, this paper briefly reviews the research status of sparse TomoSAR imaging. Then, a joint sparse imaging algorithm, based on the building points of interest (POIs) and maximum likelihood estimation, is proposed to reduce the number of acquisitions required and reject the scatterer outliers. Moreover, we adopted the proposed novel workflow in the TerraSAR-X datasets in staring spotlight (ST) work mode. The experiments on simulation data and TerraSAR-X data stacks not only indicated the effectiveness of the proposed approach, but also proved the great potential of producing a high-precision dense point cloud from staring spotlight (ST) data.

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Multi-Temporal Small Baseline Interferometric SAR Algorithms: Error Budget and Theoretical Performance

Remote Sensing ◽

10.3390/rs13040557 ◽

2021 ◽

Vol 13 (4) ◽

pp. 557

Author(s):

Antonio Pepe

Keyword(s):

Synthetic Aperture Radar ◽

Phase Unwrapping ◽

Synthetic Aperture ◽

Interferometric Synthetic Aperture Radar ◽

Error Budget ◽

Multi Temporal ◽

Small Baseline ◽

Time Inconsistent ◽

Interferometric Sar ◽

Aperture Radar

Multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques are well recognized as useful tools for detecting and monitoring Earth’s surface temporal changes. In this work, the fundamentals of error noise propagation and perturbation theories are applied to derive the ground displacement products’ theoretical error bounds of the small baseline (SB) differential interferometric synthetic aperture radar algorithms. A general formulation of the least-squares (LS) optimization problem, representing the SB methods implementation’s core, was adopted in this research study. A particular emphasis was placed on the effects of time-uncorrelated phase unwrapping mistakes and time-inconsistent phase disturbances in sets of SB interferograms, leading to artefacts in the attainable InSAR products. Moreover, this study created the theoretical basis for further developments aimed at quantifying the error budget of the time-uncorrelated phase unwrapping mistakes and studying time-inconsistent phase artefacts for the generation of InSAR data products. Some experiments, performed by considering a sequence of synthetic aperture radar (SAR) images collected by the ASAR sensor onboard the ENVISAT satellite, supported the developed theoretical framework.

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