IEEE Transactions on Geoscience and Remote Sensing

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Front Cover

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Presents the front cover for this issue of the publication.

IEEE Transactions on Geoscience and Remote Sensing publication information

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Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

Table of contents

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Presents the table of contents for this issue of the publication.

The Parallel SBAS Approach for Sentinel-1 Interferometric Wide Swath Deformation Time-Series Generation: Algorithm Description and Products Quality Assessment

Sun, 09/01/2019 - 00:00
We present an advanced differential synthetic aperture radar (SAR) interferometry (DInSAR) processing chain, based on the Parallel Small BAseline Subset (P-SBAS) technique, for the efficient generation of deformation time series from Sentinel-1 (S-1) interferometric wide (IW) swath SAR data sets. We first discuss an effective solution for the generation of high-quality interferograms, which properly accounts for the peculiarities of the terrain observation with progressive scans (TOPS) acquisition mode used to collect S-1 IW SAR data. These data characteristics are also properly accounted within the developed processing chain, taking full advantage from the burst partitioning. Indeed, such data structure represents a key element in the proposed P-SBAS implementation of the S-1 IW processing chain, whose migration into a cloud computing (CC) environment is also envisaged. An extensive experimental analysis, which allows us to assess the quality of the obtained interferometric products, is presented. To do this, we apply the developed S-1 IW P-SBAS processing chain to the overall archive acquired from descending orbits during the March 2015–April 2017 time span over the whole Italian territory, consisting in 2740 S-1 slices. In particular, the quality of the final results is assessed through a large-scale comparison with the GPS measurements relevant to nearly 500 stations. The mean standard deviation value of the differences between the DInSAR and the GPS time series (projected in the radar line of sight) is less than 0.5 cm, thus confirming the effectiveness of the implemented solution. Finally, a discussion about the performance achieved by migrating the developed processing chain within the Amazon Web Services CC environment is addressed, highlighting that a two-year data set relevant to a standard S-1 IW slice can be reliably processed in about 30 h.The presented results demonstrate the capability of the implemented P-SBAS approach to efficien- ly and effectively process large S-1 IW data sets relevant to extended portions of the earth surface, paving the way to the systematic generation of advanced DInSAR products to monitor ground displacements at a very wide spatial scale.

Estimation of Source Wavelet From Seismic Traces Using Groebner Bases

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An accurate and effective seismic wavelet estimation technique has extreme significance in the seismic data processing for analyzing the earth’s subsurface layer information. The seismic wavelet to be determined is modeled as a moving average (MA) process and assumed to be driven by a zero mean, non-Gaussian, statistically independent, and identically distributed (IID) process. In order to estimate the MA model parameter from the observed noisy seismic signal, we pose this as a blind system identification (BSI) problem. In the BSI, a set of multivariate polynomial equations is obtained by matching higher order cumulant of observed noisy data with a higher order moment of blind system’s impulse response. The Groebner bases that form the solution to this set of equations are obtained using the proposed algorithm. Numerical results demonstrate that the proposed method has a lower estimation error as compared to the previously reported methods.

A Shadowing Mitigation Approach for Sea State Parameters Estimation Using X-Band Remotely Sensing Radar Data in Coastal Areas

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A novel procedure based on filtering and interpolation approaches is proposed to estimate the sea state parameters, including significant wave height, peak wave direction, peak period, peak wavenumber, and peak wavelength in shallow waters using the X-band marine radars. The method compensates the distortions introduced by the radar acquisition process and the power decay of the radar signal along the distance applying image-enhancement techniques instead of empirical and semiempirical calibration methods that use signal-to-noise ratio and in situ measurements as external references. To determine the threshold value for the interpolation approach, the influence of the antenna height on shadowing modulation effects is examined through performing an analysis of variance (ANOVA) that uses data from two X-band radars deployed at 10 and 20 m above MSL. ANOVA results reveal that it is possible to explain the increment of intensities affected by shadowing throughout the distance using an adaptive threshold retrieved from a third-order polynomial function of the mean radar cross section (RCS). Finally, an X-band radar is installed at 13 m above MSL to test the proposed technique. During measurements, the wind and wave conditions varied, and the antenna-look direction remained constant. Errors for $H_{s}$ , $theta _{p}$ , and $T_{p}$ calculated as the difference between estimated and true data show a mean bias and a relative value of 0.05 m (2.72%), 1.52° (5.94%), and 0.15 s (1.67%), respectively. The directional and wave energy spectra derived from radar estimates, acoustic wave and current, ADVs record, as well as JONSWAP formulation are presented to illustrate the i- provement resulting from the proposed method over the frequency domain.

A Transverse Spectrum Deconvolution Technique for MIMO Short-Range Fourier Imaging

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The growing need for high-performance imaging tools for terrorist threat detection and medical diagnosis has led to the development of new active architectures in the microwave and millimeter range. Notably, multiple-input multiple-output systems can meet the resolution constraints imposed by these applications by creating large, synthetic radiating apertures with a limited number of antennas used independently in transmitting and receiving signals. However, the implementation of such systems is coupled with strong constraints in the software layer, requiring the development of reconstruction techniques capable of interrogating the observed scene by optimizing both the resolution of images reconstructed in two or three dimensions and the associated computation times. In this paper, we first review the formalisms and constraints associated with each application by taking stock of efficient processing techniques based on spectral decompositions, and then, we present a new technique called the transverse spectrum deconvolution range migration algorithm allowing us to carry out reconstructions that are both faster and more accurate than with conventional Fourier domain processing techniques. This paper is particularly relevant to the development of new computational imaging tools that require, even more pronouncedly than in the case of conventional architectures, fast image computing techniques despite a very large number of radiating elements interrogating the scene to be imaged.

Effects of Wind Wave Spectra on Radar Backscatter From Sea Surface at Different Microwave Bands: A Numerical Study

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Wind wave spectrum describes the quasi-periodic nature of the ocean surface oscillations and plays an indispensable role in the study of microwave electromagnetic scattering from sea surface. A reliable spectrum model suitable for radar cross section (RCS) predictions at different radar frequencies is desired. This paper evaluated the performances of five common spectrum models (i.e., Fung spectrum, Durden–Vesecky spectrum, Apel spectrum, Elfouhaily spectrum, and the newest version of Hwang spectrum, H18) on the normalized radar backscattering cross section (NRBCS) simulations based on advanced integral equation model (AIEM) at L-, C-, X-, and Ku-bands versus incidence angle, wind direction, and wind speed by comparing with the model and measured data for validation. These results indicate no single wave spectrum of them is satisfying for all the four radar frequencies, e.g., Apel and H18 spectra are better for L- and C-bands, Apel spectrum for X-band, and Elfouhaily and H18 spectra for Ku-band. Given this, three average composite spectrum models are constructed using different spectral models (i.e., all five spectra, Apel + Elfouhaily + H18, and Apel + H18) to simulate NRBCSs, similar to that of the individual spectrum model. It is concluded that the combination of Apel and H18 spectra overall performs best among the individual one and other composited spectra in like-polarized NRBCSs versus incidence angles, wind directions, and wind speeds, for wind speed greater than 30 m/s where the combination of the five spectra work well at Ku-band.

OS-Flow: A Robust Algorithm for Dense Optical and SAR Image Registration

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Coregistration of high-resolution optical and synthetic aperture radar (SAR) images is still an ongoing problem due to different imaging mechanisms of two kinds of remote sensing images. In this paper, we propose an optical flow-based algorithm to solve the dense registration problem [optical-to-SAR (OS)-flow]. Unlike parametric registration methods that estimate a transformation model, OS-flow aims to find pixelwise correspondences between optical and SAR images. Specifically, two frameworks of OS-flow, a global method and a local method, are proposed. Due to the drastic differences between SAR and optical images, two dense feature descriptors, rather than the raw intensities, are utilized to retain the constancy assumption in optical flow estimation. Considering the inherent properties of the two images, two dense descriptors are constructed using consistent gradient computation. After satisfying the constancy assumption, the global method estimates the flow map by optimizing an objective function, and the local method iteratively estimates the flow vector in a local neighborhood. Both methods use the coarse-to-fine matching strategy to address large displacements and reduce the computational cost. Experiments on several optical-to-SAR image pairs in various scenarios show that the proposed methods have a strong ability to match across optical and SAR images and outperform other state-of-the-art methods in terms of registration accuracy.

MODIS Reflective Solar Bands On-Orbit Calibration and Performance

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The design of the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument was driven by the scientific community’s desire to have near-daily global coverage at moderate resolution (~1km) with comprehensive spectral coverage from visible to long-wave infrared wavelengths. Since their launches in 1999 and 2002, respectively, the Terra and Aqua MODIS instruments have made continuous global observations and generated numerous data products to help users worldwide with their studies of the Earth’s system and its short- and long-term changes. The 20 reflective solar bands (RSBs) with wavelengths from 0.41 to $2.2~mu text{m}$ collect data at three nadir spatial resolutions: 250 m, 500 m, and 1 km. The solar diffuser (SD) coupled with the SD stability monitor (SDSM) provides a reflectance-based calibration on-orbit. In addition, lunar observations and response trends from pseudoinvariant desert sites are used to characterize the response versus scan-angle changes on-orbit. This paper provides a brief overview of MODIS RSB calibration algorithms, as implemented in the latest Level 1B version 6.1, operational activities, on-orbit performance, remaining challenges, and potential improvements. Results from the SD and SDSM measurements show a wavelength and mirror-side-dependent degradation in RSB responses, with the largest degradation at the shortest wavelengths, particularly for Terra MODIS. Aqua MODIS has experienced far less degradation of its optics and on-board calibrators compared with Terra MODIS, resulting in an overall better performance. With the exception of Aqua band 6, there have been no new noisy or inoperable detectors in the RSB of either instrument during postlaunch operations. As the instruments age and continue to endure the space environment, the detectors and the optical systems degrade. The challenges associated wit- incorporating these on-orbit changes to ensure a production of high-quality calibrated L1B data products are also discussed in this paper.

High-Frequency Ionospheric Monitoring System for Over-the-Horizon Radar in Canada

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The Canadian Department of National Defence (DND) is developing an experimental over-the-horizon radar (OTHR) with the potential for surveillance of Canada. Because of dynamically changing ionospheric conditions in the Earth’s high-latitude and polar regions, the operating OTHR transmission frequency and elevation angle need to be adjusted regularly to maintain constant illumination of downrange targets. In this paper, the feasible operating frequency and elevation angle radar parameters are determined for short- and long-range OTHR operation using 3-D ionosphere ray-tracing simulations. Together, the collection of all feasible radar configurations forms a characteristic profile which shifts and deforms as factors such as the time of day, season, and solar activity are varied. The range of operating frequencies and elevation angles obtained from this paper will aid developing the transmitter and receiver antenna layouts for experimental OTHR configurations in the poorly understood high-latitude and polar regions. These methods will also help to form the basis of the frequency monitoring systems (FMS) that will control the configuration of these polar OTHR systems in real time.

A Ship ISAR Imaging Algorithm Based on Generalized Radon-Fourier Transform With Low SNR

Sun, 09/01/2019 - 00:00
Existing ship inverse synthetic aperture radar (ISAR) imaging algorithms are not applicable, when the signal-to-noise ratio (SNR) is low, for the translational motion that cannot be well compensated by existing algorithms. To achieve ship ISAR imaging with low SNR, a ship ISAR imaging algorithm based on the generalized radon-Fourier transform (GRFT) is proposed in this paper. Considering not only the rotational motion but also the translational motion between the radar and the ship, the proposed algorithm uses the GRFT to simultaneously compensate the time-variant range envelopes and the Doppler phase. Thus, the signal coherence is fully utilized, and the coherent integration of the ship’s multicomponent echo signal is realized. Subsequently, to overcome the problem of the heavy computational load and improve the efficiency of the proposed algorithm, the scheme of cascaded GRFTs that consists of the coarse GRFT and the subsequent fine GRFT is adopted. The coarse GRFT with large search ranges and intervals is aimed at obtaining the real ranges of ship scatter points’ motion parameters. Based on the coarse GRFT result, the fine GRFT with small search ranges and intervals is performed to efficiently obtain the coherent integration result. Then, based on the coherent integration result, the constant false alarm rate (CFAR) detection is performed to obtain the desired scatter points and their amplitudes and motion parameters, and the multicomponent signal is reconstructed. Finally, based on the reconstructed multicomponent signal, the high-quality instantaneous ship ISAR image can be obtained. Computer simulations and experiment results validate the effectiveness of the proposed algorithm.

CoSMIR Performance During the GPM OLYMPEX Campaign

Sun, 09/01/2019 - 00:00
The airborne Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) has participated in the Global Precipitation Measurement (GPM) Olympic Mountains Experiment (OLYMPEX) from November to December, 2015, with great success. With similar channels as that of the GPM Microwave Imager (GMI) at 89–183 GHz, CoSMIR served as a proxy for GMI by flying onboard the DC-8 Aircraft for a total of 17 science flights, collecting over 72 h of observations. The high-quality, calibrated brightness temperature data set is the result of several improvements made to CoSMIR prior to OLYMPEX to make the instrument more reliable. This paper describes these improvements and gives a detailed summary of the CoSMIR measurements obtained from OLYMPEX. CoSMIR experienced minor performance issues during the campaign, most of them were not excessive and only resulted in a loss of approximately 4 h of data for the entire campaign. Performance issues are discussed and shown how they were mitigated to achieve a quality data set. Comparisons of CoSMIR and GMI observations are presented to show that the CoSMIR measurements agree well with GMI. The CoSMIR data set is publicly available as a part of the OLYMPEX data suite and can reliably be used in the GPM algorithm development and related studies.

Sentinel-2 Sharpening Using a Reduced-Rank Method

Sun, 09/01/2019 - 00:00
Recently, the Sentinel-2 (S2) satellite constellation was deployed for mapping and monitoring the Earth environment. Images acquired by the sensors mounted on the S2 platforms have three levels of spatial resolution: 10, 20, and 60 m. In many remote sensing applications, the availability of images at the highest spatial resolution (i.e., 10 m for S2) is often desirable. This can be achieved by generating a synthetic high-resolution image through data fusion. To this end, researchers have proposed techniques exploiting the spectral/spatial correlation inherent in multispectral data to sharpen the lower resolution S2 bands to 10 m. In this paper, we propose a novel method that formulates the sharpening process as a solution to an inverse problem. We develop a cyclic descent algorithm called S2Sharp and an associated tuning parameter selection algorithm based on generalized cross validation and Bayesian optimization. The tuning parameter selection method is evaluated on a simulated data set. The effectiveness of S2Sharp is assessed experimentally by comparisons to state-of-the-art methods using both simulated and real data sets.

Robust Band-Dependent Spatial-Detail Approaches for Panchromatic Sharpening

Sun, 09/01/2019 - 00:00
Pansharpening refers to the fusion of a multispectral (MS) image with a finer spectral resolution but coarser spatial resolution than a panchromatic (PAN) image. The classical pansharpening problem can be dealt with component substitution or multiresolution analysis techniques. One of the most notable approaches in the former class is the band-dependent spatial-detail (BDSD) method. It has been shown state-of-the-art performance, in particular, when the fusion of four band data sets is addressed. However, new sensors, such as the WorldView-2/-3 ones, usually acquire MS images with more than four spectral bands to be fused with the PAN image. The BDSD method has shown limitations in performance in these cases. Thus, in this paper, several BDSD-based approaches are provided to solve this issue getting a robustness of the BDSD with respect to the spectral bands to be fused. The experimental results conducted both at reduced and at full resolutions on four real data sets acquired by the IKONOS, the QuickBird, the WorldView-2, and the WorldView-3 sensors demonstrate the validity of the proposed approaches against the benchmark.

Full-Polarization Bistatic Scattering From an Inhomogeneous Rough Surface

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This paper examines the properties of bistatic scattering from an inhomogeneous rough surface, which, in this paper, is modeled by the transitional layer as a function of depth. The lower medium of the rough surface is horizontally uniform but vertically inhomogeneous. Both linear and circular polarizations are investigated in light of the dependences of transition rate, background dielectric constant, and surface roughness. The presence of dielectric inhomogeneity generally leads to several features that do not appear in the homogeneous surface, such as the scattering coefficient on the whole scattering plane is enhanced; the dynamic range of HH and VV over the azimuth plane is reduced; HV can be greater than VH; and the difference of LR and RR is decreased. With the increasing transition rate, the scattering coefficients for both the linear and circular polarizations are enhanced. As the background dielectric constant increases, the scattering responses of the linear and circular polarizations are quite different. For the linear polarization, HH exhibits a stronger angular dependence; VV reduces in the forward region and enhances notably in the backward region; and HV decreases but VH increases. For circular polarizations, the cross-polarized LR increases in the backward region but decreases in the forward region, and the copolarized RR enhances on the whole scattering plane. With the increasing surface roughness, the scattering coefficient becomes more evenly distributed over the entire scattering plane.

Ship Detection Based on Complex Signal Kurtosis in Single-Channel SAR Imagery

Sun, 09/01/2019 - 00:00
Recent studies have shown that complex information in single-channel synthetic aperture radar (SAR) imagery has practically always been underrated. This improves the perception of their potential for ocean monitoring. Based on the in-depth interpretation of complex signal kurtosis (CSK), this paper proposes a new ship detection method based on CSK in single-channel SAR imagery. The proposed method consists of two main parts, i.e., region proposal and target identification. The basic idea is to first detect potential ship locations based on the region proposal. Then, the final ship target is acquired based on the target identification. Compared to conventional methods based on detected products, e.g., the constant false alarm rate (CFAR), the proposed method has three advantages. First, CSK can take advantage of both non-Gaussianity and noncircularity, which is the fundamental concept distinguishing complex signal analysis from the real case. Second, the proposed method can be intrinsically free of false alarms caused by radio frequency interference (RFI). Finally, the proposed method can avoid missing detection in dense target situations. This methodology has been demonstrated over significant data sets acquired from Sentinel-1, TerraSAR-X, and Gaofen-3. These results validate that CSK is a vital indicator of ship detection. Complex information is expected to play a more important role in single-channel SAR imagery.

Multiscale Locality and Rank Preservation for Robust Feature Matching of Remote Sensing Images

Sun, 09/01/2019 - 00:00
As a fundamental and important task in many applications of remote sensing and photogrammetry, feature matching tries to seek correspondences between the two feature sets extracted from an image pair of the same object or scene. This paper focuses on eliminating mismatches from a set of putative feature correspondences constructed according to the similarity of existing well-designed feature descriptors. Considering the stable local topological relationship of the potential true correspondences, we propose a simple yet efficient method named multiscale Top $K$ Rank Preservation (mTopKRP) for robust feature matching. To this end, we first search the $K$ -nearest neighbors of each feature point and generate a ranking list accordingly. Then we design a metric based on the weighted Spearman’s footrule distance to describe the similarity of two ranking lists specifically for the matching problem. We build a mathematical optimization model and derive its closed-form solution, enabling our method to establish reliable correspondences in linearithmic time complexity, which requires only tens of milliseconds to handle over 1000 putative matches. We also introduce a multiscale strategy for neighborhood construction, which increases the robustness of our method and can deal with different types of degradation, even when the image pair suffers from a large scale change, rotation, nonrigid deformation, or a large number of mismatches. Extensive experiments on several representative remote sensing image data sets demonstrate the superiority of our method over state of the art.

Identification of Sun Glint Contamination in GMI Measurements Over the Global Ocean

Sun, 09/01/2019 - 00:00
This paper utilizes the model regression difference method to identify sun glint contamination on Global Precipitation Measurement Microwave Imager (GMI) data over the ocean based on observations from 2015 to 2016. The spatial distribution characteristics and the critical angles of the sun glint flags are analyzed in depth. It is found that the GMI measurements with horizontal and vertical polarizations at 10.65 GHz over the ocean are sometimes contaminated by the solar radiation reflected by the sea surface. The sun glint contamination has also been detected over high reflected land surface. The intensity and locations of the contamination are related to the sun glint angle. Only those GMI field of views with smaller sun glint angles are easily contaminated. The closer the sun glint angle is to 0°, the stronger the magnitude of the contamination. The GMI observations at other channels are not contaminated mainly because sun glint is most pronounced at 10 GHz. There are too strong constraints and tossing out of too many useful data in current GMI sun glint algorithms. The suggested critical angles of the sun glint flags for 10.65GHz is 20° to reduce false flagging. By applying the model regression difference method, the error in brightness temperature caused by sun glint can be corrected. The Tropical Rainfall Measuring Mission Microwave Imager (TMI) observations at 10.65 GHz are also contaminated by the reflected solar radiation from the ocean, and the intensity and locations of the contamination are similar to those of the GMI.

Guided Patchwise Nonlocal SAR Despeckling

Sun, 09/01/2019 - 00:00
We propose a new method for synthetic aperture radar (SAR) image despeckling, which leverages information drawn from coregistered optical imagery. Filtering is performed by patchwise nonlocal means, working exclusively on SAR data. However, the filtering weights are computed by taking into account also the optical guide, which is much cleaner than the SAR image, and hence more discriminative. To avoid injecting optical-domain information into the filtered image, an SAR-domain statistical test is preliminarily performed to reject right away any risky predictor. Experiments on two SAR-optical data sets prove the proposed method to suppress very effectively the speckle, preserving structural details, and without introducing significant filtering artifacts. Overall, the proposed method compares favorably with all the state-of-the-art despeckling filters, and also with our own previous optical-guided filter.

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