Engineering › Aerospace Engineering

Synthetic Aperture Radar (SAR) Applications and Techniques

Works Count: 35373

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Description

This cluster of papers focuses on Synthetic Aperture Radar (SAR) interferometry, including topics such as surface deformation monitoring, persistent scatterers, digital elevation models, land subsidence, polarimetric SAR, forest biomass estimation, urban development monitoring, and groundwater extraction.

Keywords

SAR Interferometry; Surface Deformation Monitoring; Persistent Scatterers; Digital Elevation Models; InSAR Technique; Land Subsidence; Polarimetric SAR; Forest Biomass Estimation; Urban Development Monitoring; Groundwater Extraction

Polarimetric Radar Imaging : From basics to applications.

2009-01-01

J.S. Lee , Éric Pottier

Overview of Polarimetric Radar Imaging Brief History of Polarimetric Radar Imaging SAR Image Formation: Summary Airborne and Space-Borne PolSAR Systems Description of the Remaining Chapters Electromagnetic Vector Wave and Polarization … Overview of Polarimetric Radar Imaging Brief History of Polarimetric Radar Imaging SAR Image Formation: Summary Airborne and Space-Borne PolSAR Systems Description of the Remaining Chapters Electromagnetic Vector Wave and Polarization Descriptors Monochromatic Electromagnetic Plane Wave Polarization Ellipse Jones Vector Stokes Vector Wave Covariance Matrix Electromagnetic Vector Scattering Operators Polarimetric Back Scattering Sinclair S Matrix Scattering Target Vectors k and Omega Polarimetric Coherency T and Covariance C Matrices Polarimetric Mueller M and Kennaugh K Matrices Change of Polarimetric Basis Target Polarimetric Characterization PolSAR Speckle Statistics Fundamental Property of Speckle in SAR Images Speckle Statistics for Multilook-Processed SAR Images Texture Model and K Distribution Effect of Speckle Spatial Correlation Polarimetric and Interferometric SAR Speckle Statistics Phase Difference Distributions of Single-Look and Multilook PolSAR Data Multilook Product Distribution Joint Distribution of Multilook Si2 and Sj2 Multilook Intensity and Amplitude Ratio Distributions Verifications of Multilook PDFs K Distribution for Multilook Polarimetric Data Summary Appendices PolSAR Speckle Filtering Introduction to Speckle Filtering of SAR Imagery Filtering of Single Polarization SAR Data Review of Multipolarization Speckle Filtering Algorithms PolSAR Speckle Filtering Scattering Model-Based PolSAR Speckle Filter Introduction to the Polarimetric Target Decomposition Concept Introduction Dichotomy of the Kennaugh Matrix K Eigenvector-Based Decompositions Model-Based Decompositions Coherent Decompositions The H/A/a Polarimetric Decomposition Theorem Introduction Pure Target Case Probabilistic Model for Random Media Scattering Roll Invariance Property Polarimetric Scattering a Parameter Polarimetric Scattering Entropy (H) Polarimetric Scattering Anisotropy (A) Three-Dimensional H/A/a Classification Space New Eigenvalue-Based Parameters Speckle Filtering Effects on H/A/a PolSAR Terrain and Land-Use Classification Introduction Maximum Likelihood Classifier Based on Complex Gaussian Distribution Complex Wishart Classifier for Multilook PolSAR Data Characteristics of Wishart Distance Measure Supervised Classification Using Wishart Distance Measure Unsupervised Classification Based on Scattering Mechanisms and Wishart Classifier Scattering Model-Based Unsupervised Classification Quantitative Comparison of Classification Capability: Fully PolSAR versus Dual- and Single-Polarization SAR Pol-InSAR Forest Mapping and Classification Introduction Pol-InSAR Scattering Descriptors Forest Mapping and Forest Classification Appendix Selected PolSAR Applications Polarimetric Signature Analysis of Manmade Structures Polarization Orientation Angle Estimation and Applications Ocean Surface Remote Sensing with PolSAR Ionosphere Faraday Rotation Estimation PolSAR Interferometry for Forest Height Estimation Nonstationary Natural Media Analysis from PolSAR Data Using a Two-Dimensional Time-Frequency Approach Appendix A: Eigen Characteristics of Hermitian Matrix Appendix B: PolSARpro Software: The Polariemtric SAR Data Processing and Educational Toolbox Index

Synthetic Aperture Radar Processing

2018-02-06

Giorgio Franceschetti , R. Lanari

FUNDAMENTALS Introduction Historical Background Synthetic Aperture Radar Systems Modes Geometric Resolution Goemetric Distortions Synthetic Aperture Radar Signal Statistics InterferometricSynthetic Aperture Radar Phase Statistics Radiometric Resolution Ambiguity Considerations Power and Noise … FUNDAMENTALS Introduction Historical Background Synthetic Aperture Radar Systems Modes Geometric Resolution Goemetric Distortions Synthetic Aperture Radar Signal Statistics InterferometricSynthetic Aperture Radar Phase Statistics Radiometric Resolution Ambiguity Considerations Power and Noise Considerations STRIP MODE TRANSFER FUNCTION Signal Analysis in Time Domain Synthetic Aperture Radar Transfer Function Squinted Geometry Earth's Rotation and Sensor Orbit Effects Reflectivity Pattern STRIP MODE DATA PROCESSING Point Target Response Synthetic Aperture Radar Transfer Function and its Approximations Narrow Focus Synthetic Aperture Radar Processing Wide Focus Syntheric Aperture Radar Processing Efficient Wide Focus Synthetic Aperture Radar Processing Range-Doppler Synthetic Aperture Radar Processing Motion Compensation Multiple Look Synthetic Aperture Radar Image Generation Estimation Procedures for Synthetic Aperture Radar Parameters SYNTHETIC APERTURE RADAR INTERFEROMETRY Introduction Interferometric Synthetic Aperture Radar Processing Interferometric Phase Noise Image Registration Techniques Interferometric Phase Statistics Decorrelation Effects Digital Elevation Model Accuracy Phase Unwrapping Weighted Phase Unwrapping Via Finite Element Method Geocoding Differential Interfermetric Synthetic Aperture Radar SCAN MODE SIGNAL ANALYSIS AND DATA PROCESSING Time Domain Analysis Frequency Domain Analysis Point Target Image Generation Scan Mode Data Processing SPOT MODE SIGNAL ANALYSIS AND DATA PROCESSING Time Domain Analysis Frequency Domain Analysis Bandwidths Considerations Residual Video Phase Compensation Spot Mode Image Generation PROCESSING CODE EXAMPLE Code Presentation Processing Code INDEX

A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers

2004-12-09

Andrew Hooper , H. A. Zebker , P. Segall +1 more

We present here a new InSAR persistent scatterer (PS) method for analyzing episodic crustal deformation in non‐urban environments, with application to volcanic settings. Our method for identifying PS pixels in … We present here a new InSAR persistent scatterer (PS) method for analyzing episodic crustal deformation in non‐urban environments, with application to volcanic settings. Our method for identifying PS pixels in a series of interferograms is based primarily on phase characteristics and finds low‐amplitude pixels with phase stability that are not identified by the existing amplitude‐based algorithm. Our method also uses the spatial correlation of the phases rather than a well‐defined phase history so that we can observe temporally‐variable processes, e.g., volcanic deformation. The algorithm involves removing the residual topographic component of flattened interferogram phase for each PS, then unwrapping the PS phases both spatially and temporally. Our method finds scatterers with stable phase characteristics independent of amplitudes associated with man‐made objects, and is applicable to areas where conventional InSAR fails due to complete decorrelation of the majority of scatterers, yet a few stable scatterers are present.

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Mapping small elevation changes over large areas: Differential radar interferometry

1989-07-10

Andrew K. Gabriel , R. M. Goldstein , H. A. Zebker

A technique that uses synthetic aperture radar (SAR) images to measure very small (1 cm or less) surface motions with good resolution (10 m) over large swaths (50 km) is … A technique that uses synthetic aperture radar (SAR) images to measure very small (1 cm or less) surface motions with good resolution (10 m) over large swaths (50 km) is presented along with experimental results. The method could be used for accurate measurements of many geophysical phenomena, including swelling and buckling in fault zones, residual displacements from seismic events, and prevolcanic swelling. The method is based on SAR interferometry, where two images are made of a scene by simultaneously flying two physically separated antennas. Then the phases of corresponding pixels are differenced, and altitude formation is deduced from some simple computation and image rectification. It is also possible to use one antenna flown twice over the same scene; then, if the second flight exactly duplicates the track of the first, an interesting possibility occurs. There would be no phase changes between the images at all unless there was a physical change in the scene, such as ground swelling, that would alter the distance from some resolution element to the antenna. Since the phase changes all occur at the short carrier wavelength, the basic limitation on sensitivity is only the phase noise in the system. When the two imaging passes are made from flight tracks that are separated (which is the case with the Seasat images used here), it is no longer possible to distinguish surface changes from the parallax caused by topography. However, with some additional computation, a third image made at some other baseline may be used to remove the topography and leave only the surface changes. This method was applied using Seasat data to an imaging site in Imperial Valley, California, where motion effects were observed that were ascribed to the expansion of water‐absorbing clays. Phase change images of this area are shown, along with associated ground truth about the presence of water. Problems with the technique are explored, along with a discussion of future experimental possibilities on upcoming SAR missions like Earth Observing System (EOS), Earth Resources Satellite (ERS 1), SIR‐C, and the Venus imaging radar, Magellan.

GMES Sentinel-1 mission

2012-02-18

Ramón Torres , P. Snoeij , Dirk Geudtner +7 more

The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar

2003-02-01

Bernhard Rabus , Michael Eineder , Achim Roth +1 more

Single-baseline polarimetric SAR interferometry

2001-01-01

Konstantinos Papathanassiou , S.R. Cloude

Examines the application of single-baseline polarimetric SAR interferometry to the remote sensing and measurement of structure over forested terrain. For this, a polarimetric coherent scattering model for vegetation cover suitable … Examines the application of single-baseline polarimetric SAR interferometry to the remote sensing and measurement of structure over forested terrain. For this, a polarimetric coherent scattering model for vegetation cover suitable for the estimation of forest parameters from interferometric observables is introduced, discussed and validated. Based on this model, an inversion algorithm which allows the estimation of forest parameters such as tree height, average extinction, and underlying topography from single-baseline fully polarimetric interferometric data is addressed. The performance of the inversion algorithm is demonstrated using fully polarimetric single baseline experimental data acquired by DLR's E-SAR system at L-band.

Polarimetric SAR interferometry

1998-01-01

S.R. Cloude , Konstantinos Papathanassiou

The authors examine the role of polarimetry in synthetic aperture radar (SAR) interferometry. They first propose a general formulation for vector wave interferometry that includes conventional scalar interferometry as a … The authors examine the role of polarimetry in synthetic aperture radar (SAR) interferometry. They first propose a general formulation for vector wave interferometry that includes conventional scalar interferometry as a special case. Then, they show how polarimetric basis transformations can be introduced into SAR interferometry and applied to form interferograms between all possible linear combinations of polarization states. This allows them to reveal the strong polarization dependency of the interferometric coherence. They then solve the coherence optimization problem involving maximization of interferometric coherence and formulate a new coherent decomposition for polarimetric SAR interferometry that allows the separation of the effective phase centers of different scattering mechanisms. A simplified stochastic scattering model for an elevated forest canopy is introduced to demonstrate the effectiveness of the proposed algorithms. In this way, they demonstrate the importance of wave polarization for the physical interpretation of SAR interferograms. They investigate the potential of polarimetric SAR interferometry using results from the evaluation of fully polarimetric interferometric shuttle imaging radar (SIR)-C/X-SAR data collected during October 8-9, 1994, over the SE Baikal Lake Selenga delta region of Buriatia, Southeast Siberia, Russia.

Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcán Alcedo, Galápagos

2007-07-01

Andrew Hooper , P. Segall , H. A. Zebker

While conventional interferometric synthetic aperture radar (InSAR) is a very effective technique for measuring crustal deformation, almost any interferogram includes large areas where the signals decorrelate and no measurement is … While conventional interferometric synthetic aperture radar (InSAR) is a very effective technique for measuring crustal deformation, almost any interferogram includes large areas where the signals decorrelate and no measurement is possible. Persistent scatterer (PS) InSAR overcomes the decorrelation problem by identifying resolution elements whose echo is dominated by a single scatterer in a series of interferograms. Existing PS methods have been very successful in analysis of urban areas, where stable angular structures produce efficient reflectors that dominate background scattering. However, man‐made structures are absent from most of the Earth's surface. Furthermore, existing methods identify PS pixels based on the similarity of their phase history to an assumed model for how deformation varies with time, whereas characterizing the temporal pattern of deformation is commonly one of the aims of any deformation study. We describe here a method for PS analysis, StaMPS, that uses spatial correlation of interferogram phase to find pixels with low‐phase variance in all terrains, with or without buildings. Prior knowledge of temporal variations in the deformation rate is not required for their identification. We apply StaMPS to Volcán Alcedo, where conventional InSAR fails because of dense vegetation on the upper volcano flanks that causes most pixels to decorrelate with time. We detect two sources of deformation. The first we model as a contracting pipe‐like body, which we interpret to be a crystallizing magma chamber. The second is downward and lateral motion on the inner slopes of the caldera, which we interpret as landsliding.

Recent advances in SAR interferometry time series analysis for measuring crustal deformation

2011-10-27

Andrew Hooper , David Bekaert , Karsten Spaans +1 more

Shuttle radar topography mission produces a wealth of data

2000-11-28

T. G. Farr , Mike Kobrick

On February 22, 2000, the Space Shuttle Endeavour landed at Kennedy Space Center, completing the highly successful 11‐day flight of the Shuttle Radar Topography Mission (SRTM). Onboard were over 300 … On February 22, 2000, the Space Shuttle Endeavour landed at Kennedy Space Center, completing the highly successful 11‐day flight of the Shuttle Radar Topography Mission (SRTM). Onboard were over 300 high‐density tapes containing data for the highest resolution digital topographic map of Earth ever made. SRTM is a cooperative project between the National Aeronautics and Space Administration (NASA) and the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense. The mission was designed to use a single‐pass radar interferometer to produce a digital elevation model (DEM) of the Earth's land surface between about 60 north and 56 south latitude. When completed, the DEM will have 30‐m pixel spacing and about 15‐m vertical accuracy. Two ortho‐rectified image mosaics, one from the ascending passes with illumination from the southeast, and one from descending passes with illumination from the southwest, will also be produced (Figure 1).

Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps

1997-04-10

H. A. Zebker , P. A. Rosen , S. Hensley

Interferogram images derived from repeat‐pass spaceborne synthetic aperture radar systems exhibit artifacts due to the time and space variations of atmospheric water vapor. Other tropospheric variations, such as pressure and … Interferogram images derived from repeat‐pass spaceborne synthetic aperture radar systems exhibit artifacts due to the time and space variations of atmospheric water vapor. Other tropospheric variations, such as pressure and temperature, also induce distortions, but the effects are smaller in magnitude and more evenly distributed throughout the interferogram than the wet troposphere term. Spatial and temporal changes of 20% in relative humidity lead to 10 cm errors in deformation products, and perhaps 100 m of error in derived topographic maps for those pass pairs with unfavorable baseline geometries. In wet regions such as Hawaii, these are by far the dominant errors in the Spaceborne Imaging Radar‐C and X Band Synthetic Aperature Radar (SIR‐C/X‐SAR) interferometric products. The unknown time delay from tropospheric distortion is independent of frequency, and thus multiwavelength measurements, such as those commonly used to correct radar altimeter and Global Positioning System (GPS) ionospheric biases, cannot be used to rectify the error. In the topographic case, the errors may be mitigated by choosing interferometric pairs with relatively long baselines, as the error amplitude is inversely proportional to the perpendicular component of the interferometer baseline. For the SIR‐C/X‐SAR Hawaii data we found that the best (longest) baseline pair produced a map supporting 100 m contouring, whereas the poorest baseline choice yielded an extremely noisy topographic map even at this coarse contour interval. In the case of deformation map errors the result is either independent of baseline parameters or else very nearly so. Here the only solution is averaging of independent interferograms, so in order to create accurate deformation products in wet regions many multiple passes may be required. Rules for designing optimal data acquisition and processing sequences for interferometric analyses in nondesert parts of the world are (1) to use the longest radar wavelengths possible, within ionospheric scintillation and Faraday rotation limits, (2) for topography, maximize interferometer baseline within decorrelation limits* and (3) for surface deformation, use multiple observations and average the derived products. Following the above recipe yields accuracies of 10 m for digital elevation models and 1 cm for deformation maps even in very wet regions, such as Hawaii.

Radar interferogram filtering for geophysical applications

1998-11-01

R. M. Goldstein , Charles Werner

The use of SAR interferometry is often impeded by decorrelation from thermal noise, temporal change, and baseline geometry. Power spectra of interferograms are typically the sum of a narrow‐band component … The use of SAR interferometry is often impeded by decorrelation from thermal noise, temporal change, and baseline geometry. Power spectra of interferograms are typically the sum of a narrow‐band component combined with broad‐band noise. We describe a new adaptive filtering algorithm that dramatically lowers phase noise, improving both measurement accuracy and phase unwrapping, while demonstrating graceful degradation in regions of pure noise. The performance of the filter is demonstrated with SAR data from the ERS satellites over the Jakobshavns glacier of Greenland.

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TanDEM-X: A Satellite Formation for High-Resolution SAR Interferometry

2007-11-01

Gerhard Krieger , Alberto Moreira , Hauke Fiedler +4 more

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an innovative spaceborne radar interferometer that is based on two TerraSAR-X radar satellites flying in close formation. The primary … <para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an innovative spaceborne radar interferometer that is based on two TerraSAR-X radar satellites flying in close formation. The primary objective of the TanDEM-X mission is the generation of a consistent global digital elevation model (DEM) with an unprecedented accuracy, which is equaling or surpassing the HRTI-3 specification. Beyond that, TanDEM-X provides a highly reconfigurable platform for the demonstration of new radar imaging techniques and applications. This paper gives a detailed overview of the TanDEM-X mission concept which is based on the systematic combination of several innovative technologies. The key elements are the bistatic data acquisition employing an innovative phase synchronization link, a novel satellite formation flying concept allowing for the collection of bistatic data with short along-track baselines, as well as the use of new interferometric modes for system verification and DEM calibration. The interferometric performance is analyzed in detail, taking into account the peculiarities of the bistatic operation. Based on this analysis, an optimized DEM data acquisition plan is derived which employs the combination of multiple data takes with different baselines. Finally, a collection of instructive examples illustrates the capabilities of TanDEM-X for the development and demonstration of new remote sensing applications. </para>

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Permanent scatterers in SAR interferometry

2001-01-01

A. Ferretti , C. Prati , F. Rocca

Temporal and geometrical decorrelation often prevents SAR interferometry from being an operational tool for surface deformation monitoring and topographic profile reconstruction. Moreover, atmospheric disturbances can strongly compromise the accuracy of … Temporal and geometrical decorrelation often prevents SAR interferometry from being an operational tool for surface deformation monitoring and topographic profile reconstruction. Moreover, atmospheric disturbances can strongly compromise the accuracy of the results. The authors present a complete procedure for the identification and exploitation of stable natural reflectors or permanent scatterers (PSs) starting from long temporal series of interferometric SAR images. When, as it often happens, the dimension of the PS is smaller than the resolution cell, the coherence is good even for interferograms with baselines larger than the decorrelation one, and all the available images of the ESA ERS data set can be successfully exploited. On these pixels, submeter DEM accuracy and millimetric terrain motion detection can be achieved, since atmospheric phase screen (APS) contributions can be estimated and removed. Examples are then shown of small motion measurements, DEM refinement, and APS estimation and removal in the case of a sliding area in Ancona, Italy. ERS data have been used.

First demonstration of airborne SAR tomography using multibaseline L-band data

2000-01-01

Andreas Reigber , Alberto Moreira

In synthetic aperture radar (SAR) interferometry, the phase differences between two different sensor positions are used to estimate the terrain topography. Although it is possible in this way to find … In synthetic aperture radar (SAR) interferometry, the phase differences between two different sensor positions are used to estimate the terrain topography. Although it is possible in this way to find a three-dimensional (3D) surface representation, the distribution of the different scatterers in the height direction at a fixed range and azimuth position remains unknown. Contrary to this, tomographic techniques enable a real geometric resolution capability in the height direction and introduce new possibilities for many applications and inversion problems. Even misinterpretations in SAR images caused by layover and foreshortening effects can be solved by the tomographic processing. In this paper, the successful experimental realization of polarimetric airborne SAR tomography is demonstrated for the first time. The authors present the concept of aperture synthesis for tomographic imaging for the case of a multibaseline imaging geometry and discuss the constraints arising from the limited number of flight tracks. They propose a method for reduction of the height ambiguities associated to the irregular and undersampled spatial distribution of the imaging positions. Finally, they address the experimental requirements for polarimetric airborne SAR tomography and show experimental results using a multibaseline data set acquired in L-band by DLR's experimental SAR (E-SAR) of a test-site near Oberpfaffenhofen, Germany.

Topographic mapping from interferometric synthetic aperture radar observations

1986-04-10

H. A. Zebker , R. M. Goldstein

Interferometric synthetic aperture radar observations provide a means for obtaining high‐resolution topographic terrain maps from data acquired simultaneously at two slightly displaced antennas. Calculation of the three‐dimensional coordinates of all … Interferometric synthetic aperture radar observations provide a means for obtaining high‐resolution topographic terrain maps from data acquired simultaneously at two slightly displaced antennas. Calculation of the three‐dimensional coordinates of all the points in a radar image can be made from the combination of along‐track, slant range, and interferometer fringe measurements. Thus the result compensates for the layover exhibited by conventional radar maps and removes the false targets generated by multiple signal paths to a given object in the scene. We have derived a topographic map of a portion of the San Francisco Bay Area utilizing data that were recorded by a radar system mounted on a NASA CV990 aircraft and processed by a general purpose digital computer. This map displays the height above sea level of a region approximately 11 km by 10 km in size, sampled on an 11‐m pixel grid. Uncertainties in the estimated height result from imprecise knowledge of the observational geometry, radar bandwidth limitations, and finite signal‐to‐noise ratios. For our system, each factor contributed approximately 3–4 m to a relative rms error of about 6 m. Additional global errors of the order of 10 m can result from inaccurate monitoring of aircraft attitude. The statistical variation of the height measurements from the ocean portion of the map, which we can presume to be quite flat, is 2–10 m rms, which is consistent with the theoretical estimate. Comparison of our results with U.S. Geological Survey contour maps indicates a high degree of correlation between the two sets of altitude data.

Synthetic aperture radar interferometry

1998-08-01

Richard Bamler , Philipp Hartl

Synthetic aperture radar (SAR) is a coherent active microwave imaging method. In remote sensing it is used for mapping the scattering properties of the Earth's surface in the respective wavelength … Synthetic aperture radar (SAR) is a coherent active microwave imaging method. In remote sensing it is used for mapping the scattering properties of the Earth's surface in the respective wavelength domain. Many physical and geometric parameters of the imaged scene contribute to the grey value of a SAR image pixel. Scene inversion suffers from this high ambiguity and requires SAR data taken at different wavelength, polarization, time, incidence angle, etc.

Radar interferometry and its application to changes in the Earth's surface

1998-11-01

D. Massonnet , K. L. Feigl

Geophysical applications of radar interferometry to measure changes in the Earth's surface have exploded in the early 1990s. This new geodetic technique calculates the interference pattern caused by the difference … Geophysical applications of radar interferometry to measure changes in the Earth's surface have exploded in the early 1990s. This new geodetic technique calculates the interference pattern caused by the difference in phase between two images acquired by a spaceborne synthetic aperture radar at two distinct times. The resulting interferogram is a contour map of the change in distance between the ground and the radar instrument. These maps provide an unsurpassed spatial sampling density (∼100 pixels km −2 ), a competitive precision (∼1 cm), and a useful observation cadence (1 pass month −1 ). They record movements in the crust, perturbations in the atmosphere, dielectric modifications in the soil, and relief in the topography. They are also sensitive to technical effects, such as relative variations in the radar's trajectory or variations in its frequency standard. We describe how all these phenomena contribute to an interferogram. Then a practical summary explains the techniques for calculating and manipulating interferograms from various radar instruments, including the four satellites currently in orbit: ERS‐1, ERS‐2, JERS‐1, and RADARSAT. The next chapter suggests some guidelines for interpreting an interferogram as a geophysical measurement: respecting the limits of the technique, assessing its uncertainty, recognizing artifacts, and discriminating different types of signal. We then review the geophysical applications published to date, most of which study deformation related to earthquakes, volcanoes, and glaciers using ERS‐1 data. We also show examples of monitoring natural hazards and environmental alterations related to landslides, subsidence, and agriculture. In addition, we consider subtler geophysical signals such as postseismic relaxation, tidal loading of coastal areas, and interseismic strain accumulation. We conclude with our perspectives on the future of radar interferometry. The objective of the review is for the reader to develop the physical understanding necessary to calculate an interferogram and the geophysical intuition necessary to interpret it.

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Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry

2006-11-16

C. Colesanti , Janusz Wąsowski

A review of target decomposition theorems in radar polarimetry

1996-03-01

S.R. Cloude , Éric Pottier

In this paper, we provide a review of the different approaches used for target decomposition theory in radar polarimetry. We classify three main types of theorem; those based on the … In this paper, we provide a review of the different approaches used for target decomposition theory in radar polarimetry. We classify three main types of theorem; those based on the Mueller matrix and Stokes vector, those using an eigenvector analysis of the covariance or coherency matrix, and those employing coherent decomposition of the scattering matrix. We unify the formulation of these different approaches using transformation theory and an eigenvector analysis. We show how special forms of these decompositions apply for the important case of backscatter from terrain with generic symmetries.

A tutorial on synthetic aperture radar

2013-03-01

Alberto Moreira , Pau Prats , Marwan Younis +3 more

Synthetic Aperture Radar (SAR) has been widely used for Earth remote sensing for more than 30 years. It provides high-resolution, day-and-night and weather-independent images for a multitude of applications ranging … Synthetic Aperture Radar (SAR) has been widely used for Earth remote sensing for more than 30 years. It provides high-resolution, day-and-night and weather-independent images for a multitude of applications ranging from geoscience and climate change research, environmental and Earth system monitoring, 2-D and 3-D mapping, change detection, 4-D mapping (space and time), security-related applications up to planetary exploration. With the advances in radar technology and geo/bio-physical parameter inversion modeling in the 90s, using data from several airborne and spaceborne systems, a paradigm shift occurred from the development driven by the technology push to the user demand pull. Today, more than 15 spaceborne SAR systems are being operated for innumerous applications. This paper provides first a tutorial about the SAR principles and theory, followed by an overview of established techniques like polarimetry, interferometry and differential interferometry as well as of emerging techniques (e.g., polarimetric SAR interferometry, tomography and holographic tomography). Several application examples including the associated parameter inversion modeling are provided for each case. The paper also describes innovative technologies and concepts like digital beamforming, Multiple-Input Multiple-Output (MIMO) and bi- and multi-static configurations which are suitable means to fulfill the increasing user requirements. The paper concludes with a vision for SAR remote sensing.

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The Shuttle Radar Topography Mission

2007-05-19

T. G. Farr , P. A. Rosen , E.R. Caro +7 more

The Shuttle Radar Topography Mission produced the most complete, highest‐resolution digital elevation model of the Earth. The project was a joint endeavor of NASA, the National Geospatial‐Intelligence Agency, and the … The Shuttle Radar Topography Mission produced the most complete, highest‐resolution digital elevation model of the Earth. The project was a joint endeavor of NASA, the National Geospatial‐Intelligence Agency, and the German and Italian Space Agencies and flew in February 2000. It used dual radar antennas to acquire interferometric radar data, processed to digital topographic data at 1 arc sec resolution. Details of the development, flight operations, data processing, and products are provided for users of this revolutionary data set.

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The displacement field of the Landers earthquake mapped by radar interferometry

1993-07-01

D. Massonnet , M. Rossi , César Carmona +4 more

Toward mapping surface deformation in three dimensions using InSAR

2004-01-01

Tim Wright , B. Parsons , Zhong Lu

One of the limitations of deformation measurements made with interferometric synthetic aperture radar (InSAR) is that an interferogram only measures one component of the surface deformation — in the satellite's … One of the limitations of deformation measurements made with interferometric synthetic aperture radar (InSAR) is that an interferogram only measures one component of the surface deformation — in the satellite's line of sight. We investigate strategies for mapping surface deformation in three dimensions by using multiple interferograms, with different imaging geometries. Geometries for both current and future missions are evaluated, and their abilities to resolve the displacement vector are compared. The north component is always the most difficult to determine using data from near‐polar orbiting satellites. However, a satellite with an inclination of about 60°/120° would enable all three components to be well resolved. We attempt to resolve the 3D displacements for the 23 October 2002 Nenana Mountain (Alaska) Earthquake. The north component's error is much larger than the signal, but proxies for eastward and vertical motion can be determined if the north component is assumed negligible. Inversions of hypothetical coseismic interferograms demonstrate that earthquake model parameters can be well recovered from two interferograms, acquired on ascending and descending tracks.

A three-component scattering model for polarimetric SAR data

1998-05-01

A. Freeman , Stephen L. Durden

An approach has been developed that involves the fit of a combination of three simple scattering mechanisms to polarimetric SAR observations. The mechanisms are canopy scatter from a cloud of … An approach has been developed that involves the fit of a combination of three simple scattering mechanisms to polarimetric SAR observations. The mechanisms are canopy scatter from a cloud of randomly oriented dipoles, evenor double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants and Bragg scatter from a moderately rough surface. This composite scattering model is used to describe the polarimetric backscatter from naturally occurring scatterers. The model is shown to describe the behavior of polarimetric backscatter from tropical rain forests quite well by applying it to data from NASA/Jet Propulsion Laboratory's (JPLs) airborne polarimetric synthetic aperture radar (AIRSAR) system. The model fit allows clear discrimination between flooded and nonflooded forest and between forested and deforested areas, for example. The model is also shown to be usable as a predictive tool to estimate the effects of forest inundation and disturbance on the fully polarimetric radar signature. An advantage of this model fit approach is that the scattering contributions from the three basic scattering mechanisms can be estimated for clusters of pixels in polarimetric SAR images. Furthermore, it is shown that the contributions of the three scattering mechanisms to the HH, HV, and VV backscatter can be calculated from the model fit. Finally, this model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem.

A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms

2004-07-01

R. Lanari , Oscar Mora , Michele Manunta +3 more

This paper presents a differential synthetic aperture radar (SAR) interferometry (DIFSAR) approach for investigating deformation phenomena on full-resolution DIFSAR interferograms. In particular, our algorithm extends the capability of the small-baseline … This paper presents a differential synthetic aperture radar (SAR) interferometry (DIFSAR) approach for investigating deformation phenomena on full-resolution DIFSAR interferograms. In particular, our algorithm extends the capability of the small-baseline subset (SBAS) technique that relies on small-baseline DIFSAR interferograms only and is mainly focused on investigating large-scale deformations with spatial resolutions of about 100/spl times/100 m. The proposed technique is implemented by using two different sets of data generated at low (multilook data) and full (single-look data) spatial resolution, respectively. The former is used to identify and estimate, via the conventional SBAS technique, large spatial scale deformation patterns, topographic errors in the available digital elevation model, and possible atmospheric phase artifacts; the latter allows us to detect, on the full-resolution residual phase components, structures highly coherent over time (buildings, rocks, lava, structures, etc.), as well as their height and displacements. In particular, the estimation of the temporal evolution of these local deformations is easily implemented by applying the singular value decomposition technique. The proposed algorithm has been tested with data acquired by the European Remote Sensing satellites relative to the Campania area (Italy) and validated by using geodetic measurements.

Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry

2000-01-01

A. Ferretti , C. Prati , F. Rocca

Discrete and temporarily stable natural reflectors or permanent scatterers (PS) can be identified from long temporal series of interferometric SAR images even with baselines larger than the so-called critical baseline. … Discrete and temporarily stable natural reflectors or permanent scatterers (PS) can be identified from long temporal series of interferometric SAR images even with baselines larger than the so-called critical baseline. This subset of image pixels can be exploited successfully for high accuracy differential measurements. The authors discuss the use of PS in urban areas, like Pomona, CA, showing subsidence and absidence effects. A new approach to the estimation of the atmospheric phase contributions, and the local displacement field is proposed based on simple statistical assumptions. New solutions are presented in order to cope with nonlinear motion of the targets.

Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery

1994-01-01

Jong-Sen Lee , K. W. Hoppel , S. Mango +1 more

Polarimetric and interferometric SAR data are frequently multilook processed for speckle reduction and data compression. The statistical characteristics of multilook data are quite different from those of single-look data. The … Polarimetric and interferometric SAR data are frequently multilook processed for speckle reduction and data compression. The statistical characteristics of multilook data are quite different from those of single-look data. The authors investigate the statistics of their intensity and phase. Probability density function (PDF's) of the multilook phase difference, magnitude of complex product, and intensity and amplitude ratios between two components of the scattering matrix are derived, and expressed in closed forms. The PDF's depend on the complex correlation coefficient and the number of looks. Comparisons of these theoretically derived PDF's are made to measurements from NASA/JPL AIRSAR data. The results of this paper can be applied to feature classification using polarimetric SAR and to the estimation of decorrelation effects of the interferometric SAR.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

Relating forest biomass to SAR data

1992-03-01

Thuy Le Toan , Amélie Beaudoin , J. Riom +1 more

The authors present the results of an experiment defined to demonstrate the use of radar to retrieve forest biomass. The SAR data were acquired by the NASA/JPL SAR over the … The authors present the results of an experiment defined to demonstrate the use of radar to retrieve forest biomass. The SAR data were acquired by the NASA/JPL SAR over the Landes pine forest during the 1989 MAESTRO-1 campaign. The SAR data, after calibration, were analyzed together with ground data collected on forest stands from a young stage (eight years) to a mature stage (46 years). The dynamic range of the radar backscatter intensity from forest was found to be greatest at P-band and decreased with increasing frequencies. Cross-polarized backscatter intensity yielded the best sensitivities to variations of forest biomass. L-band data confirmed past results on good correlation with forest parameters. The most striking observation was the strong correlation of P-band backscatter intensity to forest biomass.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>

A multi‐temporal InSAR method incorporating both persistent scatterer and small baseline approaches

2008-08-01

Andrew Hooper

Synthetic aperture radar (SAR) interferometry is a technique that provides high‐resolution measurements of the ground displacement associated with many geophysical processes. Advanced techniques involving the simultaneous processing of multiple SAR … Synthetic aperture radar (SAR) interferometry is a technique that provides high‐resolution measurements of the ground displacement associated with many geophysical processes. Advanced techniques involving the simultaneous processing of multiple SAR acquisitions in time increase the number of locations where a deformation signal can be extracted and reduce associated error. Currently there are two broad categories of algorithms for processing multiple acquisitions, persistent scatterer and small baseline methods, which are optimized for different models of scattering. However, the scattering characteristics of real terrains usually lay between these two end‐member models. I present here a new method that combines both approaches, to extract the deformation signal at more points and with higher overall signal‐to‐noise ratio than can either approach alone. I apply the combined method to data acquired over Eyjafjallajökull volcano in Iceland, and detect time‐varying ground displacements associated with two intrusion events.

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A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR

2011-05-13

A. Ferretti , Alfio Fumagalli , F. Novali +3 more

Permanent Scatterer SAR Interferometry (PSInSAR) aims to identify coherent radar targets exhibiting high phase stability over the entire observation time period. These targets often correspond to point-wise, man-made objects widely … Permanent Scatterer SAR Interferometry (PSInSAR) aims to identify coherent radar targets exhibiting high phase stability over the entire observation time period. These targets often correspond to point-wise, man-made objects widely available over a city, but less present in non-urban areas. To overcome the limits of PSInSAR, analysis of interferometric data-stacks should aim at extracting geophysical parameters not only from point-wise deterministic objects (i.e., PS), but also from distributed scatterers (DS). Rather than developing hybrid processing chains where two or more algorithms are applied to the same data-stack, and results are then combined, in this paper we introduce a new approach, SqueeSAR, to jointly process PS and DS, taking into account their different statistical behavior. As it will be shown, PS and DS can be jointly processed without the need for significant changes to the traditional PSInSAR processing chain and without the need to unwrap hundreds of interferograms, provided that the coherence matrix associated with each DS is properly “squeezed” to provide a vector of optimum (wrapped) phase values. Results on real SAR data, acquired over an Alpine area, challenging for any InSAR analysis, confirm the effectiveness of this new approach.

Synthetic Aperture Radar Interferometry to Measure Earth’s Surface Topography and Its Deformation

2000-05-01

Roland Bürgmann , P. A. Rosen , E. J. Fielding

Synthetic aperture radar interferometry (InSAR) from Earth-orbiting spacecraft provides a new tool to map global topography and deformation of the Earth’s surface. Radar images taken from slightly different viewing directions … Synthetic aperture radar interferometry (InSAR) from Earth-orbiting spacecraft provides a new tool to map global topography and deformation of the Earth’s surface. Radar images taken from slightly different viewing directions allow the construction of digital elevation models of meter-scale accuracy. These data sets aid in the analysis and interpretation of tectonic and volcanic landscapes. If the Earth’s surface deformed between two radar image acquisitions, a map of the surface displacement with tens-of-meters resolution and subcentimeter accuracy can be constructed. This review gives a basic overview of InSAR for Earth scientists and presents a selection of geologic applications that demonstrate the unique capabilities of InSAR for mapping the topography and deformation of the Earth.

Synthetic aperture radar interferometry

2000-03-01

P. A. Rosen , S. Hensley , Ian Joughin +4 more

Synthetic aperture radar interferometry is an imaging technique for measuring the topography of a surface, its changes over time, and other changes in the detailed characteristic of the surface. By … Synthetic aperture radar interferometry is an imaging technique for measuring the topography of a surface, its changes over time, and other changes in the detailed characteristic of the surface. By exploiting the phase of the coherent radar signal, interferometry has transformed radar remote sensing from a largely interpretive science to a quantitative tool, with applications in cartography, geodesy, land cover characterization, and natural hazards. This paper reviews the techniques of interferometry, systems and limitations, and applications in a rapidly growing area of science and engineering.

A novel phase unwrapping method based on network programming

1998-05-01

E. Costantini

Phase unwrapping is the reconstruction of a function on a grid given its values mod 2/spl pi/. Phase unwrapping is a key problem in all quantitative applications of synthetic aperture … Phase unwrapping is the reconstruction of a function on a grid given its values mod 2/spl pi/. Phase unwrapping is a key problem in all quantitative applications of synthetic aperture radar (SAR) interferometry, but also in other fields. A new phase unwrapping method, which is a different approach from existing techniques, is described and tested. The method starts from the fact that the phase differences of neighboring pixels can be estimated with a potential error that is an integer multiple of 2/spl pi/. This suggests the formulation of the phase unwrapping problem as a global minimization problem with integer variables. Recognizing the network structure underlying the problem makes for an efficient solution. In fact, it is possible to equate the phase unwrapping problem to the problem of finding the minimum cost flow on a network, for the solution of which there exist very efficient techniques. The tests performed on real and simulated interferometric SAR data confirm the validity of the approach.

Polarimetric SAR speckle filtering and its implication for classification

1999-01-01

Jong-Sen Lee , M.R. Grunes , G. De Grandi

This paper proposes a new approach in polarimetric synthetic aperture radar (SAR) speckle filtering. The new approach emphasizes preserving polarimetric properties and statistical correlation between channels, not introducing crosstalk, and … This paper proposes a new approach in polarimetric synthetic aperture radar (SAR) speckle filtering. The new approach emphasizes preserving polarimetric properties and statistical correlation between channels, not introducing crosstalk, and not degrading the image quality. In the last decade, speckle reduction of polarimetric SAR imagery has been studied using several different approaches. All of these approaches exploited the degree of statistical independence between linear polarization channels. The preservation of polarimetric properties and statistical characteristics such as correlation between channels were not carefully addressed. To avoid crosstalk, each element of the covariance matrix must be filtered independently. This rules out current methods of polarimetric SAR filtering. To preserve the polarimetric signature, each element of the covariance matrix should be filtered in a way similar to multilook processing by averaging the covariance matrix of neighboring pixels. However, this must be done without the deficiency of smearing the edges, which degrades image quality and corrupts polarimetric properties. The proposed polarimetric SAR filter uses edge-aligned nonsquare windows and applies the local statistics filter. The impact of using this polarimetric speckle filtering on terrain classification is quite dramatic in boosting classification performance. Airborne polarimetric radar images are used for illustration.

An entropy based classification scheme for land applications of polarimetric SAR

1997-01-01

S.R. Cloude , Éric Pottier

The authors outline a new scheme for parameterizing polarimetric scattering problems, which has application in the quantitative analysis of polarimetric SAR data. The method relies on an eigenvalue analysis of … The authors outline a new scheme for parameterizing polarimetric scattering problems, which has application in the quantitative analysis of polarimetric SAR data. The method relies on an eigenvalue analysis of the coherency matrix and employs a three-level Bernoulli statistical model to generate estimates of the average target scattering matrix parameters from the data. The scattering entropy is a key parameter is determining the randomness in this model and is seen as a fundamental parameter in assessing the importance of polarimetry in remote sensing problems. The authors show application of the method to some important classical random media scattering problems and apply it to POLSAR data from the NASA/JPL AIRSAR data base.

Four-component scattering model for polarimetric SAR image decomposition

2005-07-27

Yoshio Yamaguchi , Takahiro Moriyama , Motoi Ishido +1 more

A four-component scattering model is proposed to decompose polarimetric synthetic aperture radar (SAR) images. The covariance matrix approach is used to deal with the nonreflection symmetric scattering case. This scheme … A four-component scattering model is proposed to decompose polarimetric synthetic aperture radar (SAR) images. The covariance matrix approach is used to deal with the nonreflection symmetric scattering case. This scheme includes and extends the three-component decomposition method introduced by Freeman and Durden dealing with the reflection symmetry condition that the co-pol and the cross-pol correlations are close to zero. Helix scattering power is added as the fourth component to the three-component scattering model which describes surface, double bounce, and volume scattering. This helix scattering term is added to take account of the co-pol and the cross-pol correlations which generally appear in complex urban area scattering and disappear for a natural distributed scatterer. This term is relevant for describing man-made targets in urban area scattering. In addition, asymmetric volume scattering covariance matrices are introduced in dependence of the relative backscattering magnitude between HH and VV. A modification of probability density function for a cloud of dipole scatterers yields asymmetric covariance matrices. An appropriate choice among the symmetric or asymmetric volume scattering covariance matrices allows us to make a best fit to the measured data. A four-component decomposition algorithm is developed to deal with a general scattering case. The result of this decomposition is demonstrated with L-band Pi-SAR images taken over the city of Niigata, Japan.

Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization

2001-02-01

Curtis W. Chen , H. A. Zebker

Interferometric radar techniques often necessitate two-dimensional (2-D) phase unwrapping, defined here as the estimation of unambiguous phase data from a 2-D array known only modulo 2pi rad. We develop a … Interferometric radar techniques often necessitate two-dimensional (2-D) phase unwrapping, defined here as the estimation of unambiguous phase data from a 2-D array known only modulo 2pi rad. We develop a maximum a posteriori probability (MAP) estimation approach for this problem, and we derive an algorithm that approximately maximizes the conditional probability of its phase-unwrapped solution given observable quantities such as wrapped phase, image intensity, and interferogram coherence. Examining topographic and differential interferometry separately, we derive simple, working models for the joint statistics of the estimated and the observed signals. We use generalized, nonlinear cost functions to reflect these probability relationships, and we employ nonlinear network-flow techniques to approximate MAP solutions. We apply our algorithm both to a topographic interferogram exhibiting rough terrain and layover and to a differential interferogram measuring the deformation from a large earthquake. The MAP solutions are complete and are more accurate than those of other tested algorithms.

Theory and design of interferometric synthetic aperture radars

1992-01-01

Ernesto Rodríguez , Jan M. L. Martin

Interferometric synthetic aperture radar (InSAR) is a method which may provide a means of estimating global topography with high spatial resolution and height accuracy. The paper presents a derivation of … Interferometric synthetic aperture radar (InSAR) is a method which may provide a means of estimating global topography with high spatial resolution and height accuracy. The paper presents a derivation of the signal statistics, an optimal estimator of the interferometric phase, and the expressions necessary to calculate the height-error budget. These expressions are used to derive methods of optimising the InSAR-system parameters, and are then used in a specific design example for a system to perform high-resolution global topographic mapping with a one-year mission lifetime, subject to current technological constraints. Finally, a Monte Carlo simulation of this InSAR system is performed to evaluate its performance for realistic topography. The results indicate that this system has the potential to satisfy the stringent accuracy and resolution requirements for geophysical use of global topographic data.

Linear and nonlinear terrain deformation maps from a reduced set of interferometric sar images

2003-10-01

Oscar Mora , Jordi J. Mallorquí , A. Broquetas

In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the … In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the displacement, the error of the digital elevation model (DEM) used to cancel the topographic terms, and the atmospheric artifacts from a reduced set of low spatial resolution interferograms. The pixel candidates are selected from those presenting a good coherence level in the whole set of interferograms and the resulting nonuniform mesh tessellated with the Delauney triangulation to establish connections among them. The linear component of movement and DEM error are estimated adjusting a linear model to the data only on the connections. Later on, this information, once unwrapped to retrieve the absolute values, is used to calculate the nonlinear component of movement and atmospheric artifacts with alternate filtering techniques in both the temporal and spatial domains. The method presents high flexibility with respect to the required number of images and the baselines length. However, better results are obtained with large datasets of short baseline interferograms. The technique has been tested with European Remote Sensing SAR data from an area of Catalonia (Spain) and validated with on-field precise leveling measurements.

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Satellite radar interferometry: Two‐dimensional phase unwrapping

1988-07-01

R. M. Goldstein , H. A. Zebker , Charles Werner

Interferometric synthetic aperture radar observations provide a means for obtaining high‐resolution digital topographic maps from measurements of amplitude and phase of two complex radar images. The phase of the radar … Interferometric synthetic aperture radar observations provide a means for obtaining high‐resolution digital topographic maps from measurements of amplitude and phase of two complex radar images. The phase of the radar echoes may only be measured modulo 2π; however, the whole phase at each point in the image is needed to obtain elevations. We present here our approach to “unwrapping” the 2π ambiguities in the two‐dimensional data set. We find that noise and geometrical radar layover corrupt our measurements locally, and these local errors can propagate to form global phase errors that affect the entire image. We show that the local errors, or residues, can be readily identified and avoided in the global phase estimation. We present a rectified digital topographic map derived from our unwrapped phase values.

A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms

2002-11-01

P. Berardino , G. Fornaro , R. Lanari +1 more

We present a new differential synthetic aperture radar (SAR) interferometry algorithm for monitoring the temporal evolution of surface deformations. The presented technique is based on an appropriate combination of differential … We present a new differential synthetic aperture radar (SAR) interferometry algorithm for monitoring the temporal evolution of surface deformations. The presented technique is based on an appropriate combination of differential interferograms produced by data pairs characterized by a small orbital separation (baseline) in order to limit the spatial decorrelation phenomena. The application of the singular value decomposition method allows us to easily "link" independent SAR acquisition datasets, separated by large baselines, thus increasing the observation temporal sampling rate. The availability of both spatial and temporal information in the processed data is used to identify and filter out atmospheric phase artifacts. We present results obtained on the data acquired from 1992 to 2000 by the European Remote Sensing satellites and relative to the Campi Flegrei caldera and to the city of Naples, Italy, that demonstrate the capability of the proposed approach to follow the dynamics of the detected deformations.

TOPSAR: Terrain Observation by Progressive Scans

2006-08-23

Francesco De Zan , Andrea Monti Guarnieri

In this paper, a novel (according to the authors' knowledge) type of scanning synthetic aperture radar (ScanSAR) that solves the problems of scalloping and azimuth-varying ambiguities is introduced. The technique … In this paper, a novel (according to the authors' knowledge) type of scanning synthetic aperture radar (ScanSAR) that solves the problems of scalloping and azimuth-varying ambiguities is introduced. The technique employs a very simple counterrotation of the radar beam in the opposite direction to a SPOT: hence, the name terrain observation with progressive scan (TOPS). After a short summary of the characteristics of the ScanSAR technique and its problems, TOPSAR, which is the technique of design, the limits, and a focusing technique are introduced. A synthetic example based on a possible future system follows.

Unsupervised classification using polarimetric decomposition and the complex Wishart classifier

1999-01-01

Jong-Sen Lee , M.R. Grunes , Thomas L. Ainsworth +3 more

The authors propose a new method for unsupervised classification of terrain types and man-made objects using polarimetric synthetic aperture radar (SAR) data. This technique is a combination of the unsupervised … The authors propose a new method for unsupervised classification of terrain types and man-made objects using polarimetric synthetic aperture radar (SAR) data. This technique is a combination of the unsupervised classification based on polarimetric target decomposition, S.R. Cloude et al. (1997), and the maximum likelihood classifier based on the complex Wishart distribution for the polarimetric covariance matrix, J.S. Lee et al. (1994). The authors use Cloude and Pottier's method to initially classify the polarimetric SAR image. The initial classification map defines training sets for classification based on the Wishart distribution. The classified results are then used to define training sets for the next iteration. Significant improvement has been observed in iteration. The iteration ends when the number of pixels switching classes becomes smaller than a predetermined number or when other criteria are met. The authors observed that the class centers in the entropy-alpha plane are shifted by each iteration. The final class centers in the entropy-alpha plane are useful for class identification by the scattering mechanism associated with each zone. The advantages of this method are the automated classification, and the interpretation of each class based on scattering mechanism. The effectiveness of this algorithm is demonstrated using a JPL/AIRSAR polarimetric SAR image.

Persistent Scatterer Interferometry: A review

2015-11-19

Michele Crosetto , Oriol Monserrat , María Cuevas-González +2 more

Persistent Scatterer Interferometry (PSI) is a powerful remote sensing technique able to measure and monitor displacements of the Earth’s surface over time. Specifically, PSI is a radar-based technique that belongs … Persistent Scatterer Interferometry (PSI) is a powerful remote sensing technique able to measure and monitor displacements of the Earth’s surface over time. Specifically, PSI is a radar-based technique that belongs to the group of differential interferometric Synthetic Aperture Radar (SAR). This paper provides a review of such PSI technique. It firstly recalls the basic principles of SAR interferometry, differential SAR interferometry and PSI. Then, a review of the main PSI algorithms proposed in the literature is provided, describing the main approaches and the most important works devoted to single aspects of PSI. A central part of this paper is devoted to the discussion of different characteristics and technical aspects of PSI, e.g. SAR data availability, maximum deformation rates, deformation time series, thermal expansion component of PSI observations, etc. The paper then goes through the most important PSI validation activities, which have provided valuable inputs for the PSI development and its acceptability at scientific, technical and commercial level. This is followed by a description of the main PSI applications developed in the last fifteen years. The paper concludes with a discussion of the main open PSI problems and the associated future research lines.

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Polarimetric Radar Imaging

2010-05-26

Jong-Sen Lee , Éric Pottier

Review: Regional land subsidence accompanying groundwater extraction

2011-08-25

Devin L. Galloway , Thomas J. Burbey

PCA Weight Determination-Based InSAR Baseline Optimization Method: A Case Study of the HaiKou Phosphate Mining Area in Kunming, Yunnan Province, China

2025-06-24

W. Y. Xu , Jingchun Zhou , Jinliang Wang +3 more | Remote Sensing

In InSAR processing, optimizing baselines by selecting appropriate interferometric pairs is crucial for ensuring interferogram quality and improving InSAR monitoring accuracy. However, in multi-temporal InSAR processing, the quality of interferometric … In InSAR processing, optimizing baselines by selecting appropriate interferometric pairs is crucial for ensuring interferogram quality and improving InSAR monitoring accuracy. However, in multi-temporal InSAR processing, the quality of interferometric pairs is constrained by spatiotemporal baseline parameters and surface scattering characteristics. Traditional selection methods, such as those based on average coherence thresholding, consider only a single factor and do not account for the interactions among multiple factors. This study introduces a principal component analysis (PCA) method to comprehensively analyze four factors: temporal baseline, spatial baseline, NDVI difference, and coherence, scientifically setting weights to achieve precise selection of interferometric pairs. Additionally, the GACOS (Generic Atmospheric Correction Online Service) atmospheric correction product is applied to further enhance data quality. Taking the Haikou Phosphate Mine area in Kunming, Yunnan, as the study area, surface deformation information was extracted using the SBAS-InSAR technique, and the spatiotemporal characteristics of subsidence were analyzed. The research results show the following: (1) compared with other methods, the PCA-based interferometric pair optimization method significantly improves the selection performance. The minimum value decreases to 0.248 rad, while the mean and standard deviation are reduced to 1.589 rad and 0.797 rad, respectively, effectively suppressing error fluctuations and enhancing the stability of the inversion; (2) through comparative analysis of the effective pixel ratio and standard deviation of deformation rates, as well as a comprehensive evaluation of the deformation rate probability density function (PDF) distribution, the PCA optimization method maintains a high effective pixel ratio while enhancing sensitivity to surface deformation changes, indicating its advantage in deformation monitoring in complex terrain areas; (3) the combined analysis of spatial autocorrelation (Moran’s I coefficient) and spatial correlation coefficients (Pearson and Spearman) verified the advantages of the PCA optimization method in maintaining spatial structure and result consistency, supporting its ability to achieve higher accuracy and stability in complex surface deformation monitoring. In summary, the PCA-based baseline optimization method significantly improves the accuracy of SBAS-InSAR in surface subsidence monitoring, fully demonstrating its reliability and stability in complex terrain areas, and providing a solid technical support for dynamic monitoring of surface subsidence in mining areas.

A Data Reconstruction Method for Inspection Mode in GBSAR Monitoring Using Sage–Husa Adaptive Kalman Filtering and RTS Smoothing

2025-06-24

Yaolong Qi , Jialiang Guo , Jiaxin Hui +4 more | Sensors

Ground-based synthetic aperture radar (GBSAR) has been widely used in the fields of early warning of geologic hazards and deformation monitoring of engineering structures due to its characteristics of high … Ground-based synthetic aperture radar (GBSAR) has been widely used in the fields of early warning of geologic hazards and deformation monitoring of engineering structures due to its characteristics of high spatial resolution, zero spatial baseline, and short revisit period. However, in the continuous monitoring process of GBSAR, due to the sudden failure of radar equipment, such as power failure, or the influence of alternating work between multiple regions, it often leads to discontinuous data collection, and this problem caused by missing data is collectively called “inspection mode”. The problem of missing data in the inspection mode not only destroys the spatial and temporal continuity of the data but also affects the accuracy of the subsequent deformation analysis. In order to solve this problem, in this paper, we propose a data reconstruction method that combines Sage–Husa Kalman adaptive filtering and the Rauch–Tung–Striebel (RTS) smoothing algorithm. The method is based on the principle of Kalman filtering and solves the problem of “model mismatch” caused by the fixed noise statistics of traditional Kalman filtering by dynamically adjusting the noise covariance to adapt to the non-stationary characteristics of the observed data. Subsequently, the Rauch–Tung–Striebel (RTS) smoothing algorithm is used to process the preliminary filtering results to eliminate the cumulative error during the period of missing data and recover the complete and smooth deformation time series. The experimental and simulation results show that this method successfully restores the spatial and temporal continuity of the inspection data, thus improving the overall accuracy and stability of deformation monitoring.

Analysis of the Driving Factors for Land Subsidence in the Northern Anhui Plain: A Case Study of Bozhou City

2025-06-22

Q. He , Hehe Liu , Wei Lu +1 more | Water

In recent years, land subsidence in the Northern Anhui Plain has become increasingly pronounced, posing serious risks to infrastructure and groundwater management. However, quantitative assessments of its driving mechanisms remain … In recent years, land subsidence in the Northern Anhui Plain has become increasingly pronounced, posing serious risks to infrastructure and groundwater management. However, quantitative assessments of its driving mechanisms remain limited. This study focuses on Bozhou, a typical resource-based city, and employs 186 Sentinel-1 SAR images and SBAS-based interferometric analysis to retrieve the spatiotemporal evolution of land subsidence from 2022 to 2024. Results show that the peak subsidence rate reaches 102 mm/year and has its major distribution in the central and eastern sectors of Bozhou. Temporally, the subsidence pattern shows an initial intensification followed by gradual stabilization. Furthermore, a GeoDetector-based analysis indicates that excessive groundwater extraction and coal mining are the dominant factors, with significant interactive enhancement effects. These findings provide crucial insights for the prevention and mitigation of land subsidence in resource-based cities.

P-Band PolInSAR Sub-Canopy Terrain Retrieval in Tropical Forests Using Forest Height-to-Unpenetrated Depth Mapping

2025-06-22

Chuanjun Wu , Jiali Hou , Peng Shen +3 more | Remote Sensing

For tropical forests characterized by tall and densely packed trees, even long-wavelength SAR signals may fail to achieve full penetration, posing a significant challenge for retrieving sub-canopy terrain using polarimetric … For tropical forests characterized by tall and densely packed trees, even long-wavelength SAR signals may fail to achieve full penetration, posing a significant challenge for retrieving sub-canopy terrain using polarimetric interferometric SAR (InSAR)(PolInSAR) techniques. This paper proposes a single-baseline PolInSAR-based correction method for sub-canopy terrain estimation based on a one-dimensional lookup table (LUT) that links forest height to unpenetrated depth. The approach begins by applying an optimal normal matrix approximation to constrain the complex coherence measurements. Subsequently, the difference between the PolInSAR Digital Terrain Model (DTM) derived from the Random Volume over Ground (RVoG) model and the LiDAR DTM is defined as the unpenetrated depth. A nonlinear iterative optimization algorithm is then employed to estimate forest height, from which a fundamental mapping between forest height and unpenetrated depth is established. This mapping can be used to correct the bias in sub-canopy terrain estimation based on the PolInSAR RVoG model, even with only a small amount of sparse LiDAR DTM data. To validate the effectiveness of the method, experiments were conducted using fully polarimetric P-band airborne SAR data acquired by the European Space Agency (ESA) during the AfriSAR campaign over the Mabounie region in Gabon, Africa, in 2016. The experimental results demonstrate that the proposed method effectively mitigates terrain estimation errors caused by insufficient signal penetration or the limitation of single-interferometric geometry. Further analysis reveals that the availability of sufficient and precise forest height data significantly improves sub-canopy terrain accuracy. Compared with LiDAR-derived DTM, the proposed method achieves an average root mean square error (RMSE) of 5.90 m, representing an accuracy improvement of approximately 38.3% over traditional RVoG-derived InSAR DTM retrieval. These findings further confirm that there exist unpenetrated phenomena in single-baseline low-frequency PolInSAR-derived DTMs of tropical forested areas. Nevertheless, when sparse LiDAR topographic data is available, the integration of fully PolInSAR data with LUT-based compensation enables improved sub-canopy terrain retrieval. This provides a promising technical pathway with single-baseline configuration for spaceborne missions, such as ESA’s BIOMASS mission, to estimate sub-canopy terrain in tropical-rainforest regions.

Land Subsidence Susceptibility Modelling in Attica, Greece: A Machine Learning Approach Using InSAR and Geospatial Data

2025-06-21

Vishnuvardhan Reddy Yaragunda , Divya Sekhar Vaka , Emmanouil Oikonomou | Earth

Land subsidence significantly threatens urban infrastructure, agricultural productivity, and environmental sustainability. This study develops a land subsidence susceptibility model by integrating Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) … Land subsidence significantly threatens urban infrastructure, agricultural productivity, and environmental sustainability. This study develops a land subsidence susceptibility model by integrating Small Baseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) data with key geospatial factors using machine learning approaches. The study focuses on the Attica prefecture, Greece, and utilizes SBAS InSAR data from 2015 to 2021 to extract ground deformation velocities by classifying them into four susceptibility levels: stable, low, moderate, and high. The susceptibility results indicate that stable zones constitute 58.2% of the study area, followed by low (27.2%), moderate (11.2%), and high susceptibility zones (3.4%), predominantly concentrated in areas undergoing hydrological stress and urbanization. Random Forest (RF) and XGBoost (XGB) models incorporate a comprehensive set of causal factors, including slope, aspect, land use, groundwater level, geology, and rainfall. The evaluation of the models includes accuracy metrics and confusion matrices. The XGB model achieved the highest performance, recording an accuracy of 94%, with well-balanced predictions across all susceptibility classes. Addressing class imbalance during model training improved the recall of minority classes, though with slight trade-offs in precision. Feature importance analysis identifies proximity to streams, land use, aspect, rainfall, and groundwater extraction as the most influential factors driving subsidence susceptibility. This methodology demonstrates high reliability and robustness in predicting land subsidence susceptibility, providing critical insights for land-use planning and mitigation strategies. These findings establish a scalable framework for regional and global applications, contributing to sustainable land management and risk reduction efforts.

Monitoring of Ground Deformation in Mining Region Based on Time-series InSAR

2025-06-20

D. Yu | Theoretical and Natural Science

Tailings ponds, essential for mining operations yet potential geological hazards, require rigorous safety monitoring. Conventional ground deformation methods are inadequate for contemporary precision and spatial coverage standards. InSAR technology, offering … Tailings ponds, essential for mining operations yet potential geological hazards, require rigorous safety monitoring. Conventional ground deformation methods are inadequate for contemporary precision and spatial coverage standards. InSAR technology, offering millimeter-level accuracy and robust spatio-temporal continuity, has become vital for monitoring deformation in mining areas. This study examines InSAR-based monitoring of ground deformation at the Baizhangzi Gold Mine's tailings pond and collapse zone in Lingyuan, Liaoning, China. Utilizing SBAS-InSAR, this study processes SAR image data for comprehensive analysis. Findings indicate that while the tailings pond remains stable, the collapse zone experiences significant subsidence, primarily attributed to anthropogenic mining activities. The results demonstrate that SBAS-InSAR is effective for monitoring subsidence in mining regions, contributing to geological hazard mitigation and serving as a reference for analogous mining sites.

Millimeter ground deformation retrieving from high-resolution PAZ SAR images with a combined correction of unwrapping and long-wavelength errors: A case study in Alcoy, Spain

2025-06-20

Xiaojie Liu , Roberto Tomás , Chaoying Zhao +2 more | Remote Sensing of Environment

First three-dimensional imaging experiment of Chinese commercial SAR satellite Fucheng-1

2025-06-20

Hui Bi , Shuang Jin , Weihao Xu +7 more | Science China Information Sciences

Absolute Vertical Accuracy of ArcticDEM and Copernicus DEM and In-Situ GNSS Measurements

2025-06-19

I. M. Aleshin , К. И. Холодков , F. V. Perederin +2 more | Research Square (Research Square)

<title>Abstract</title> This paper discusses the vertical accuracy of digital elevation models (DEMs) along public roads for three modern global DEMs. Validation is performed with <italic>in-situ</italic> Global Navigation Satellite System (GNSS) … <title>Abstract</title> This paper discusses the vertical accuracy of digital elevation models (DEMs) along public roads for three modern global DEMs. Validation is performed with <italic>in-situ</italic> Global Navigation Satellite System (GNSS) measurements. Due to the fact that the specifications of these DEMs indicate very high absolute vertical accuracy (up to 4 meters at best), the verification was performed without registering the DEMs to local ground control points. The study highlights that these DEMs can be used in a variety of applications without the need for mandatory local registration.

Spatiotemporal atmospheric phase mitigation in multi-temporal InSAR for low-frequency localized deformation monitoring

2025-06-18

Long Jiang , Ligong Yang , Qiming Zeng +1 more | International Journal of Remote Sensing

Multi-scale deformation monitoring and characterization of large-span railway bridge by joint satellite/ground-based InSAR and BDS

2025-06-17

Xinyi Li , Lv Zhou , Jun Ma +5 more | Measurement

ST-YOLOv8: Small-Target Ship Detection in SAR Images Targeting Specific Marine Environments

2025-06-13

Fei Gao , Yang Tian , Yongliang Wu +1 more | Applied Sciences

Synthetic Aperture Radar (SAR) image ship detection faces challenges such as distinguishing ships from other terrains and structures, especially in specific marine complex environments. The motivation behind this work is … Synthetic Aperture Radar (SAR) image ship detection faces challenges such as distinguishing ships from other terrains and structures, especially in specific marine complex environments. The motivation behind this work is to enhance detection accuracy while minimizing false positives, which is crucial for applications like defense vessel monitoring and civilian search and rescue operations. To achieve this goal, we propose several architectural improvements to You Only Look Once version 8 Nano (YOLOv8n) and present Small Target-YOLOv8(ST-YOLOv8)—a novel lightweight SAR ship detection model based on the enhance YOLOv8n framework. The C2f module in the backbone’s transition sections is replaced by the Conv_Online Reparameterized Convolution (C_OREPA) module, reducing convolutional complexity and improving efficiency. The Atrous Spatial Pyramid Pooling (ASPP) module is added to the end of the backbone to extract finer features from smaller and more complex ship targets. In the neck network, the Shuffle Attention (SA) module is employed before each upsampling step to improve upsampling quality. Additionally, we replace the Complete Intersection over Union (C-IoU) loss function with the Wise Intersection over Union (W-IoU) loss function, which enhances bounding box precision. We conducted ablation experiments on two widely used multimodal SAR datasets. The proposed model significantly outperforms the YOLOv8n baseline, achieving 94.1% accuracy, 82% recall, and 87.6% F1 score on the SAR Ship Detection Dataset (SSDD), and 92.7% accuracy, 84.5% recall, and 88.1% F1 score on the SAR Ship Dataset_v0 dataset (SSDv0). Furthermore, the ST-YOLOv8 model outperforms several state-of-the-art multi-scale ship detection algorithms on both datasets. In summary, the ST-YOLOv8 model, by integrating advanced neural network architectures and optimization techniques, significantly improves detection accuracy and reduces false detection rates. This makes it highly suitable for complex backgrounds and multi-scale ship detection. Future work will focus on lightweight model optimization for deployment on mobile platforms to broaden its applicability across different scenarios.

Quantitative understanding of the contribution of factors on land subsidence with maximal information coefficient: a case study in Tongzhou, Beijing, China

2025-06-13

Zhuangzhuang Liu , Guangyao Duan , Jijun He +3 more | Groundwater for Sustainable Development

Applications of InSAR for Monitoring Post-Wildfire Ground Surface Displacements

2025-06-13

Ryan van der Heijden , Ehsan Ghazanfari , Donna M. Rizzo +2 more | Remote Sensing

Wildfires pose a significant threat to the natural and built environment and may alter the hydrologic cycle in burned areas increasing the risk of flooding, erosion, debris flows, and shallow … Wildfires pose a significant threat to the natural and built environment and may alter the hydrologic cycle in burned areas increasing the risk of flooding, erosion, debris flows, and shallow landslides. In this paper, we investigate the feasibility of using differential interferometric synthetic aperture radar (DInSAR) to interpret changes in ground surface elevation following the 2017 Eagle Creek Wildfire in Oregon, USA. We show that DInSAR is capable of measuring ground surface displacements in burned areas not obscured by vegetation cover and that interferometric coherence can differentiate between areas that experienced different burn severities. The distribution of projected vertical displacement was analyzed, suggesting that different areas experience variable rates of change, with some showing little to no change for up to four years after the fire. Comparison of the projected vertical displacements with cumulative precipitation and soil moisture suggests that increases in precipitation and soil moisture are related to periods of increased vertical displacement. The findings of this study suggest that DInSAR may have value where in situ instrumentation is infeasible and may assist in prioritizing areas at high-risk of erosion or other changes over large geographical extents and measurement locations for deployment of instrumentation.

Dendritic computing with differential evolution for unsupervised synthetic aperture radar image change detection

2025-06-11

Meng Jia , Xiaoying Lou , Zhiqiang Zhao +1 more | International Journal of Remote Sensing

Improved application of the split-spectrum method to L-band interferograms for ionospheric phase mitigation: a practical recipe

2025-06-06

Shogo Nagaoka , Youichiro Takada , Yu Morishita | Earth Planets and Space

SHAP-enhanced interpretive MGTWR-CNN-BILSTM-AM framework for predicting surface subsidence: a case study of Shanghai municipality

2025-06-05

Long Wen-Jiang , Xuexiang Yu , Zhu Ming-Fei +3 more | Scientific Reports

Sentinel-1 SAR modeling of a highway in a landslide-susceptible area

2025-06-03

Roberto Monti , Mirko Reguzzoni , Osmari Aponte | Engineering Research Express

Abstract Highways are an essential component of the global transportation network, significantly reducing commute times and facilitating connectivity within each nation. These infrastructures have been constructed over several decades, necessitating … Abstract Highways are an essential component of the global transportation network, significantly reducing commute times and facilitating connectivity within each nation. These infrastructures have been constructed over several decades, necessitating continuous monitoring for their preservation and safety. Traditional techniques, such as extensometers, accelerometers and geodetic surveys are widely employed for localized monitoring of critical elements. In contrast, satellite-based methods, which are more recent, offer a broader perspective. Among these, SAR is particularly noteworthy due to its continuous spatial coverage of the entire infrastructure, albeit coarser in time. This coverage eliminates the limitations imposed by the placement of in-situ instruments. This study aims to define a reliable methodology for modeling highways using Sentinel-1 SAR data, which presents challenges and limitations due to its medium spatial resolution. The proposed processing workflow includes several steps: preprocessing of level-1 SAR data using SNAP libraries, application of the Persistent Scatterer Interferometry technique by StaMPS, validation of the resulting displacement time series exploiting in-situ GNSS measurements, and interpolation of the raw displacements in both space and time using cubic splines. This interpolation involves an iterative selection of the number of splines and rejection of outliers. The final deformation model is then estimated along the road centerline, as the radar cannot distinguish between the two lanes. Additionally, the area under study presents challenges due to its complex orography and the presence of multiple active landslides. Satisfactory results are achieved, with displacement models that are coherent across different monitoring techniques and reasonably capture the deformation trends of various road sections.

Mapping of paddy field by Sentinel-1 SAR images and cadastre data in Yunlin, Taiwan

2025-06-02

Jui-Han Yang , Kuo‐Hsin Tseng , Shu‐Ling Chen +4 more | International Journal of Remote Sensing

An Efficient Eigenvalue Decomposition-Based Attention Network for Polarimetric Synthetic Aperture Radar Image Classification

2025-06-01

Maryam Imani , Samsung Lim | Advances in Space Research

Ground subsidence evolution and groundwater variation in the middle route of south to north water diversion project

2025-06-01

Rui Zhang , Ting Wang , Guoxiang Liu +5 more | Scientific Reports

AltiCube+: A low-cost long fixed-baseline radar altimeter solution based on cubesats on-orbit assembly

2025-06-01

Jian Guo , P. Hoogeboom , Paco López‐Dekker +6 more | Acta Astronautica

Research on a Prediction Model Based on a Newton–Raphson-Optimization–XGBoost Algorithm Predicting Environmental Electromagnetic Effects for an Airborne Synthetic Aperture Radar

2025-05-29

Yan Shen , Yazhou Chen , Yuming Wang +2 more | Electronics

Airborne synthetic aperture radar (SAR) serves as critical battlefield reconnaissance equipment, yet it remains vulnerable to electromagnetic interference (EMI) in combat environments, leading to image-quality degradation. To address this challenge, … Airborne synthetic aperture radar (SAR) serves as critical battlefield reconnaissance equipment, yet it remains vulnerable to electromagnetic interference (EMI) in combat environments, leading to image-quality degradation. To address this challenge, this study proposes an EMI-effect prediction framework for airborne SAR electromagnetic environments, based on the Newton–Raphson-based optimization (NRBO) and XGBoost algorithms. The methodology enables interference-level prediction through electromagnetic signal parameters obtained from reconnaissance operations, providing operational foundations with which SAR systems can mitigate the impacts of EMI. A laboratory-based airborne SAR EMI test system was developed to establish mapping relationships between EMI signal parameters and SAR imaging performance degradation. This experimental platform facilitated EMI-effect investigations across diverse interference scenarios. An evaluation methodology for SAR image degradation caused by EMI was formulated, revealing the characteristic influence patterns of different interference signals in the context of SAR imagery. The NRBO–XGBoost framework was established through algorithmic integration of Newton–Raphson search principles with trap avoidance mechanisms from the Newton–Raphson optimization algorithm, optimizing the XGBoost hyperparameters. Utilizing the developed test system, comprehensive EMI datasets were constructed under varied interference conditions. Comparative experiments demonstrated the NRBO–XGBoost model’s superior accuracy and generalization performance relative to conventional prediction approaches.

Deep learning-based InSAR time-series deformation prediction in coal mine areas

2025-05-29

Chuanzeng Shu , Zhiguo Meng , Ying Yang +4 more | Geo-spatial Information Science

Land Subsidence Analysis Using Machine Learning Algorithm Random Forest Method in DKI Jakarta

2025-05-28

Camelia Nur Hidayah , Panca Dewi Pamungkasari , Sari Ningsih +3 more | Green Intelligent Systems and Applications

Land subsidence is an environmental phenomenon that causes the earth's surface to decline gradually or suddenly. Land subsidence occurred in DKI Jakarta due to various factors such as excessive groundwater … Land subsidence is an environmental phenomenon that causes the earth's surface to decline gradually or suddenly. Land subsidence occurred in DKI Jakarta due to various factors such as excessive groundwater exploitation, infrastructure loads, and geological conditions. The purpose of this study was to analyze land subsidence in DKI Jakarta and the distribution of existing land subsidence. The results were compared with previous findings using PS-InSAR. Land subsidence was predicted using the Random Forest algorithm. Random Forest, as a type of machine learning, was able to reduce noise and minimize the impact of overfitting through ensemble techniques. Researchers used four metrics, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), R², and Kling-Gupta Efficiency (KGE), to assess the accuracy of the algorithm. The analysis results of land subsidence in DKI Jakarta using Random Forest aligned with the PS-InSAR method. It was observed that areas experiencing land subsidence were predominantly in North and West Jakarta compared to other regions. Furthermore, the prediction of land subsidence using the 2017–2021 dataset indicated a decrease of up to -60 mm/year.