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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]

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]

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]

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]

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]

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]

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]

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]

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]

The Moon-based Synthetic Aperture Radar (Moon-Based SAR), using the Moon as a platform, has a great potential to offer global-scale coverage of the earth's surface with a high revisit cycle and is able to meet the scientific requirements for climate change study. However, operating in the lunar orbit, Moon-Based SAR imaging is confined within a complex geometry of the Moon-Based SAR, Moon, and Earth, where both rotation and revolution have effects. The extremely long exposure time of Moon-Based SAR presents a curved moving trajectory and the protracted time-delay in propagation makes the "stop-and-go" assumption no longer valid. Consequently, the conventional SAR imaging technique is no longer valid for Moon-Based SAR. This paper develops a Moon-Based SAR theory in which a signal model is derived. The Doppler parameters in the context of lunar revolution with the removal of -stop-and-go' assumption are first estimated, and then characteristics of Moon-Based SAR imaging's azimuthal resolution are analyzed. In addition, a signal model of Moon-Based SAR and its two-dimensional (2-D) spectrum are further derived. Numerical simulation using point targets validates the signal model and enables Doppler parameter estimation for image focusing. [ABSTRACT FROM AUTHOR]

We apply Shannon entropy, an information content measure, in sensitivity analysis (SA), stemming from the fact that the essence of SA is to preserve the maximum information content of the parameters of interest that are inverted from the radar response. Then, the sensitivity to the observation configuration and surface parameters is subsequently analyzed. Attempts are also made to explore advantages, by maximizing the information content, of dual-polarization and multi-angle in improving the parameter retrieval from radar sensing of rough surface. Simulation results show that the entropy is a good indicator of the sensitivity of the radar response to the surface parameter, as it contains information on not only the probability distribution of the scattering coefficient but also on its deviation. By information entropy, richer details, to large extent, on the scattering behavior are offered through quantitatively predicting the scattering signal saturation, evaluating the effect of using multi-polarization and multi-angle observation configuration, and identifying non-significant variables. It is found that Shannon entropy, compared to Renyi entropy, appears to better represent the sensitivity with respect to monotonic variation and narrower parameter ranges. The proposed entropy-based SA method helps to deepen our understanding of the microwave scattering behavior in response to surface parameters. [ABSTRACT FROM AUTHOR]

In this paper, an attempt is made to investigate the angular signatures of bistatic scattering, in the azimuthal direction, from rough surfaces, with the aim of deepening our understanding of the bistatic scattering behaviors and exploring its potential applications. Three distinct angular features, dip angle, scattering strength, and angular width, as a function of the surface roughness and dielectric constant, are identified. Brewster’s scattering, and its role in angular behavior, is examined at limited extent. Results reveal that the angular features strongly correlate with the surface parameters and scattering geometry. For small scattering angle, dip angle and width are independent of surface roughness. Comparatively, for larger incident and scattering angles, beyond 50°, the dip angle and scattering strength are sensitive, simultaneously, to rms height and dielectric constant, while the dip width only responses to rms height. Dips, induced by Brewster’s scattering effect, not only shift in the polar direction, but also in the azimuthal direction, and are strongly dependent on surface parameters and bistatic geometry. Increasing the surface roughness or, equivalently, the incident angle tends to promote the disappearance of dips. The main contributions of this paper can be summarized as follows: 1) quantitative description of dip features, including angle, scattering strength, and angular width; 2) comprehensive characterization of the dip features and their dependence on surface parameters and bistatic geometries; and 3) limited investigation of the behavior of Brewster’s scattering-induced dip. [ABSTRACT FROM PUBLISHER]

Theoretical modeling plays a significant role as forward and inverse problem in active and passive microwave remote sensing. Understanding the validity and limitations of the models is essential for model refinements and, perhaps more importantly, model applications. Motivated by these, this paper presents a comprehensive analysis of the scattering, both backscattering and bistatic scattering, and emission of rough soil surface predicted by the advanced integral equation model (AIEM), a well-established theoretical model. Numerically simulated data, covering a wide range of surface parameters, and in situ measurement data set of well-characterized bare soil surfaces were used to evaluate the performance of AIEM in predicting the scattering coefficient and microwave emissivity over a wide range of geometric parameters and ground surface conditions. The results show that the AIEM predictions are generally in good consistency with both numerical simulations and experiment measurements in terms of angular, frequency, and polarization dependences, except for some deviations in a few cases (e.g., at large incident angles and dry soil conditions). Extensive comparison confirms the effectiveness and practicability of AIEM for both scattering and emission of rough soil surface. Possible explanations for the discrepancy between the model prediction and data are given, together with suggestions for model usage and refinements. [ABSTRACT FROM AUTHOR]

In this paper, a physically based numerical electromagnetic approach, by solving Maxwell's equations, is developed to investigate the scattering and the emission from double-layered media, where both the top and bottom interfaces are random sastrugi surfaces with a random horizontal shift between the two corresponding negative-slope facets of both interfaces. Numerical simulations are illustrated for bistatic scattering and four Stokes parameters at L-, C-, X-, and K-bands. Results indicate that the bistatic scattering and Stokes parameters are asymmetric for the double-sastrugi media, whereas for the other two structures, sastrugi surface alone and sastrugi surface with a planar bottom boundary, their scattering and the first two Stokes parameters are even symmetric relative to the azimuthal angle of 90°, and the third and fourth Stokes parameters are odd symmetric. In particular, the Stokes results no longer have the strong coherent fluctuations in angular variations shown in periodic double-layered structures because the random double-layered structure eliminates the coherent interference. It is interesting to observe that the internal total reflection may cancel if the coupled interactions between the two sastrugi interfaces are very strong, which results in decreasing scattering at the L-band, and its Stokes parameters are similar to those of the sastrugi alone. Numerical results also reveal that the maxima of cross-polarized specular scattering from double-sastrugi structures can be observed at cross incidence; however, they are at a deep dip for the latter two statistical symmetric structures. The sastrugi-sastrugi structure, being geometrically anisotropic, is capable of generating strong cross-polarized scattering and, subsequently, significant amounts of the third and fourth Stokes. The azimuthal patterns, at a viewing angle of 55°, of four Stokes parameters, although more complex, are feature rich where two striking extrema of third and fourth Stokes are presented. Compared with the L-band, the C-band presents strong azimuthal dependence of four Stokes. The simulation results offer deeper insights into the scattering and emission process in sastrugi surface and may lead to better retrieval of surface parameters from radar or radiometric measurements. [ABSTRACT FROM PUBLISHER]

The Soil Moisture Active Passive (SMAP) mission, which is the newest L-band satellite that is specifically designed for soil moisture monitoring, was launched on January 31, 2015. A beta quality version of the SMAP radiometer soil moisture product was recently released to the public. It is crucial to evaluate the reliability of this product before it can be routinely used in hydrometeorological studies at a global scale. In this paper, we carried out a preliminary evaluation of the SMAP radiometer soil moisture product against in situ measurements collected from three networks that cover different climatic and land surface conditions, including two dense networks established in the U.S. and Finland, and one sparse network set up in Romania. Results show that the SMAP soil moisture product is in good agreement with the in situ measurements, although it exhibits dry or wet bias at different network regions. It well reproduces the temporal evolution and anomalies of the observed soil moisture with a favorable correlation greater than 0.7. The overall ubRMSE (unbiased root mean square error) of SMAP product is 0.036 m3 $\cdot$ m−3, well within the mission requirement of 0.04 m3 $\cdot$ m−3. The error sources of SMAP soil moisture product may be associated with the parameterization of vegetation and surface roughness but still needs to be tested and confirmed in more extent. Considering that the algorithms are still under refinement, it can be reasonably expected that hydrometeorological applications will benefit from the SMAP radiometer soil moisture product. [ABSTRACT FROM PUBLISHER]

This paper investigates the bistatic scattering from randomly corrugated surfaces with irregular grooves. For a given incident wave, the surface fields and the scattered field were computed by the method of moments in which the rooftop basis function was used to account for fast phase changes due to steep surface slopes. The total scattered field is decomposed into coherent and incoherent components to analyze their respective contributions. We found that, for randomly corrugated surfaces with irregular ridges or grooves, the coherent scattering is profound at several scattering angles with strong main lobes, whose beamwidths are strongly correlated with the ridge density. The numerical simulation has shown that the lobe angular shift away from the specular direction is quasi-linearly dependent on the ridge density, suggesting that the coherent scattering pattern substantially contains the surface geometric information. We expect this paper to offer deeper understanding of coherent imaging of rough surface and to help in designing a novel imaging system. [ABSTRACT FROM AUTHOR]

Radar interferometry has been widely applied in measuring the terrain height and its changes. The information about surface can be derived from phase interferograms. However, the inherent phase noise reduces the accuracy and reliability of that information. Hence, the minimization of phase noise is essential prior to the retrieval of surface information that is embedded in an interferometric phase. This paper presents a refined filter based on the Lee adaptive complex filter and the improved sigma filter that was originally developed for amplitude image filtering. The basic idea is to adaptively filter the interferometric phase according to the local noise level to minimize the loss of signal for a particular pattern of fringes, including such extreme cases as involving broken fringes, following the removal of undesired pixels. Ultimately, the goals are to preserve the fringe pattern, to reduce phase bias and deviation, to reduce the number of residues, and to minimize the phase error. The preservation of the fringe pattern is particularly of concern in areas of high frequency of fringe and large phase gradient corresponding to steep terrains. The proposed refined filter was validated using both simulated data and real interferometric data. Results demonstrate that the filtering performance is better than that of commonly used filters. [ABSTRACT FROM AUTHOR]

This paper investigates the radar image statistics of rough surfaces by simulating the scattered signal's dependence on the surface roughness. Statistically, the roughness characteristics include the height probability density (HPD) and, to the second-order, the power spectral density (PSD). We simulated the radar backscattered signal by computing the far-field scattered field from the rough surface within the antenna beam volume in the context of synthetic aperture radar (SAR) imaging. To account for the non-Gaussian height distribution, we consider microscopic details of the roughness on comparable radar wavelength scales to include specularly, singly, and multiply scatterers. We introduce surface roughness index (RSI) to distinguish the statistical characteristics of rough surfaces with different height distributions. Results suggest that increasing the RMS height does not impact the Gaussian HPD surface but significantly affects the Weibull surface. The results confirm that as the radar frequency increases, or reaches a relatively larger roughness, the surface's HPD causes significant changes in incoherent scattering due to more frequent multiple scattering contributions. As a result, the speckle move further away from the Rayleigh model. By examining individual RSI, we see that the Gaussian HPD surface is much less sensitive to RMS height than the Weibull HPD surface. We demonstrate that to retrieve the surface parameters (both dielectric and roughness) from the estimated RCS, less accuracy is expected for the non-Gaussian surface than the Gaussian surface under the same conditions. Therefore, results drawn from this study are helpful for system performance evaluations, parameters estimation, and target detection for SAR imaging of a rough surface. [ABSTRACT FROM AUTHOR]

We present a GPU-based computation for simulating the synthetic aperture radar (SAR) image of the complex target. To be more realistic, we included the multiple scattering field and antenna pattern tracking in producing the SAR echo signal for both Stripmap and Spotlight modes. Of the signal chains, the computation of the backscattering field is the most computationally intensive. To resolve the issue, we implement a computation parallelization for SAR echo signal generation. By profiling, the overall processing was identified to find which is the heavy loading stage. To further accommodate the hardware structure, we made extensive modifications in the CUDA kernel function. As a result, the computation efficiency is much improved, with over 224 times the speed up. The computation complexity by comparing the CPU and GPU computations was provided. We validated the proposed simulation algorithm using canonical targets, including a perfectly electric conductor (PEC), dielectric spheres, and rotated/unrotated dihedral corner reflectors. Additionally, the targets can be a multi-layered dielectric coating or a layered medium. The latter case aimed to evaluate the polarimetric response quantitively. Then, we simulated a complex target with various poses relative to the SAR imaging geometry. We show that the simulated images have high fidelity in geometric and radiometric specifications. The decomposition of images from individual scattering bounce offers valuable exploitation of the scattering mechanisms responsible for imaging certain target features. [ABSTRACT FROM AUTHOR]

The prevailing complex geological and ecological conditions of Taiwan have drawn considerable attention from various geo-ecological communities because of their vulnerability to produce various natural hazards at different scales. Located in the tropical/subtropical zone of the Pacific Rim, its ecological and rugged mountainous properties are environmentally sensitive making monitoring and observation especially difficult because of the high population density. In this article, we have investigated the land deformation in two adjacent industrial parks, Jhong-Li and Guei-Shan, in northern Taiwan using radar interferometry. The Interferometric Synthetic Aperture Radar technique for processing a series of data sets was first validated by comparison with ground levelling measurements over a test site. Excellent agreement was obtained in both deformation pattern and magnitude of subsidence rate. The period of observation dated from 1993 to 2000 with Synthetic Aperture Radar images from ERS-1 and ERS-2. The results, after least-squares adjustment, revealed that the maximum subsidence reached 10 cm and the subsidence rates were about 1.8 cm year−1 (at epicentres) since 1993 at both parks. It was also found that the subsidence rate slowed down after 1998 at Jhong-Li park while continuing at Guei-Shan park. This was strongly associated with local groundwater extraction activities. [ABSTRACT FROM AUTHOR]

Uncertainties in the length of active faults and the styles of deformation often hamper the evaluation of seismic potentials in a region. In the area near Chiayi City of southwestern Taiwan, where historically there have been many strong earthquakes, complex fault and fold systems produced by regional tectonic forces and the subsequent deformation are frequently obscured by vegetation and anthropogenic effects; and therefore detailed deformation information has not been available for evaluation of the seismic potential. By stacking the results from Differential Interferometry and removing the ambiguity of interferograms using GPS data, we were able to retrieve surface deformation information about the area under consideration near Chiayi City. In our results, we found that the Meishan fault to the north of Chiayi City extended 10 km to the west of its currently documented area and served as a geological boundary separating the northern part, where sediments were thicker, from the southern part of the westward extension of the Meishan fault. Chiayi City was under active deformation by a double plunging fold with vertical uplift rate at approximately 1 cm/yr. Frequent seismicity and active deformation allowed the tectonic stress to permute between strike–slip and thrust in this area. Continuous folding of Chiayi City and episodic large earthquakes along the Meishan Fault posed a serious threat of seismic hazards in this region, and called for continuous monitoring of the area. [Copyright &y& Elsevier]

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 Tibetan Plateau (TP), known as the "Third Pole," is a climate-sensitive and ecology-fragile region. In this study, the spatiotemporal trends of soil moisture (SM) and vegetation were analyzed using satellite-based ESA CCI SM and MODIS LAI data, respectively, in the growing season during the last 20 years (2000–19) over the TP covering diverse climate zones. The climatic drivers (precipitation and air temperature) of SM and LAI variations were fully investigated by using both ERA5 reanalysis and observation-based gridded data. The results reveal the TP is generally wetting and significantly greening in the last 20 years. The SM with significant increasing trend accounts for 21.80% (fraction of grid cells) of the TP, and is about twice of the SM with significant decreasing trend (10.19%), while more than half of the TP (58.21%) exhibits significant increasing trend of LAI. Though the responses of SM and LAI to climatic factors are spatially heterogeneous, precipitation is the dominant driver of SM variation with 48.36% (ERA5) and 32.51% (observation-based) precipitation data showing the strongest significant positive partial correlation with SM. Temperature rise largely explains the vegetation greening, though precipitation also plays an important role in vegetation growth in arid and semiarid zones. The combined trend of SM and LAI indicates the TP is mainly composed of wetting and greening areas, followed by drying and greening regions. The change rate of SM is negative at low altitudes and becomes positive as altitude increases, while the LAI value and its change rate decrease as altitude increases. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP), known as the "Third Pole," is a climate-sensitive and ecology-fragile region. In this study, the spatiotemporal trends of soil moisture (SM) and vegetation were analyzed using satellite-based ESA CCI SM and MODIS LAI data, respectively, in the growing season during the last 20 years (2000–19) over the TP covering diverse climate zones. The climatic drivers (precipitation and air temperature) of SM and LAI variations were fully investigated by using both ERA5 reanalysis and observation-based gridded data. The results reveal the TP is generally wetting and significantly greening in the last 20 years. The SM with significant increasing trend accounts for 21.80% (fraction of grid cells) of the TP, and is about twice of the SM with significant decreasing trend (10.19%), while more than half of the TP (58.21%) exhibits significant increasing trend of LAI. Though the responses of SM and LAI to climatic factors are spatially heterogeneous, precipitation is the dominant driver of SM variation with 48.36% (ERA5) and 32.51% (observation-based) precipitation data showing the strongest significant positive partial correlation with SM. Temperature rise largely explains the vegetation greening, though precipitation also plays an important role in vegetation growth in arid and semiarid zones. The combined trend of SM and LAI indicates the TP is mainly composed of wetting and greening areas, followed by drying and greening regions. The change rate of SM is negative at low altitudes and becomes positive as altitude increases, while the LAI value and its change rate decrease as altitude increases. [ABSTRACT FROM AUTHOR]

Fully bistatic radar scattering from rough surfaces is of vital importance in terrain remote sensing, but results in bulky data volume. The scattering is dependent on physical parameters of the media and is controlled by the radar observation geometry. Together, the two sets of parameters determine the scattering patterns in a bistatic plane confined by incident and polar angles in both incident and scattering directions. For radar remote sensing, it is desirable to infer surface parameters of interest, with satisfactory accuracy, from large volumes of measured data sets. This is essentially a task of data mining. In this paper, we present model-generated bistatic radar scattering data, followed by a sensitivity analysis, to identify a suitable configuration in terms of parameter inversion from fully bistatic measurements by a Kalman filter-trained dynamic learning neural network (DLNN). Results indicate that with bistatic observation, superior retrieval performance (as compared to backscattering observation) can be readily achieved. [ABSTRACT FROM AUTHOR]

The sea surface essentially contains multiscale roughness with capillary waves of many sizes riding on large-scale waves that are also of many sizes. It is instructive to exploit the effect of radar frequency and observation geometry on the effective roughness scales responsible for radar backscattering so that the scattering mechanism and the scattering source can be better understood and quantitated. Based on common sea spectra and a theoretical scattering model, an attempt is made to attain the above objective. Model predictions, with selective roughness scales, are compared with wide validation data, including L-band radar observations, and predictions from C-band and Ku-band empirical models: geophysical model function (CMOD7) and NASA scatterometer (NSCAT-4) for C- and Ku-bands at different incident angles. Numerical results indicate that effective roughness scales for radar backscattering vary with radar frequency and incidence angle and are related to a portion of sea spectral components; the low limit of which is linearly proportional to the Bragg wavenumber determined by frequency and incidence angle, and the scale factor of the linear relationship is about 0.05. In addition, the root mean square (RMS) height and the correlation length of the effective roughness (i.e., scattering source) derived from the effective roughness decrease gradually as incident angle increases. In particular, the correlation length also linearly depends on the effective wavelength with a coefficient of 3.2. Moreover, these two coefficients are both independent of wind speed, radar frequency, and incident angle. These findings also reveal the essential properties of the spectral components contributing to radar backscattering and its variation with radar frequency and incident angle. [ABSTRACT FROM AUTHOR]

In recent years, bistatic synthetic aperture radar (SAR) technique has attracted considerable and increasing attention. Compared to monostatic SAR for which only the backscattering is measured, bistatic SAR expands the scattering measurements in aspects of angular region and polarization, and greatly enhances the capability of remote sensing over terrain and sea. It has been pointed out in recent theoretical researches that bistatic scattering measured in the forward region is preferable to that measured in the backward region in lines of surface parameters retrieval. In the forward region, both dynamic range and signal sensitivity increase to a great extent. For these reasons, bistatic SAR imaging is desirable. However, because of the separated positions of the transmitter and receiver, the degrees of freedom in the parameter space is increased and the forward bistatic imaging is more complicated than the backward bistatic SAR in the aspects of bistatic range history, Doppler parameter estimation and motion compensation, et, al. In this study, we analyze bistatic SAR in terms of ground range resolution, azimuth resolution, bistatic range history and signal to noise ratio (SNR) in different bistatic configurations. Effects of system motion parameters on bistatic SAR imaging are investigated through analytical modeling and numerical simulations. The results indicate that the range resolution is extremely degraded in some cases in forward bistatic SAR imaging. In addition, due to the different imaging projection rules between backward and forward bistatic SAR, the ghost point is produced in the forward imaging. To avoid the above problems, the forward bistatic imaging geometry must be carefully considered. For a given application requirement with the desired imaging performances, the design of the motion parameters can be considered as a question of solving the nonlinear equation system (NES). Then the improved chaos particle swarm optimization (CPSO) is introduced to solve the NES and obtain the optimal solutions. And the simulated imaging results are used to test and verify the effectiveness of CPSO. The results help to deepen understanding of the constraints and properties of bistatic SAR imaging and provide the reference to the optimal design of the motion parameters for a specific requirement, especially in forward bistatic configurations. [ABSTRACT FROM AUTHOR]

Imaging simulation of synthetic aperture radar (SAR) is one of the potential tools in the field of remote sensing. The echo signal in imaging simulation based on the point target model cannot be linked to practical scenes due to the model being a simple mathematical form, stating only the synthetic process and lacking the physical process based on electromagnetic theory. In this paper, the full-wave method is applied to include the electromagnetic effects in raw data generation, and then a refined omega-K algorithm is used to perform image focusing. According to the proposed method, the focused images not only demonstrate the difference under dielectric constant variation but also present the diversified interaction among the targets with the spacing change. In addition, the images are simulated in different observation modes and bandwidths to provide a satisfactory reference for the design of system parameters. The simulation results from the full-wave method also compare well with chamber experiments. The simulation of SAR imaging based on a full-wave method offers more complete recovery of scattering information and is useful in designing future novel SAR systems and in speckle reduction analysis. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate, by means of experimental measurements and full-wave simulations, the dominant factors for the very high-resolution (VHR) radar image speckles from exponentially correlated rough surfaces. A Ka-band radar system was used to collect the return signal from such a surface sample fabricated by 3D printing and that signal was further processed into images at different resolution scales, where the image samples were obtained by horizontally turning around the surface sample. To cross-validate the results and to further discuss the VHR speckle properties, full wave simulations by full 3D Finite Difference Time Domain (FDTD) method were conducted with 1600 realizations for the speckle analysis. At the considered very high resolution, speckle statistics show divergence from the fully developed Rayleigh distribution. The factors that impact on the high-resolution speckle properties from exponentially correlated rough surface, are analyzed in views of the equivalent number of scatterers theory and scattering scales, respectively. From the data results and extended discussions, it is evident that both of the above factors matter for VHR speckle of backscattering, from the exponentially correlated rough surface as a good representative for the ground surface. [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]

Color enhancement of decomposed fully polarimetric synthetic aperture radar (PolSAR) image is vital for visual understanding and interpretation of the polarimetric information about the target. It is common practice to use RGB or HIS color space to display the chromatic information for polarization-encoded, Pauli-basis images, or model-based target decomposition of PolSAR images. However, to represent the chroma for multi-polarization SAR data, the region of basic RGB color space does not fully cover the human perceptual system, leading to information loss. In this paper, we propose a color-encoding framework based on the CIE-Lab, a perceptually uniform color space, aiming at a better visual perception and information exploration. The effective interpretability in increasing chromatic, and thus visual enhancement, is presented using extensive datasets. In particular, the four decomposed components—volume scattering, surface scattering, double bounce, and helix scattering—along with total return power, are simultaneously mapped into the color space to improve the discernibility among the scattering components. The five channels derived from the four-component decomposition method can be simultaneously mapped to CIE-Lab color space intuitively. Results show that the proposed color enhancement not only preserves the color tone of the polarization signatures, but also magnifies the target information embedded in the total returned power. [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]

Soil moisture (SM) plays a significant role in water, energy, and carbon cycles, and is a key variable related to multiple sustainable development goals. The frequent occurrence of extreme events in the 21st century complicates the understanding of terrestrial SM change and its drivers under diverse environmental conditions, particularly in the global scope. Here we globally explored the spatial-temporal trend of satellite-based SM (ESA CCI SM) and its possible drivers under a variety of environmental factors (land cover, soil texture, terrain, and vegetation coverage) during 2000–2021. Results indicate that global SM has generally declined with a rate of −0.10 × 10−3 m3m−3 yr−1 which is mainly dominated by the drying trend of the southern hemisphere. The moisture replenishment role of precipitation dominates in areas with relatively high SM values, and the positive influence of vegetation and precipitation on SM is prominent in regions where SM values are relatively low. But vegetation has a pronounced negative impact on SM north of 60°N and in southeastern China. Compared with precipitation and vegetation, topsoil temperature has less impact on SM globally. Land cover types, soil properties, elevation, and vegetation cover influence SM variability and its response to climate and vegetation to varying degrees. For example, the overall wetting trend of SM is unique under loam soils and high elevations (> 1000 m) in terms of different soil texture and elevations. The increase in vegetation cover within a certain amount is accompanied by the wetting of SM, but in densely vegetated regions such as forests, the water retention effect of vegetation on SM is weakened. An evaluation of 'Dry gets drier, wet gets wetter' (DDWW) paradigm from the SM viewpoint shows the paradigm summarizes 41.06% of areas with significant SM changes. Precipitation replenishment and vegetation water retention profoundly impact the 'wet gets wetter' and 'dry gets wetter' patterns. Temperature is a strong influencing factor of the 'wet gets drier' pattern, while the reduction of vegetation and precipitation jointly affect the 'dry gets drier' pattern. These findings can deepen the understanding of SM changes in relation to climate, ecology, and land surface features, particularly in the 21st century with profound changes of the environment. • Soil moisture (SM) trend and its driving mechanisms are investigated globally. • SM presents an overall drying trend, particularly in the southern hemisphere. • Precipitation and vegetation have greater influence on SM than temperature does. • The SM trend and its drivers are significantly affected by environmental factors. • SM variation in arid zones generally follows the 'dry get drier' paradigm. [ABSTRACT FROM AUTHOR]

We investigate the magnitude of Sun-glint through modeling the Soil Moisture Active Passive (SMAP) brightness temperature (BT). Model results show that the specular reflection of Sun-glint in the L-band can spread over a wide range of view angles due to the roughness and undulation of the land surface and therefore affect SMAP radiometer observations. Due to SMAP’s low incidence angle (40°), Sun-glint in the specular direction is never observed, and only the noncoherent component of Sun-glint has influence on SMAP observations. Sun-glint is particularly an issue over wet soil surfaces at low solar zenith angles (SZAs), and caution has to be taken for the terrain effect even for high SZAs, because the local solar incident angle can be significantly changed by the terrain slope and then the specular reflection of Sun-glint can be viewed by SMAP. Model results also show that BT in V-pol is less contaminated by Sun-glint than that in H-pol. During an intense solar radio burst, it was found that the land surface BT in H-pol increased by 50 K in the forward scattering direction from the SMAP observation. This is roughly equivalent to 1 K increment by every 100 solar flux units on a dry soil and/or dense vegetation. When the solar activity is quiet in 2015, the Sun-glint from both wet land and ocean surfaces can reach up to 10 K in the SMAP L1B BT product. This paper suggests that BT observations around the solar specular direction should be masked for soil moisture retrieval at the L-band. [ABSTRACT FROM PUBLISHER]

This paper presents an electromagnetic modeling of temporal variations of microwave backscatter from rice canopy based on radiative transfer theory to understand the complex microwave scattering mechanisms of rice crops at different growth stages. Model validation is made by a comparison with field measurements from four independent campaigns by ground-based scatterometers and spaceborne synthetic aperture radar (SAR). Then, the frequency responses and angular dependence are examined, followed by an analysis of parameter sensitivity and uncertainty to microwave backscatter. The validation shows promising results for the physically based model in assessing radar response of rice plant in its full-growth stage. It is found that radar scattering of rice canopy is highly dependent on the growing stages of rice plants, in addition to radar configurations, such as frequency, polarization, and incident angle. Moreover, backscattering of rice canopy is more dependent on stems than on leaves, and as rice plants grow, increasing stems and leaves tend to promote HH- and VH-polarized scattering, while first promoting and then reducing VV-polarized scattering. Moreover, the greatest uncertainty takes place at the late growth stage for copolarization and at the early stages for cross-polarization. The main contributions of this paper can be summarized as follows: 1) the establishment of a rice canopy microwave backscattering model using radiative transfer theory adapted to all the stages in the phenological cycle of rice; 2) the validation of the performance of the proposed model with numerous independent measurements from spaceborne SAR and ground-based scatterometers from different countries and regions; 3) the investigation of the interactions between microwave backscatter signatures and rice canopy growth variables over growth stages; and 4) the identification of the dominant influential parameters of the rice scattering model and determination model uncertainty. [ABSTRACT FROM PUBLISHER]

Abstract: The Surface Energy Balance Algorithm for Land (SEBAL) has been successfully applied to remote sensing data to estimate surface evapotranspiration (ET) at different spatial and temporal resolutions in more than 30 countries. However, the selection of dry and wet pixels over the area of interest (AOI) makes the SEBAL-estimated ET subject to the sizes of the AOI and the satellite pixels. This paper investigates the effect of the sizes of the AOI and satellite pixels on SEBAL-derived surface energy components by proposing generalized analytical equations. These equations demonstrate how the variations in the intermediate variables, the AOI, and the pixel size affect the resulting surface energy components and under which circumstances the sensible heat flux will be misestimated, without needing to run the SEBAL model. These analytical equations were verified through application to 23 clear-sky MODIS overpasses that cover different soil water contents and crop growth stages from January 2010 to late October 2011. The spatial effects of increasing the size of the AOI for SEBAL can be summarized as follows: (1) if the locations of dry and wet pixels do not vary, the pixel-by-pixel sensible heat flux (H LA ) calculated using the larger AOI is equal to that of the smaller AOI (H SA , with H LA /H SA =1), (2) if only the surface temperatures of wet pixels do not vary, the relative variation in H is equal to the relative variation of the slope (a) of the linear equation between the near-surface air temperature difference and the surface temperature (H LA /H SA =1+ δH SA /H SA =1+ δa/a), and (3) under other circumstances, H LA /H SA decreases with surface temperatures at a slowing pace from ∼∞ at the temperature of the wet pixel (T s,wet ) to a certain value at the temperature of the dry pixel (T s,dry ) (both temperatures are for the small AOI). Analogously, a general analytical equation—a function of the coefficients of the linear equation between the near-surface air temperature difference and surface temperature at the high-resolution, the effective temperature, and the effective momentum roughness length—could be used to quantify the spatial-scale effect of the satellite pixel size. The findings from this study may help determine suitable sizes of the AOIs and the satellite pixels and aid in quantifying uncertainties in the SEBAL-derived surface energy components. [Copyright &y& Elsevier]

Based upon Huygens' subgridding (HSG) technique and unconditionally stable time domain algorithms, we present a synchronized multigrid time domain method for 2- and 3-D scattering problems. In this method, the implicit algorithms are employed in the fine grid region, while the Yee-FDTD is marching on the coarse mesh. As a result, the electromagnetic fields in both coarse and fine grid regions are updated synchronously. The synchronization has greatly simplified the HSG implementation and reduced updating substeps. Numerical examples demonstrate extremely low spurious reflection at the interface, robust stability for arbitrarily large spatial ratios, and suppression of late time instability. [ABSTRACT FROM PUBLISHER]

Conventional direction-of-arrival (DOA) estimation methods are primarily used in point source scenarios and based on array signal processing. However, due to the local scattering caused by sea surface, signals observed from radar antenna cannot be regarded as a point source but rather as a spatially dispersed source. Besides, with the advantages of flexibility and comparably low cost, synthetic aperture radar (SAR) is the present and future trend of space-based systems. This paper proposes a novel DOA estimation approach for SAR systems using the simulated radar measurement of the sea surface at different operating frequencies and wind speeds. This article's forward model is an advanced integral equation model (AIEM) to calculate the electromagnetic scattered from the sea surface. To solve the DOA estimation problem, we introduce a convolutional neural network (CNN) framework to estimate the transmitter's incident angle and incident azimuth angle. Results demonstrate that the CNN can achieve a good performance in DOA estimation at a wide range of frequencies and sea wind speeds. [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]

Soil moisture is one of the vital environmental variables in the land–atmosphere cycle. A study of the sensitivity analysis of bistatic scattering coefficients from bare soil at the Ku-band is presented, with the aim of deepening our understanding of the bistatic scattering features and exploring its potential in soil moisture retrieval. First, a well-established advanced integral method was adopted for simulating the bistatic scattering response of bare soil. Secondly, a sensitivity index and a normalized weight quality index were proposed to evaluate the effect of soil moisture on the bistatic scattering coefficient in terms of polarization and angular diversity, and the combinations thereof. The results of single-polarized VV data show that the regions with the maximum sensitivity and high quality index, simultaneously, to soil moisture are in the forward off-specular direction. However, due to the effect of surface roughness and surface autocorrelation function (ACF), the single-polarized data have some limitations for soil moisture inversion. By contrast, the results of two different polarization combinations, as well as a dual-angular simulation of one transmitter and two receivers, show significant estimation benefits. It can be seen that they all provide better ACF suppression capabilities, larger high-sensitivity area, and higher quality indices compared to single-polarized estimation. In addition, dual polarization or dual angular combined measurement provides the possibility of retrieving soil moisture in backward regions. These results are expected to contribute to the design of future bistatic observation systems. [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]