Search

Abstract Background Although huge fetal hepatic hemangiomas are rare, they can cause fatal complications. The purpose of this study is to describe the imaging features and prognosis of these tumors. Methods Imaging data were collected for 6 patients with huge fetal hepatic hemangiomas treated at our hospital. Imaging modalities included prenatal magnetic resonance imaging and ultrasound and postnatal color Doppler ultrasound and contrast-enhanced computed tomography (CT). Results Among the 93,562 fetuses of 92,126 pregnant women examined at our hospital, 6 had huge hepatic hemangiomas (incidence rate, 0.64/10,000), as confirmed via postnatal color Doppler imaging and contrast-enhanced CT. Five fetuses had solitary lesions, whereas 1 (fetus 2) had multiple lesions. Four fetuses had lesions in the right liver lobe and 1 had a lesion in the left liver lobe, and 1 (fetus 2) had lesions in both lobes. All lesions showed centripetal enhancement on postnatal contrast-enhanced CT, which was more intense peripherally. Following postnatal treatment with oral propranolol, with or without dexamethasone or interventional therapy with the medical sclerosant pingyangmycin, all lesions decreased in size, with calcification plaques appearing 6 months after treatment. Conclusions Huge hepatic hemangiomas have typical ultrasonographic features and can be diagnosed prenatally. Treatment with propranolol, with or without dexamethasone, may result in a favorable prognosis.

In passive microwave remote sensing of the Earth's surface, it is essential to relate the emission to geophysical parameters. The emissivity ranges between 0 and 1. Hence, a slight emissivity variation leads to a significant change in brightness temperature. Many sources of error contribute to such tiny variations in emission. This paper quantifies microwave emission variability from a rough surface through model simulation due to the non-Gaussianity in height probability density (HPD) and power spectrum density (PSD). We considered Gaussian and exponential distributions for surface height and correlation functions, representing two extremes of asperity and skewness. Additionally, the surface under consideration contains multiscale roughness. The impact of the HPD and multiscale roughness on the polarization index of the emissivity is evaluated as a function of frequency and roughness. In general, assuming that Gaussian-distributed height leads to an underestimation of the emissivity, with V polarization being less sensitive to the non-Gaussian HPD and PSD effects than H polarization, the emissions are enhanced at high roughness with small look angles but are reduced for smooth surfaces at large look angles under non-Gaussian PSD. In a specific scenario, the dynamic range of the difference between exponential and Gaussian HPD is 0~10%, and the difference in emissivity caused by non-Gaussian PSD ranges from −2% to 16%. These results should be helpful in interpreting the radiometric measurements that exhibit fluctuations and differences with model predictions. [ABSTRACT FROM AUTHOR]

Natural rough surfaces have inherent multiscale roughness. This article presents the modeling and analysis of microwave emission from a multiscale soil surface. Unlike the linear superposition of different correlation functions with various correlation lengths, we applied the frequency modulation concept to characterize the multiscale roughness, in which the modulation does not destroy the surface's curvature but only modifies it. The multiscale effect on emission under different observation geometries and surface parameters was examined using an AIEM model. The paper provides new insights into the dependence of polarized emissivity on multiscale roughness: V-polarized emissivity is much less sensitive to multiscale roughness across the moisture content from dry to wet (5–30%). The H-polarized is sensitive to multiscale roughness, especially at higher moisture content. The predicted emissivity will have considerable uncertainty, even for the same baseline correlation length, without accounting for the multiscale roughness effect. V-polarized emissivity is less sensitive to the multiscale effect than H-polarized and the higher modulation ratio indicates larger emissivity. The higher modulation ratio indicates larger emissivity. Multiscale roughness weakens the polarization difference, particularly in higher moisture conditions. In addition, ignoring the multiscale effect leads to underestimated emissivity to a certain extent, particularly at the larger RMS height region. Finally, when accounting for multiscale roughness, model predictions of emission from a soil surface are in good agreement with two independently measured data sets. [ABSTRACT FROM AUTHOR]

In modeling a rough surface, it is common to assume a Gaussian height distribution. This hypothesis cannot describe an eventual asymmetry between crests and troughs of natural surfaces. We analyzed the bistatic scattering from a rough surface with non-Gaussian height distributions using the Kirchhoff scattering theory. Two extreme cases of Gamma-distributed surfaces were compared in particular: exponential and Gaussian distributions. The bistatic angular dependence was examined under various root mean square (RMS) heights and power spectrum densities. Contribution sources to the coherent and incoherent scattering components were singled out relating to the surface height distribution. For an exponential height surface, the coherent scattering strengthens even as the surface becomes rough. The non-Gaussian effect on the incoherent scattering is connected with surface power spectrum density. The height distribution impacts differ in the different regions of the bistatic scattering plane and thus complicate the differentiation of the scattering patterns due to height distribution. [ABSTRACT FROM AUTHOR]

The imaging performance of the lunar-based synthetic aperture radar (LBSAR) is susceptible to the orbital perturbation effects. In particular, the perturbations of orbital inclination and right ascension of ascending node (RAAN) could give rise to the temporally varying orbit drift of LBSAR and further lead to Doppler errors in the radio signal. As a result, the LBSAR image performance might be influenced by such effects. This study comprehensively probes into the phase error induced by perturbations of orbital inclination and RAAN, and its effects on the LBSAR imaging performance are further explored. It is found that the LBSAR imaging performance in terms of focusing quality and geometric fidelity is affected by the perturbations of orbital inclination and RAAN, wherein the deterioration of focusing quality is closely associated with the synthetic aperture time. In this regard, the azimuth resolution on a decameter level is optimum for Earth observation of LBSAR with satisfactory image quality. Regarding the geometric fidelity, the accuracy requirement for the orbit determination of the LBSAR under perturbations of the orbital inclination and RAAN is proposed. The analysis results show that the LBSAR orbit determination in terms of the position and velocity determinations is most strenuous in the z-direction. Finally, point target responses are simulated to illustrate the preceding analysis. [ABSTRACT FROM AUTHOR]

The signal propagation of the lunar-based synthetic aperture radar (LBSAR) is affected by perturbations of the lunar orbit, wherein the apsidal precession that exerts a significant impact on the LBSAR imaging performance of the LBSAR deserves special care. Accordingly, the orbital determination used to maintain well-focused quality and high geometric fidelity in the existing SAR system becomes critical for the LBSAR. In this article, through establishing criteria for the orbital determination of LBSAR based on its imaging performance under the influence of apsidal precession, we investigate the accuracy requirements for the LBSAR orbital determination in terms of the position and velocity determinations. Analysis results show that the required accuracy for the LBSAR position determination depends on the geometric fidelity in the range direction, while the accuracy requirement for the velocity determination is dominated by the azimuth positioning accuracy. The focusing quality is not a primary issue for the LBSAR orbital determination. In addition, the far look angle of LBSAR accounts for the highest accuracy requirement in the position and velocity determinations; thus, it can be treated as the optimum look angle for the LBSAR orbital determination. It is also found that both velocity and position determinations are challenging in the ${z}$ -direction for the LBSAR. [ABSTRACT FROM AUTHOR]

As the second generation of Chinese polar-orbiting meteorological satellite missions, the Fengyun (FY)-3D satellite provides the latest multi-frequency brightness temperature (TB) of FY-3 series satellites. The microwave radiation imager (MWRI) boarded on FY-3D has similar sensor configuration as Advanced Microwave Scanning Radiometer 2 (AMSR2), and thus the intercalibration of these two sensors can make their TB data more consistent and continuous to facilitate their joint applications. In this study, the FY-3D H-pol and V-pol TB at five frequencies from 10.7 to 89 GHz during 2019 to 2020 were calibrated against AMSR2 TB over land. Two categories of intercalibration methods were compared, including global intercalibration method, i.e., global linear regression, and per-pixel-based intercalibration methods, i.e., per-pixel linear regression joint global linear regression, per-pixel linear regression joint inverse distance interpolation, per-pixel linear regression joint nearest neighbor interpolation, and global per-pixel linear regression. Furthermore, the effects of diverse environmental variables (i.e., land cover and its heterogeneity, climate types, water body fraction, terrain and its complexity, soil texture, and vegetation coverage) on FY-3D calibration accuracy were fully investigated. The results indicate that all five approaches can reduce the bias between FY-3D and AMSR2 TB, and the root-mean-square difference (RMSD) also reduces accordingly. Among them, the global per-pixel linear regression method performs the best with the lowest averaged RMSD of 2.93 K (at ascending overpass) and 2.34 K (at descending overpass), followed by the per-pixel linear regression joint inverse distance interpolation. The global linear regression method performs the worst with the largest RMSD of 4.69 and 3.82 K at ascending and descending overpass, respectively. The RMSD is relatively larger in temperate and polar climate zones, as well as in grasslands and croplands than in other climate and land cover types. The calibration errors generally decrease as the altitude increases, while they increase with the increase in land cover heterogeneity. The water body fraction exerts the greatest impact on the calibration accuracy, and the RMSD reaches 3 K when the water body fraction is greater than 15%. Soil texture, terrain complexity, and vegetation coverage generally have little influence on the calibration accuracy. These findings can provide a good reference for the intercalibration of satellites with similar configuration to generate long-term climate data records. [ABSTRACT FROM AUTHOR]

The Lee sigma filter was developed in 1983 based on the simple concept of two-sigma probability, and it was reasonably effective in speckle filtering. However, deficiencies were discovered in producing biased estimation and in blurring and depressing strong reflected targets. The advancement of synthetic aperture radar (SAR) technology with high-resolution data of large dimensions demands better and efficient speckle filtering algorithms. In this paper, we extend and improve the Lee sigma filter by eliminating these deficiencies. The bias problem is solved by redefining the sigma range based on the speckle probability density functions. To mitigate the problems of blurring and depressing strong reflective scatterers, a target signature preservation technique is developed. In addition, we incorporate the minimum-mean-square-error estimator for adaptive speckle reduction. Simulated SAR data are used to quantitatively evaluate the characteristics of this improved sigma filter and to validate its effectiveness. The proposed algorithm is applied to spaceborne and airborne SAR data to demonstrate its overall speckle filtering characteristics as compared with other algorithms. This improved sigma filter remains simple in concept and is computationally efficient but without the deficiencies of the original Lee sigma filter. Index Terms---Sigma filter, speckle, speckle filtering, synthetic aperture radar (SAR).

This article presents the computation of the backscattered field in simulation of synthetic aperture radar (SAR) raw data. We develop an improved Kirchhoff approximation to estimate the surface fields induced by the incident waves. The improved Kirchhoff approximation is a second-order iterative solution of the integral equations governing the targets’ electric and magnetic current densities. In computing the second-order re-radiated fields, we applied the shoot-bouncing-ray (SBR) technique to enhance propagation path tracking efficiency. The geometrical theory of diffraction (GTD) was employed to account for the diffraction fields from the edges and wedges, which constitute the total scattered fields collected by SAR in synthetic aperture. As the SAR moves along the azimuth direction, the backscattered signal computation is repeated as the antenna beam crosses the targets. This procedure demands heavy computational resources but requires no priori assumptions of radar cross-sections (RCSs) nor speckle statistics. The raw data is generated as an output signal of the SAR system response into which the backscattered signal is input. We chose three types of the target to demonstrate our approach to confirm the effectiveness. The first set of targets are three dihedral reflectors – two of them were rotated to constitute three unique scattering matrices. The results show that the polarimetric information, both relative amplitudes and phases, are well–preserved. The second target is a rough surface with exponential power spectral density and Gaussian height probability density. We examined image speckle statistics of multi-looking image. The third target type is an electrically large cargo ship (container) sitting over a sea surface. Polarimetric analysis via the Pauli and Y4R decompositions reveals that the polarimetric features are well preserved. Simulation results demonstrate that the present approach is fully coherent in streamlining the data flow from backscattered field to complex single look images within the SAR imaging scene. [ABSTRACT FROM AUTHOR]

In this study, the bistatic radar scattering coefficients related to an oil-covered sea surface are predicted by modeling both the oil damping effect on surface roughness–through the advanced integral equation method–and the oil modification on the dielectric properties of the scattering surface. The bistatic scattering is analyzed in the whole upper scattering space under different radar frequencies, incidence angles, wind speeds, and oil thicknesses. Numerical predictions show that the scattering energy of an oil-covered sea surface is generally higher in the forward scattering zone than that in the backward one. In addition, the oil damping effect is the main mechanism ruling the scattering behavior in the backward region. The information related to the bistatic scattering geometry is also explored to retrieve oil thickness, representing one of the key parameters for radar-based marine oil pollution observation. A new index is proposed to quantify the sensitivity of bistatic scattering coefficients to oil thickness in different cases: single-polarization features, dual co-polarization features, namely, the polarization ratio (PR) and the normalized polarization difference index (NPDI), and dual-angular scattering features. Numerical results show that the bistatic scattering coefficients result in an enhanced sensitivity to oil thickness with respect to the monostatic case. The single HH-polarized scattering coefficients show better oil thickness sensitivity in the backward region, while the VV-polarized ones are more sensitive to oil thickness in the forward region. The combination of dual-polarized scattering coefficients significantly improves the oil thickness sensitivity compared to single-polarization radar observations, especially in the forward region. PR outperforms NPDI, even though the latter can suppress the effect of wind speed. The combination of dual-angular observations can significantly increase its sensitivity of oil thickness in the backward region but at the expense of reduced sensitivity in the forward region. [ABSTRACT FROM AUTHOR]

In this paper, we study the bistatic scattering using an advanced integral equation model (AIEM). By keeping all the surface current terms in the Kirchhoff surface fields, the bistatic scattering coefficients are obtained. For simplification, the complete Kirchhoff field did not cast into the derivation of the complementary field. We compare varied updated versions of IEM-based models with the small perturbation model, geometrical optics model, and Kirchhoff approximation standard models at respective regions of validity. The results indicate that the new AIEM provides much more accurate predictions for bistatic scattering. Index Terms--Bistatic scattering, geometrical optics model (GOM), integral equation model (IEM), Kirchhoff approximation (KA), rough surface, small perturbation model (SPM).

Four radiative transfer equations for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands 11, 12, 13, and 14 are built involving six unknowns (average atmospheric temperature, land surface temperature, and four band emissivities), which is a typical ill-posed problem. The extra equations call be built by using linear or nonlinear relationship between neighbor band emissivities because the emissivity of every land surface type is almost constant for bands 11, 12, 13, and 14. The neural network (NN) can make full use of potential information between band emissivities through training data because the NN simultaneously owns function approximation, classification, optimization computation, and self-study ability. The training database can be built through simulation by MODTRAN4 or can be obtained from the reliable measured data. The average accuracy of the land surface temperature is about 0.24 K, and the average accuracy of emissivity in bands 11, 12, 13, and 14 is under 0.1105 for test data. The retrieval result by the NN is, on average, higher by about 0.7 K than the ASTER standard product (AST08), and the application and comparison indicated that the retrieval result is better than the ASTER standard data product. To further evaluate self-study of the NN, the ASTER standard products are assumed as measured data. After using AST09, AST08, and AST05 (ASTER Standard Data Product) as the compensating training data, the average relative error of the land surface temperature is under 0.1 K relative to the AST08 product, and the average relative error of the emissivity in bands 11, 12, 13, and 14 is under 0.001 relative to AST05, which indicates that the NN owns a powerful self-study ability and is capable of suiting more conditions if more reliable and high-accuracy ASTER standard products can be compensated. Index Terms--Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, emissivity, land surface temperature (LST).

In this paper, a novel technique is proposed for a supervised classification of multisource images for the purpose of landslide hazard assessment. The method, known as the generalized positive Boolean function (GPBF), is developed for land cover classification based on the fusion of remotely sensed images of the same scene collected from multiple sources. It presents a framework for data fusion of multisource remotely sensed images, which consists of two approaches, referred to as the band generation process (BGP) and the positive Boolean function (PBF) classifier. The PBF classifier developed from a stack filter has been successfully applied in hyperspectral image classification. For the PBF to be effective for multispectral images, a multiple adaptation BGP is introduced to create a new set of additional bands especially accommodated to landslide classes. These bands include nonlinear normalized difference vegetation index data and morphological information in the form of digital elevation model (DEM)-derived slope values that originate from multiple sources. The performance of the proposed method is evaluated by fusing Systeme Pour l'Observation de ht Terre images and DEM information for land cover classification during the post 921 Earthquake period in Taiwan. Experimental results demonstrate the proposed GPBF multiclassification approach is suitable for land cover classification in Earth remote sensing and improves the precision of image classification compared to conventional classifiers. Index Terms--Band generation process (BGP), data fusion, digital elevation model (DEM), generalized positive Boolean function (GPBF), normalized difference vegetation index (NDVI), positive Boolean function (PBF), stack filter.

A novel method, which employs both a matrix doubling algorithm and the first-order solution of a radiative transfer (RT) equation for modeling microwave backscattering from forest, is presented in the paper. The method is based on the assumption that a forest canopy can be divided into a number of distinct horizontal vegetation layers over a dielectric half-space rough surface. The scattering phase matrix of each layer is calculated by either matrix doubling to account for the multiple-scattering effect or first-order solution of an RT equation, depending on the scattering characteristics of the layer. The first-order solution of the RT equation is used for the trunk layer while the matrix doubling technique is applied to both the crown layer and understory. The advanced integral equation model and reflectivity matrix are used to calculate the noncoherent and coherent surface boundary conditions. Comparisons between model predictions and field measurements on radar backscattering coefficients for a walnut orchard showed a good agreement at both L-band and X-band and for all three polarizations. Comparative analyses of model predictions for backscattering from a forest medium calculated using the combined model, first-order RT model, and the standard matrix doubling model were also presented. Understory effects, that can significantly change the weight of each scattering mechanism, were also evaluated by using the combined method. Index Terms--Combined model, forest, matrix doubling.

This study develops a parameterized bare surface emission model for the applications in analyses of the passive microwave satellite measurements from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). We first evaluated the capability of the advanced integral equation model (AIEM) in simulating wide-band and high-incidence surface emission signals in comparison with INRA's field experimental data obtained in 1993. The evaluation results showed a very good agreement. With the confirmed confidence, we generated a bare surface emission database for a wide range of surface dielectric and roughness properties under AMSR-E sensor configurations using the AIEM model. Through the evaluations of the commonly used semiempirical models with both the AIEM simulated and the field experimental data, we developed a parameterized multifrequency-polarization surface emission model--the Qp model. This model relates the effects of the surface roughness on the emission signals through the roughness variable Qp at the polarization p. The Qp can be simply described as a single-surface roughness property--the ratio of the surface rms height and the correlation length. The comparison of the emissivity simulations by the Qp and AIEM models indicated that the absolute error is extremely small at the magnitude of [10.sup.-3]. The newly developed surface emission model should be very useful in modeling, improving our understanding, analyses, and predictions of the AMSR-E measurements. Index Terms--Microwave, modeling, surface emissivity, roughness.

An integral equation method (IEM) surface scattering model was examined in terms of its applicability to laboratory measurement and numerical simulations. New expressions for both single scattering and multiple scattering were obtained by rederiving the scattering coefficient to keep all the phase terms in the spectral representation of the Green's function. After quite intricate mathematical manipulations, a fairly compact form is obtained for the scattering coefficients. In addition, the Fresnel reflection coefficients used in the model were replaced by a transition function that takes surface roughness and permittivity into account. The results of comparisons with both the numerical simulations and measurements for the backscattering case indicate that the IEM is improved, becoming more accurate and practical to use. Index Terms--Backscattering, integral equation method (IEM) model, rough surface.

This paper presents a method, based on a fuzzy neural network, that uses fully polarimetric information for terrain and land-use classification of synthetic aperture radar (SAR) image. The proposed approach makes use of statistical properties of polarimetric data, and takes advantage of a fuzzy neural network. A distance measure, based on a complex Wishart distribution, is applied using the fuzzy c-means clustering algorithm, and the clustering result is then incorporated into the neural network. Instead of preselecting the polarization channels to form a feature vector, all elements of the polarimetric covariance matrix serve as the target feature vector as inputs to the neural network. It is thus expected that the neural network will include fully polarimetric backscattering information for image classification. With the generalization, adaptation, and other capabilities of the neural network, information contained in the covariance matrix, such as the amplitude, the phase difference, the degree of polarization, etc., can be fully explored. A test image, acquired by the .let Propulsion Laboratory Airborne SAR (AIRSAR) system, is used to demonstrate the advantages of the proposed method. It is shown that the proposed approach can greatly enhance the adaptability and the flexibility giving fully polarimetric SAR for terrain cover classification. The integration of fuzzy c-means (FCM) and fast generalization dynamic learning neural network (DLNN) capabilities makes the proposed algorithm an attractive and alternative method for polarimetric SAR classification. Index Terms--Fuzzy c-means, neural classification, polarimetric synthetic aperture radar, speckle filtering.

This article presents a numerical study of the wave scattering from a modulated rough surface characterized by a modulated correlation function that shows zero crossings along the lag distance. The zero crossings imply the presence of multiscale roughness. In such a way, we treat the rough surface to include a baseband correlation length and a modulation length. The modulation ratio, the ratio of baseband correlation length, and the modulated length determine the degree of multiscale roughness. We then examine the dependence of bistatic scattering, both in level and angular trends, on the modulation length. The results indicate that as the modulation ratio increases, the scattering coefficients reduce in the incident plane. Comparing the model predictions with two independent sets of measurement data demonstrates a good agreement of the scattering coefficients between the experimental data and the model predictions with modulation effects. The proposed modulated rough surface concept offers higher flexibility to model the radar scattering of multiscale rough surface. [ABSTRACT FROM AUTHOR]

There are few studies on predicting fully bistatic scattering from the rough surface of Mars, though some bistatic radar observations have been made, such as in the MARS EXPRESS mission. To better understand the interaction of radar signals with a planetary surface in bistatic radar observations, the topographic-scale roughness of Mars, characterized by a two-dimensional power spectrum density (2D-PSD), is examined in view of its global roughness variations and scale dependence on geological units. The analysis shows that the Martian 2D-PSD is strongly dependent on the geological units and that it lies between Gaussian and exponential functions, with a power index equal to 1.9. The bistatic scattering coefficients are calculated by an advanced integral equation model (AIEM) with the 2D-PSD as the input. It shows that the specific surface roughness spectrum and the dielectric inhomogeneity should be taken into account in interpreting the bistatic radar scattering response. [ABSTRACT FROM AUTHOR]

Electromagnetic scattering and emission from 1-D rough surfaces with multiple elevations are studied using full-wave simulations. Both the root-mean-square (rms) heights and the surface length are large compared to the wavelength. A novel multilevel steepest decent-sparse matrix canonical grid (MLSD-SMCG) method is proposed to address limitations in the original SMCG. The uniform Nystrom method and neighborhood impedance boundary condition (NIBC) are also incorporated in solving the dual surface integral equations (SIEs) of the method of moments (MoM). Simulation results are illustrated at L-band for soil and ocean surfaces. The surface rms heights and lengths are up to 1.43 and 243.8 m corresponding to 6 and 1024 wavelengths at 1.26 GHz, respectively. For ocean surfaces, the wind speeds up to 20 m/s are considered, and the entire spectrum is included to capture all relevant surface length scales. Numerical results indicate the proposed approach is computationally efficient and accurate. Energy conservation checks in simulations are at 10−4 for ocean scattering and emission. Also, the effects of wind-driven roughness on ocean emissivity are further investigated using the proposed approach in terms of wind speed and observation angle for both polarizations. [ABSTRACT FROM AUTHOR]

There have been considerable interests in the lunar-based synthetic aperture radar (LBSAR) for monitoring large-scale geoscience phenomena. However, the signal distortions given rise by lunar orbital perturbations, especially the apsidal precession, are particularly severe in the LBSAR. The apsidal precession effects can induce a coordinate drift of the LBSAR, which can further lead to the variation in the range history of the LBSAR. As a result, LBSAR’s image performance might be affected. In this letter, we thoroughly investigate whether the apsidal precession effects cause the phase decorrelation in the signal of the LBSAR, and how such effects impact the LBSAR imaging. The theoretical result shows that the impact of the lunar apsidal precession mainly results in the first-order and second-order Doppler errors, which further influence the geometric location and focusing quality along the azimuth direction. Numerical simulations using the point target response show good consistency with the theoretical analysis. To this end, the lunar apsidal precession effects deserve special care in the LBSAR for high imaging quality. [ABSTRACT FROM AUTHOR]

Numerical simulation of random rough surface finds wide applications in scientific disciplines, e.g., radar remote sensing of terrain and sea. In scattering simulation of rough surface, not only energy conservation must be ensured, but also, perhaps equally important, the surface inherent properties must be preserved. However, the proper choice of surface and grid sizes that are statistically representative poses a problematic issue. This study applied the entropy measure to determine such parameter settings by examining the relative error of sample entropy associated with roughness parameters and by noticing the fact that a rough surface with certain roughness parameters, including power spectrum density function, must have unique sample entropy. It is found that if the two criteria are met, proper choice of surface length and grid size is attainable to warrant minimum uncertainties of rough surfaces and maximum information content for different roughness spectra density functions under different correlation lengths. The feasibility and superiority of the proposed entropy-based method are validated in terms of minimum error of roughness parameters and also the energy conservation in bistatic scattering coefficients of rough surfaces generated using obtained simulation parameters. [ABSTRACT FROM AUTHOR]

The interaction of radar signals with a planetary surface is critical for the utility of radar data. Herein, a power‐law roughness spectrum is used to model the roughness and an inhomogeneous vertical permittivity to describe the dielectrics from the surface of Mars. Numerical simulations of depolarised radar backscattering are then conducted. To gain a more complete picture of depolarised characteristics, a wide range of surface roughness is considered. Results reveal that the depolarised backscattering is sensitive to the dielectric profiles with –10 dB is observed. The polarization conversion ratio, the ratio of depolarisation to total polarization backscattering, is a sensitive indicator of dielectric profiles and roughness, and thus is useful in retrieving dielectric profile. [ABSTRACT FROM AUTHOR]

This article presents a new index, polarization-conversion ratio (PCR) to characterize depolarized bistatic scattering from rough surfaces with dielectric inhomogeneity and spatial anisotropy. We then investigate the dependence of PCR on both surface and radar parameters. Numerical results show that the distribution of PCR on the scattering plane varies with the polarization state of the incident wave and incident angle. The PCR clusters more in the cross-plane for horizontally polarized incidence. However, for vertically polarized incidence, the PCR disperses as “triangular shape” on the whole scattering plane with a sharp valley occurring in the incident plane. The following points can be drawn: 1) the inhomogeneity effectively enhances the PCR in the cross-plane; 2) the effect of anisotropy on the PCR is relatively weak, because the scattering is less affected by correlation length; 3) the impacts of surface rms height on the PCR are negative on the whole scattering plane; and 4) as the background permittivity increases, at the horizontally polarized incidence, the PCR is enhanced in the backward and forward regions, while at vertically polarized incidence, it is enhanced in the incident plane and the forward region. As is demonstrated, the PCR is an effective measure of the sensitivity of depolarization, making it potentially useful as a new reliable index for surface parameter inversion. [ABSTRACT FROM AUTHOR]

In this article, we devise a polarimetric calibration method utilizing only three types of calibration targets, i.e., trihedral, dihedral, and a 22.5°-rotated dihedral corner reflectors and requiring no assumptions on the scene statistics. The influence of the roll angle in a 22.5°-rotated dihedral corner reflector is assessed by a full-wave numerical simulation. The effectiveness and accuracy of the method are verified with a ground-based synthetic aperture radar system and an airborne L-band Pi-SAR data. We demonstrate that an amplitude error as low as 0.5 dB and a phase error within 3° can be achieved, showing an excellent agreement between the theoretical and calibrated polarimetric signatures for the reference targets. We further exploit the calibration on the Pauli decomposition, Yamaguchi four-component decomposition, and the estimation of the polarimetric parameters derived from target scattering vector method decomposition to show the superior performance of the devised calibration method. [ABSTRACT FROM AUTHOR]

The spatiotemporal coverage of a Moon-based synthetic aperture radar (SAR) is analyzed based on the imaging geometry, upon which the spatial coverage and image formulation rely. The distance from the Earth to the Moon-based SAR and bounds of the grazing and azimuthal angles jointly determine the coverage area on the Earth’s surface. Meanwhile, the ground coverage of the Moon-based SAR is determined by the bounds of the grazing and azimuthal angles and geographic coordinates of the nadir point at a specified time. Moreover, the temporal variation in the spatial coverage is pertinent to the temporally varying nadir point of the Moon-based SAR on the Earth’s surface. Furthermore, numerical simulations using the lunar ephemeris data are carried out to complement the analysis and to illustrate the spatiotemporal coverage. Finally, a guideline for the optimal site selection of a Moon-based SAR is proposed. In conclusion, a Moon-based SAR has the potential to perform long-term, continuous Earth observations on a global scale to enhance our capability to understand the planet. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is a key parameter for many fields of study. Currently, LST retrieved from satellite thermal infrared (TIR) measurements is attainable with an accuracy of about 1 K for most natural flat surfaces. However, over urban areas, TIR measurements are influenced by 3-D structures and their radiation that could degrade the performance of existing LST retrieval algorithms. Therefore, quantitative models are needed to investigate such impact. Current 3-D radiative transfer models are generally based on time-consuming numerical integrations whose solutions are not analytical, and are therefore difficult to exploit in the methods of physical retrieval of LST in urban areas. This article proposes an analytical TIR radiative transfer model over urban (ATIMOU) areas that considers the impact of 3-D structures and their radiation. The magnitude of this impact on TIR measurements is investigated in detail, using ATIMOU, under various conditions. Simulations show that failure to acknowledge this impact can potentially introduce a 1.87-K bias to the ground brightness temperature for street canyon whose ratio “wall height/road width” is 2, wall and road temperature is 300 K, wall emissivity is 0.906, and road emissivity is 0.950. This bias reaches 4.60 K if road emissivity decreases to 0.921, and road temperature decreases to 260 K. ATIMOU is also compared to the discrete anisotropic radiative transfer (DART) model. Small mean absolute error of 0.10 K was found between the models regarding the simulated ground brightness temperatures, indicating that ATIMOU is in good agreement with DART. [ABSTRACT FROM AUTHOR]

This article attempts to examine the Brewster effect of incoherent scattering from a lossy inhomogeneous rough surface with a vertical dielectric profile. Five typical dielectric profiles are selected for the purpose of illustration. In calculating the reflection coefficients, a transition model is used to convert the angle of incidence to local incidence, which accounts for the surface roughness. Numerical results show that the Brewster angle gradually moves to the large incident angle with an increase in the background dielectric constant and in the surface root-mean-squared (rms) height. The angular dependence of reflection coefficients, both the level and the trend, is slightly affected by the correlation length. The scattering strength is much more sensitive to the rms height than to the correlation length. The results could be useful in the retrieval of vertical soil moisture content when proper radar observation is available. [ABSTRACT FROM AUTHOR]

The effectiveness of refined interferometric synthetic aperture radar (InSAR) filter (refined filter) was validated using both simulated and real interferometric data. However, the threshold as a key parameter in the refined filter is determined by repeated attempts, and the deterministic method has some disadvantages, such as strong subjectivity, long time consuming, and bad adaptation. This letter makes full use of the robustness of inverse distance weighting (IDW) to simplify the refined filter. In the proposed filter, using an $11 \times 11$ window and an improved IDW, the computational burden of $| {\langle {e^{j\psi _{z}}} \rangle } |$ for 16 windows per pixel is avoided, and the need for setting the threshold is eliminated. From the beginning, the initial window angle is determined using four preprocessing windows. The filtering direction of the center pixel is affected by the initial window angle of each pixel, the degree of homogeneity of each pixel, and the distance of the pixel from the center pixel in the $11\times 11$ window. The improved weighting method is then used to further refine the window angle of the center pixel. Numerical experiments by simulated and real InSAR data were used to validate the proposed approach. By comparison, the proposed filter greatly improves the efficiency of the refined filter and exhibits the superiority in filtering performance compared to commonly used filters, particularly for regions of low coherence, high-coherence-gradient, and high-phase gradient. [ABSTRACT FROM AUTHOR]

Due to the earth and moon’s revolutions, the Doppler centroid of the moon-based synthetic aperture radar (moon-based SAR) varies dramatically along the orbit of the moon when the SAR system is looking broadside (nonsquinted). However, the Doppler centroid should be kept as small as possible to avoid range ambiguity and to alleviate difficulty with focus. This letter presents the Doppler properties along the orbit of the moon in accordance with the antenna coordinate system. Based on the Doppler analysis and the phase scan, we propose a method for Doppler centroid steering to minimize the Doppler centroid frequency without rotating the platform. The new method can accurately compensate the Doppler centroid to zero, because it considers the effects of the lunar orbit and the relative motion between earth’s target and moon-based SAR. To validate the proposed method, we also derived the lower and upper bounds of the look angle. Subsequently, we performed simulations in accordance with Jet Propulsion Laboratory Development Ephemeris 430 (JPL DE430). Finally, the performance requirement of the phase scan is analyzed so as to validate the proposed method. [ABSTRACT FROM AUTHOR]

Soil moisture is a pivotal hydrological variable that links the terrestrial water, energy, and carbon cycles. In this article, a new soil moisture (SM) index (SMI), which aims to capture the temporal variability of SM, irrespective of cloud cover and solar illumination, was developed by using the L-band SM active passive (SMAP) radiometer observations. The SMI was proposed on the basis of two key foundations: 1) vegetation and roughness have similar effects on “depolarization” of microwave emission, while SM enhances polarization differences and 2) vegetation and roughness generally impose positive effects on surface emissivity, while SM and emissivity are negatively correlated. Based on the two physical principles, it is possible to decouple the effects of SM and those of vegetation and surface roughness in a 2-D space independent of vegetation type and roughness condition. The proposed SMI was then validated by in situ measurements from five dense SM networks covering different vegetation and climatic conditions and also compared with SMAP passive and European space agency climate change initiative (ESA CCI) SM products at a coarse resolution of 36 km, and SMAP-enhanced passive and Japan Aerospace Exploration Agency (JAXA) advanced microwave scanning radiometer (AMSR2) SM products at a medium resolution of 9 km. The results show that the new SMI is able to well reproduce the temporal dynamic of SM with a favorable averaged correlation coefficient value of 0.87 and 0.84 at 36 and 9 km, respectively, higher than that of SMAP passive (0.80), SMAP-enhanced passive (0.77), ESA CCI (0.69), and JAXA AMSR2 (0.53). After removing the systematic differences between satellite and site-specific SM data by using the cumulative distribution function (CDF) matching technique, the SMI can achieve an average root mean squared error (RMSE) of 0.031 and 0.036 m3m−3 at 36 and 9 km during the validation period, respectively, lower than that of the satellite SM products. In addition to surface temperature, the SMI does not need any further information from other sensors [e.g., the optical normalized difference vegetation index (NDVI) or leaf area index (LAI) data] to guarantee an all-weather monitoring. Therefore, it has great potential to estimate SM variability on a global scale. [ABSTRACT FROM AUTHOR]

The upwind–downwind asymmetry in normalized radar backscattering cross section (NRBCS) from ocean surface is well known; one acceptable and convincing reasoning is explained by the fact that the surface height distribution deviates from Gaussian one, which causes a nonzero skewness function, and consequently affects the radar cross section in up and down wind directions. Specific forms of skewness function, in between Gaussian and exponential, have been proposed in previous studies to account for the upwind/downwind asymmetry in radar backscatter. Attempt is made, through numerical simulation, in this article to examine the impact of these two types of skewness functions on NRBCS. The simulated NBRCSs, with and without skewness contributions, are compared with measured data in upwind and downwind directions at L-, C-, and Ku-bands for different wind speeds. The results indicate that the Gaussian-type skewness function works better to account for the upwind/downwind asymmetry of NBRCS by choosing an appropriate root mean square (RMS) height appearing in skewness function and as the wind speed or radar frequency increases, the RMS height increases but regardless of wind direction and radar incidence angle. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper examines the polarized backscattering of spatially anisotropic rough surfaces. To better explore the physical mechanisms that control the azimuthal dependence of the backscattering from anisotropic surfaces, the effects of surface roughness [correlation length and root-mean-square (rms) height], dielectric constant, and radar parameters from anisotropic surfaces are studied. The advanced integral equation model (AIEM) is used to simulate both co- and cross-polarized backscattering coefficients, including the single and multiple scattering. Numerical results suggest that the multiple scattering exhibits a stronger azimuthal dependence for HH than VV polarization, especially more so at a larger incident angle. For weakly anisotropic surface, the azimuthal variation of backscattering tends to be a sinusoidal-like pattern. However, with the enhancement of anisotropy, such a scattering pattern is distorted, and the sharp dip appears at up/down direction. As the rms height and dielectric constant increase, the scattering is enhanced on the whole. The HH/VV ratio at lower dielectric constant is greater than that at higher one. In comparison, scattering shows stronger dependence on anisotropy at lower dielectric constant, especially at a larger incident angle. As an application example, we compare the model predictions with reported measurements from two different sites. Preliminary results are quite encouraging, and thus, the analysis presented in this paper is potentially useful to predict and interpret backscattering from crop field surface, where strong anisotropic surfaces commonly present due to plowing or raking practice. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, effects of the earth’s curvature and lunar revolution on the performance of the moon-based synthetic aperture radar (SAR) are examined by a comprehensive analysis of the motion-induced Doppler frequency and Doppler rate on which azimuthal imaging relies. The motion effects include the earth’s self-rotation related to the earth’s curvature and lunar revolution around the earth. An extended hyperbolic range equation (EHRE) is proposed in line of the equivalent velocity and equivalent squint angle, and then the signal model based on the EHRE is established to simulate the moon-based SAR image from which the imaging performance is analyzed. Theoretical analyses show that the earth’s curvature is a dominant factor in determining the moon-based SAR’s Doppler and azimuthal resolution. Furthermore, the earth’s curvature distorts the SAR image by way of rotating the azimuth imaging from the cross-range direction within a certain skewed angle. The overall effects of lunar revolution generate a velocity correction factor and a deviate squint angle, which subsequently deteriorate the azimuthal resolution and image focusing. Results also show that effects of the earth’s curvature and lunar revolution are in connection with relative positions of the ground target and moon-based SAR. To this end, numerical simulations using point target response is carried out to accentuate the necessary for taking account of the Doppler error induced by the lunar revolution. [ABSTRACT FROM AUTHOR]

Microwave backscattering models play key roles in surface scattering modeling and soil moisture inversion in active microwave remote sensing. However, numerous evaluations indicate that significant discrepancies between the model simulations and radar observations remain, and these discrepancies are regarded to be attributed to inaccuracies in the models. What do such discrepancies originate from is unclear and has not been comprehensively analyzed. To this end, this paper presents an uncertainty analysis to explore the intrinsic reason for the discrepancies between the backscattering model simulations and radar observations. The probability distribution function and the corresponding statistical characteristics are introduced to describe the uncertainty in the model outputs. We find that the scale dependence of the key model inputs leads to significant uncertainties in the model inputs, and the uncertainties are transferred into the model outputs. Thus, the discrepancies between the model simulations and radar observations are intrinsically caused by the spatial scaling and related uncertainties of key model inputs. In short, the scale mismatch between the model inputs and remote sensing pixels is an intrinsic factor that causes the discrepancies between the model simulations and radar observations. This finding suggests that the scaling effect of model inputs should be carefully considered when using the backscattering models at the pixel scale, and equivalent inputs matched at the corresponding scales should be developed for remote sensing applications. Thus, this analysis insights into the scale dependence of inputs for backscattering models and suggests to provide scale-matched inputs where the models are applied at different scales. [ABSTRACT FROM AUTHOR]

Active and passive microwave signatures respond differently to the land surface and provide complementary information on the characteristics of the observed scenes. The objective of this paper is to explore the synergy of active radar and passive radiometer observations at the same spatial scale to constrain a discrete radiative transfer model, the Tor Vergata (TVG) model, to gain insights into the microwave scattering and emission mechanisms over grasslands. The TVG model can simultaneously simulate the backscattering coefficient and emissivity with a set of input parameters. To calibrate this model, in situ soil moisture and temperature data collected from the Maqu area in the northeastern region of the Tibetan Plateau, interpolated leaf area index (LAI) data from the Moderate Resolution Imaging Spectroradiometer LAI eight-day products, and concurrent and coincident Soil Moisture Active Passive (SMAP) radar and radiometer observations are used. Because this model needs numerous input parameters to be driven, the extended Fourier amplitude sensitivity test is first applied to conduct global sensitivity analysis (GSA) to select the sensitive and insensitive parameters. Only the most sensitive parameters are defined as free variables, to separately calibrate the active-only model (TVG-A), the passive-only model (TVG-P), and the active and passive combined model (TVG-AP). The accuracy of the calibrated models is evaluated by comparing the SMAP observations and the model simulations. The results show that TVG-AP can well reproduce the backscattering coefficient and brightness temperature, with correlation coefficients of 0.87, 0.89, 0.78, and 0.43 and root-mean-square errors of 0.49 dB, 0.52 dB, 7.20 K, and 10.47 K for $\sigma _{\mathrm{ HH}}^{o} $ , $\sigma _{\mathrm{ VV}}^{o} $ , $T_{\mathrm {BH}}$ , and $T_{\mathrm {BV}}$ , respectively. In contrast, TVG-A and TVG-P can only accurately model the backscattering coefficient and brightness temperature, respectively. Without any modifications of the calibrated parameters, the error metrics computed from the validation data are slightly worse than those of the calibration data. These results demonstrate the feasibility of the synergistic use of SMAP active radar and passive radiometer observations under the unified framework of a physical model. In addition, the results demonstrate the necessity and effectiveness of applying GSA in model optimization. It is expected that these findings can contribute to the development of model-based soil moisture retrieval methods using active and passive microwave remote sensing data. [ABSTRACT FROM AUTHOR]

This letter explores the optimal bistatic radar configurations for bare soil moisture retrieval at L-band using a global sensitivity analysis method, the extended Fourier amplitude sensitivity test (EFAST) algorithm. Complete sets of bistatic scattering, covering a wide range of geometric parameters and ground surface conditions, are simulated by the well-established advanced integral equation model. The sensitivity of radar bistatic signals to soil moisture and surface roughness, and the interactions among the parameters are quantified using the EFAST algorithm. The results show that in bistatic scattering, VV polarization has notably higher sensitivity to soil moisture than HH polarization, particularly at large incident angles. For VV polarization, as incident angle increases, the sensitivity zone of soil moisture expands and shifts toward the forward direction, specifically at small azimuth scattering angles and large scattering angles, thereby becoming promising configurations for soil moisture retrieval. For HH polarization, in contrast, the sensitive zone gradually moves to the backward direction as incident angle increases, and an intermediate incident angle (e.g., 40°) is recommended for retrieving soil moisture by considering both sensitivity strength and parameter interaction effects. [ABSTRACT FROM AUTHOR]

In this letter, we investigate volume-scattering effects on microwave emission from a foam-covered ocean surface by a comparative study of emissivities and polarization indexes of a numerical radiative transfer model and an incoherent emission model. The matrix doubling method is applied in the numerical model, which fully accounts for the multiple scattering in the foam layer and at the interfaces. The incoherent emission model considers incoherent interactions between air–foam and foam–seawater interfaces but ignores the volume scattering in the foam layer. Model analyses show that foam volume scattering affects both the magnitude and polarization index of emission from the foam-covered ocean surface. Foam volume scattering reduces the rate of increase in emissivity with increasing foam water fraction. Results also show that polarization index is more sensitive to volume scattering at a large observation angle and at a low foam water fraction. Comparison between model predictions and experimental measurements accentuate the need to account for foam-scattering effects in interpreting emission measurements from the foam-covered ocean surface. [ABSTRACT FROM PUBLISHER]