Performance Evaluation of Azimuth Offset Method for Mitigating the Ionospheric Effect on SAR Interferometry

Synthetic aperture radar (SAR) signals interact with the ionosphere layer when they propagate through the atmosphere, leading to the phase delay error for SAR interferometry (InSAR). To mitigate this error for SAR interferometry, azimuth offset method is proposed. However, the performance of it has not been fully investigated. In this situation, this study makes a comprehensive performance analysis of azimuth offset method through processing the simulated and real SAR data. The experimental result indicates that this method can effectively mitigate the ionospheric phase delay error, where the standard deviation of phase difference after correction (2.6 rad.) decreased by almost 2 times, compared to those before correction (5.3 rad.) for the real SAR data. However, it is also found that the method is affected by the random noise, which may induce the improper estimation of integral constants and consequently affect the ionospheric correction. Moreover, the severe deformation signals in the interferogram may lead to the estimation error of integral constants and scaling factor. Therefore, it should mask out the deformation signals when using the azimuth offsets method to correct the ionospheric error. This study may provide useful information when using azimuth offset method to mitigate the ionospheric phase delay error on InSAR.

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Long-Term Remote Monitoring of Ground Deformation Using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR): Applications and Insights into Geotechnical Engineering Practices

Applied Sciences ◽

10.3390/app10217447 ◽

2020 ◽

Vol 10 (21) ◽

pp. 7447

Author(s):

Ryan Ramirez ◽

Seung-Rae Lee ◽

Tae-Hyuk Kwon

Keyword(s):

Synthetic Aperture Radar ◽

Ground Deformation ◽

Geotechnical Engineering ◽

Sar Interferometry ◽

Synthetic Aperture ◽

Successful Implementation ◽

Persistent Scatterers ◽

Sar Data ◽

Aperture Radar

Development of synthetic aperture radar (SAR) technology and the dedicated suite of processing tools have aided the evolution of remote sensing techniques for various Earth Observation (EO) applications. Interferometric SAR (InSAR) is a relatively new geodetic technique which provides high-speed and reliable geographic, geologic, and hazards information allowing the prognosis of future environmental and urban planning. In this study, we explored the applicability of two differential interferometry techniques, conventional and advanced differential InSAR (A-DInSAR), for topographic mapping and long-term geotechnical monitoring by exploiting satellite data, particularly Sentinel-1 SAR data, which is publicly shared. We specifically used the open-source tools of SeNtinel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS) for interferometric data processing to implement A-DInSAR. This study presents various applications, which include generation of a digital elevation model (DEM), mapping of seismically induced displacement and associated damages, and detection and long-term monitoring of tunneling-induced ground deformation and rainfall-induced landslide. Geometric and temporal decorrelations posed challenges and limitations in the successful implementation of Sentinel-1 SAR interferometry specifically in vegetated areas. The presented results proved the validity and reliability of the exploited SAR data and InSAR techniques for addressing geotechnical engineering related problems.

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Deep Learning Based Lithology Classification Using Dual-Frequency Pol-SAR Data

Applied Sciences ◽

10.3390/app8091513 ◽

2018 ◽

Vol 8 (9) ◽

pp. 1513

Author(s):

Wenguang Wang ◽

Xin Ren ◽

Yan Zhang ◽

Meng Li

Keyword(s):

Classification Performance ◽

Synthetic Aperture ◽

Experimental Result ◽

Dual Frequency ◽

High Similarity ◽

Polarimetric Synthetic Aperture Radar ◽

Class Separability ◽

Sparse Autoencoder ◽

Sar Data ◽

Sar Imagery

Lithology classification is a crucial step in the prospecting process, and polarimetric synthetic aperture radar (Pol-SAR) imagery has been extensively used for it. However, despite significant improvements in both information content of Pol-SAR imagery and advanced classification approaches, lithology classification using Pol-SAR data may not provide satisfactory classification accuracy due to high similarity of certain classes. In this paper, a novel Pol-SAR lithology classification method based on a stacked sparse autoencoder (SSAE) is proposed. By using superpixel segmentation, new features can be extracted from dual-frequency Pol-SAR data, which can increase the class separability of the input data. Then, these features and the coherency matrices are incorporated into SSAE to classify the lithology. The classification performance is evaluated on an SIR-C dataset acquired over Xinjiang, China. The experimental result shows that this method is effective for lithology classification and can improve the overall accuracy up to 98.90%.

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Meso- and microscale sea-ice motion in the East Siberian Sea as determined from ERS-1 SAR Data

Journal of Glaciology ◽

10.1017/s0022143000001878 ◽

1999 ◽

Vol 45 (150) ◽

pp. 370-383 ◽

Cited By ~ 7

Author(s):

Kim Morris ◽

Shusun Li ◽

Martin Jeffries

Keyword(s):

Time Series ◽

Sea Ice ◽

Large Scale ◽

Vector Fields ◽

Lateral Displacement ◽

Motion Vector ◽

Sar Interferometry ◽

East Siberian Sea ◽

Pack Ice ◽

Sar Data

Abstract Synthetic aperture radar- (SAR-)derived ice-motion vectors and SAR interferometry were used to study the sea-ice conditions in the region between the coast and 75° N (~ 560 km) in the East Siberian Sea in the vicinity of the Kolyma River. ERS-1 SAR data were acquired between 24 December 1993 and 30 March 1994 during the 3 day repeat Ice Phase of the satellite. The time series of the ice-motion vector fields revealed rapid (3 day) changes in the direction and displacement of the pack ice. Longer-term (≥ 1 month) trends also emerged which were related to changes in large-scale atmospheric circulation. On the basis of this time series, three sea-ice zones were identified: the near-shore, stationary-ice zone; a transitional-ice zone;and the pack-ice zone. Three 3 day interval and one 9 day interval interferometric sets (amplitude, correlation and phase diagrams) were generated for the end of December, the begining of February and mid-March. They revealed that the stationary-ice zone adjacent to the coast is in constant motion, primarily by lateral displacement, bending, tilting and rotation induced by atmospheric/oceanic forcing. The interferogram patterns change through time as the sea ice becomes thicker and a network of cracks becomes established in the ice cover. It was found that the major features in the interferograms were spatially correlated with sea-ice deformation features (cracks and ridges) and major discontinuities in ice thickness.

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Mapping of glacial motion and surface topography of Hielo Patagónico Norte, Chile, using satellite SAR L-band interferometry data

Annals of Glaciology ◽

10.1017/s026030550001346x ◽

1996 ◽

Vol 23 ◽

pp. 209-216 ◽

Cited By ~ 23

Author(s):

Eric Rignot ◽

Rick Forster ◽

Bryan Isacks

Keyword(s):

Surface Topography ◽

Radar Data ◽

Sar Interferometry ◽

Synthetic Aperture ◽

Topographic Map ◽

Imaging Radar ◽

Northern Patagonia ◽

Ice Velocity ◽

San Rafael ◽

Motion Map

The first topographic and ice-motion maps of the northwestern flank of Hielo Patagónico Norte (HPN, northern Patagonia Icefield), in Chile, were produced using satellite synthetic-aperture interferometric radar data acquired by NASA’s Spaceborne Imaging Radar C instrument in October 1994. The topographic map has a 10 m vertical precision with a 30 m horizontal spacing, which should be sufficient to serve as a reference for monitoring future mass changes of the icefield. The ice-motion map is accurate to within 4 mm d−1 (or 1 m a−1). The radar-derived surface topography and ice velocity are used to estimate the ice discharge from the accumulation area of four outlet glaciers, and the calving flux and mass balance of Glaciar San Rafael. The results demonstrate the use of SAR interferometry for monitoring glaciological parameters on a spatial and temporal scale unattainable by any other means.

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Deceptive Jamming Detection for SAR Based on Cross-Track Interferometry

Sensors ◽

10.3390/s18072265 ◽

2018 ◽

Vol 18 (7) ◽

pp. 2265 ◽

Cited By ~ 2

Author(s):

Qingqing Feng ◽

Huaping Xu ◽

Zhefeng Wu ◽

Wei Liu

Keyword(s):

Sar Interferometry ◽

Synthetic Aperture ◽

Sar Image ◽

Frequency Detection ◽

Interferometric Phase ◽

Deceptive Jamming ◽

Jamming Detection ◽

Novel Method ◽

The Difference ◽

Cross Track

Deceptive jamming against synthetic aperture radar (SAR) can create false targets or deceptive scenes in the image effectively. Based on the difference in interferometric phase between the target and deceptive jamming signals, a novel method for detecting deceptive jamming using cross-track interferometry is proposed, where the echoes with deceptive jamming are received by two SAR antennas simultaneously and the false targets are identified through SAR interferometry. Since the derived false phase is close to a constant in interferogram, it is extracted through phase filtering and frequency detection. Finally, the false targets in the SAR image are obtained according to the detected false part in the interferogram. The effectiveness of the proposed method is validated by simulation results based on the TanDEM-X system.

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Four-Stage Inversion Algorithm for Forest Height Estimation Using Repeat Pass Polarimetric SAR Interferometry Data

Remote Sensing ◽

10.3390/rs10081174 ◽

2018 ◽

Vol 10 (8) ◽

pp. 1174 ◽

Cited By ~ 3

Author(s):

Tayebe Managhebi ◽

Yasser Maghsoudi ◽

Mohammad Valadan Zoej

Keyword(s):

Extinction Coefficient ◽

European Space Agency ◽

Sar Interferometry ◽

Experimental Result ◽

Single Frequency ◽

Height Estimation ◽

Suggested Algorithm ◽

Forest Height ◽

Temporal Decorrelation ◽

The Mean

This paper proposes a new method for forest height estimation using single-baseline single frequency polarimetric synthetic aperture radar interferometry (PolInSAR) data. The new algorithm estimates the forest height based on the random volume over the ground with a volume temporal decorrelation (RVoG+VTD) model. We approach the problem using a four-stage geometrical method without the need for any prior information. In order to decrease the number of unknown parameters in the RVoG+VTD model, the mean extinction coefficient is estimated in an independent procedure. In this respect, the suggested algorithm estimates the mean extinction coefficient as a function of a geometrical index based on the signal penetration in the volume layer. As a result, the proposed four-stage algorithm can be used for forest height estimation using the repeat pass PolInSAR data, affected by temporal decorrelation, without the need for any auxiliary data. The suggested algorithm was applied to the PolInSAR data of the European Space Agency (ESA), BioSAR 2007 campaign. For the performance analysis of the proposed approach, repeat pass experimental SAR (ESAR) L-band data, acquired over the Remningstorp test site in Southern Sweden, is employed. The experimental result shows that the four-stage method estimates the volume height with an average root mean square error (RMSE) of 2.47 m against LiDAR heights. It presents a significant improvement of forest height accuracy, i.e., 5.42 m, compared to the three-stage method result, which ignores the temporal decorrelation effect.

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Multispectral and Radar Data for the Setting of Gold Mineralization in the South Eastern Desert, Egypt

Remote Sensing ◽

10.3390/rs11121450 ◽

2019 ◽

Vol 11 (12) ◽

pp. 1450 ◽

Cited By ~ 12

Author(s):

Basem Zoheir ◽

Ashraf Emam ◽

Mohamed Abdel-Wahed ◽

Nehal Soliman

Keyword(s):

Synthetic Aperture Radar ◽

Gold Mineralization ◽

Eastern Desert ◽

Synthetic Aperture ◽

The South ◽

Quartz Veins ◽

South Eastern ◽

Vein Formation ◽

Band Ratios ◽

Sar Data

Satellite-based multi-sensor data coupled with field and microscopic investigations are used to unravel the setting and controls of gold mineralization in the Wadi Beitan–Wadi Rahaba area in the South Eastern Desert of Egypt. The satellite-based multispectral and Synthetic Aperture Radar (SAR) data promoted a vibrant litho-tectonic understanding and abetted in assessing the regional structural control of the scattered gold occurrences in the study area. The herein detailed approach includes band rationing, principal component and independent component analyses, directional filtering, and automated and semi-automated lineament extraction techniques to Landsat 8- Operational Land Imager (OLI), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Phased Array L-band Synthetic Aperture Radar (PALSAR), and Sentinel-1B data. Results of optical and SAR data processed as grayscale raster images of band ratios, Relative Absorption Band Depth (RBD), and (mafic–carbonate–hydrous) mineralogical indices are used to extract the representative pixels (regions of interest). The extracted pixels are then converted to vector shape files and are finally imported into the ArcMap environment. Similarly, manually and automatically extracted lineaments are merged with the band ratios and mineralogical indices vector layers. The data fusion approach used herein reveals no particular spatial association between gold occurrences and certain lithological units, but shows a preferential distribution of gold–quartz veins in zones of chlorite–epidote alteration overlapping with high-density intersections of lineaments. Structural features including en-echelon arrays of quartz veins and intense recrystallization and sub-grain development textures are consistent with vein formation and gold deposition syn-kinematic with the host shear zones. The mineralized, central-shear quartz veins, and the associated strong stretching lineation affirm vein formation amid stress build-up and stress relaxation of an enduring oblique convergence (assigned as Najd-related sinistral transpression; ~640–610 Ma). As the main outcome of this research, we present a priority map with zones defined as high potential targets for undiscovered gold resources.

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On The Estimation of Temporal Changes of Snow Water Equivalent by Spaceborne Sar Interferometry: A New Application for the Sentinel-1 Mission

Journal of Hydrology and Hydromechanics ◽

10.2478/johh-2018-0003 ◽

2019 ◽

Vol 67 (1) ◽

pp. 93-100 ◽

Cited By ~ 8

Author(s):

Vasco Conde ◽

Giovanni Nico ◽

Pedro Mateus ◽

João Catalão ◽

Anna Kontu ◽

...

Keyword(s):

Measurement Accuracy ◽

Snow Water Equivalent ◽

Temporal Variations ◽

Sar Interferometry ◽

Synthetic Aperture ◽

Snow Layer ◽

Illumination Condition ◽

Interferometric Phase ◽

Snow Water

Abstract In this work we present a methodology for the mapping of Snow Water Equivalent (SWE) temporal variations based on the Synthetic Aperture Radar (SAR) Interferometry technique and Sentinel-1 data. The shift in the interferometric phase caused by the refraction of the microwave signal penetrating the snow layer is isolated and exploited to generate maps of temporal variation of SWE from coherent SAR interferograms. The main advantage of the proposed methodology with respect to those based on the inversion of microwave SAR backscattering models is its simplicity and the reduced number of required in-situ SWE measurements. The maps, updated up to every 6 days, can attain a spatial resolution up to 20 m with sub-centimetre ΔSWE measurement accuracy in any weather and sun illumination condition. We present results obtained using the proposed methodology over a study area in Finland. These results are compared with in-situ measurements of ΔSWE, showing a reasonable match with a mean accuracy of about 6 mm.

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Vegetated Target Decorrelation in SAR and Interferometry: Models, Simulation, and Performance Evaluation

Remote Sensing ◽

10.3390/rs12162545 ◽

2020 ◽

Vol 12 (16) ◽

pp. 2545 ◽

Cited By ~ 3

Author(s):

Andrea Monti-Guarnieri ◽

Marco Manzoni ◽

Davide Giudici ◽

Andrea Recchia ◽

Stefano Tebaldini

Keyword(s):

Formal Method ◽

Temporal Stability ◽

Sar Interferometry ◽

Synthetic Aperture ◽

Short Term ◽

Realistic Case ◽

X Band ◽

Temporal Decorrelation ◽

And Performance

The paper addresses the temporal stability of distributed targets, particularly referring to vegetation, to evaluate the degradation affecting synthetic aperture radar (SAR) imaging and repeat-pass interferometry, and provide efficient SAR simulation schemes for generating big dataset from wide areas. The models that are mostly adopted in literature are critically reviewed, and aim to study decorrelation in a range of time (from hours to days), of interest for long-term SAR, such as ground-based or geosynchronous, or repeat-pass SAR interferometry. It is shown that none of them explicitly account for a decorrelation occurring in the short-term. An explanation is provided, and a novel temporal decorrelation model is proposed to account for that fast decorrelation. A formal method is developed to evaluate the performance of SAR focusing, and interferometry on a homogenous, stationary scene, in terms of Signal-to-Clutter Ratio (SCR), and interferometric coherence. Finally, an efficient implementation of an SAR simulator capable of handling the realistic case of heterogeneous decorrelation over a wide area is discussed. Examples are given by assuming two geostationary SAR missions in C and X band.

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Forest mapping and monitoring with interferometric synthetic aperture radar (InSAR)

Progress in Physical Geography Earth and Environment ◽

10.1177/030913330102500201 ◽

2001 ◽

Vol 25 (2) ◽

pp. 159-177 ◽

Cited By ~ 68

Author(s):

H. Balzter

Keyword(s):

Synthetic Aperture Radar ◽

Electromagnetic Waves ◽

Forest Canopy ◽

Thermal State ◽

Time Lag ◽

Sar Interferometry ◽

Synthetic Aperture ◽

Dimensional Structure ◽

Forest Mapping ◽

Aperture Radar

A synthetic aperture radar (SAR) is an active sensor transmitting pulses of polarized electromagnetic waves and receiving the backscattered radiation. SAR sensors at different wavelengths and with different polarimetric capabilities are being used in remote sensing of the earth. The value of an analysis of backscattered energy alone is limited due to ambiguities in the possible ecological factor configurations causing the signal. From two SAR images taken from similar viewing positions with a short time-lag, interference between the two waves can be observed. By subtracting the two phases of the signals, it is feasible to eliminate the random contribution of the scatterers to the phase. The interferometric correlation and the interferometric phase contain additional information on the three-dimensional structure of the scattering elements in the imaged area. A brief review of SAR sensors is given, followed by an outline of the physical foundations of SAR interferometry and the practical data-processing steps involved. An overview of applications of InSAR to forest mapping and monitoring is given, covering tree-bole volume and biomass, forest types and land cover, fire scars, forest thermal state and forest canopy height.

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