Surface-scattering Model Research Articles

Assessment of Surface Scattering Models Within the Water Cloud Model Toward Soil Moisture Retrievals Using Sentinel-1 and Sentinel-2 Images

Assessment of Surface Scattering Models Within the Water Cloud Model Toward Soil Moisture Retrievals Using Sentinel-1 and Sentinel-2 Images

Optimization of Random Surface Scattering Models for RR Polarization in SoOp-R/GNSS-R Applications

Optimization of Random Surface Scattering Models for RR Polarization in SoOp-R/GNSS-R Applications

Rough Surface Scattering Model Comparisons for Radar Altimetry of Sea Ice

Currently, sea-ice thickness is often estimated using microwave radar altimetry. It is well known that radar measurements are highly dependent on the roughness characteristics of the observed scene and can have a profound effect on altimetry-based thickness estimates. This simulation-based study highlights the importance of sea-ice roughness parameterization in the context of radar altimetry. This work provides a new sea-ice roughness parameterization in the form of an elevation spectrum developed from field campaign data. The formulation of this elevation spectrum is partly based on the generalized power law. Simulations have been developed to predict electromagnetic scattering from surfaces described by the new spectrum, with a focus on the X-band (10 GHz) scattering with nadir incidence. In this work, both the analytical small slope approximation and numerically exact Method of Moments are applied to various sea-ice surface spectra, representing a wide range of surface roughness conditions. The results show that the normalized radar cross section of the sea-ice interface varies significantly depending on the surface elevation spectrum and the statistics of the rough interface. Comparisons with numerically exact methods show that analytical approximations to rough surface scattering work reasonably well for the cases considered here, except at large scattering angles.

Surface and Volume Scattering Model in Microwave Remote Sensing of Snow and Soil Moisture

Surface and Volume Scattering Model in Microwave Remote Sensing of Snow and Soil Moisture

First-order nonparaxial scalar theory of surface and bulk scattering for high-quality optical coatings.

A novel nonparaxial scalar theory is presented to calculate the angular scattering that is due to interface roughnesses or bulk inhomogeneities in a high-quality optical coating. Based on the empirically modified Beckmann-Kirchhoff surface scatter model, this theory in surface scattering and bulk scattering predicts similar formulas for the angular scattered intensity, and at the same time provides new understanding and insight into multilayer scattering phenomena. It is worth noting that the derived expressions are in the same form as those given by the typical vector methods. Based on comparisons of the surface and bulk models with the corresponding typical models for several multilayer designs, the novel theory is demonstrated to be valid for multilayer coatings even with large incident and scattering angles.

Onto a Skewness Approach to the Generalized Curvature Ocean Surface Scattering Model

The generalized curvature ocean surface scattering model [general curvature model (GCM)] is extended and revisited. Two key steps are addressed in this paper, namely, a necessary sea surface spectrum undressing procedure and the inclusion of a skewness phase-related component. Normalized radar cross-section (NRCS) simulations are generated at C-band for various wind conditions, polarizations, and incidence angles. Results are compared with CMOD5.n. Although the sea surface spectrum undressing procedure is a necessary step, the overall NRCS dynamic is notably affected only in low wind conditions (≤5 m/s). The inclusion of the skewness phase-related component makes the most impact to the NRCS dynamic where the upwind/downwind asymmetry is clearly detectable. A good agreement between the upwind/downwind asymmetry of the extended GCM and CMOD5.n is achieved for moderate winds (≈5–10 m/s) and moderate incidence angles (≈32°–40°). For low incidence angles (<26°), the GCM tends to overestimate the upwind/downwind asymmetry compared with CMOD5.n.

Estimation of supraglacial debris thickness using a novel target decomposition on L‐band polarimetric SAR images in the Tianshan Mountains

AbstractDebris is widely distributed in the ablation zones of mountain glaciers in the Tianshan Mountains. Supraglacial debris can accelerate or hamper glacier ablation, depending on its thickness. Thus, it plays an important role in the mass balance of debris‐covered glaciers. This paper proposes a novel method to estimate supraglacial debris thickness by using L‐band polarimetric synthetic aperture radar. A new model‐based target decomposition is used to extract the surface scattering, double bounce, and volume scattering components. The surface scatter model uses the extended Bragg scatter, which considers the depolarization effect for rough surfaces. The volume scatter model uses elliptical scatterers, which approximate the shape of the solids in the debris. The volume scattering power is related to the dielectric properties of the debris, the radar wavelength, the incidence angle, and the elliptical scatter shape. Once the target decomposition is performed, the debris thickness can be inverted from the volume scattering power and other known parameters. Through comparison with a large number of field measurements, the inversion is shown to be reasonable, and the accuracy is validated to be ±0.12 m. Based on the inversion map in the study area, the debris thicknesses of the Koxkar glacier and its neighboring glaciers are presented and analyzed.

X-Band Two-Scale Sea Surface Scattering Model to Predict the Contrast due to an Oil slick

In this study, a sea/oil contrast model, based on the two-scale sea surface scattering Boundary Perturbation Model and an improved Marangoni damping model, is exploited to predict the X-band contrast due to an oil slick. Theoretical predictions are then compared with actual X-band synthetic aperture radar (SAR) measurements collected by COSMO-SkyMed and TerraSAR-X satellites over the polluted area off the Aberdeen coast (United Kingdom) during the Gannet Alpha oil spillage occurred in 2011. The contrast model is here verified at X-band for the first time and exploited in a very challenging scenario, i.e., when an oil slick is in place. In addition, a detailed analysis on the effect of sensor's noise equivalent sigma zero (NESZ) on the predicted and measured contrast is undertaken. Experimental results confirm model predictions, witnessing a remarkable agreement between predicted and measured contrasts. Moreover, they demonstrate that NESZ significantly affects the information content of the signal backscattered off the oil-covered area.

High spatial frequency laser induced periodic surface structure formation in germanium by mid-IR femtosecond pulses

Formation of high spatial frequency laser induced periodic surface structures (HSFL) in germanium by 90 fs mid-IR pulses at a 1 kHz repetition rate with wavelengths between λ = 2 and 3.6 μm was studied with varying angle of incidence and polarization. The period of these structures varied from λ/3 to λ/8. A modified surface-scattering model including Drude excitation and the optical Kerr effect explains the spatial period scaling of HSFL across the mid-IR wavelengths. Transmission electron microscopy shows the presence of a 30 nm amorphous layer above the structure of crystalline germanium. Various mechanisms including two photon absorption and defect-induced amorphization are discussed as probable causes for the formation of this layer.

A surface-scattering model satisfying energy conservation and reciprocity

Roughness scattering models based on Kirchhoff׳s approximation or perturbation theory give a good account of the angular distribution of the scattered intensity but do not satisfy energy conservation and reciprocity rigorously. For applications such as solar cells with rough interfaces producing a quasi isotropic intensity in the multiple scattering regime, an accurate model of the angular pattern is not required. Instead, energy conservation and reciprocity must be satisfied with great accuracy. Here we present a surface scattering model based on analysis of scattering from a layer of particles on top of a substrate in the dipole approximation which satisfies both energy conservation and reciprocity and is thus accurate in all frequency ranges. The model takes into account the absorption in the substrate induced by the particles but does not take into account the near-field interactions between the particles. In arriving at this model, we use the effective-medium approach to show how we can proceed from modeling the electromagnetic scattering from a single particle to modeling the scattering from a layer of particles positioned above a substrate, and finally relate this to the bidirectional scattering distribution function of the substrate.

InSAR Image Regularization and DEM Error Correction With Fractal Surface Scattering Model

This paper presents a method for removing spikes in digital elevation models (DEMs) caused by residues in interferometric synthetic aperture radar (InSAR) phase image. We consider that the scattering mechanism is properly modeled by the small perturbation method for fractal surfaces and present a model that relates the phase and magnitude in InSAR image. This data model provides the regularization term of the method, without directly enforcing smooth phase or magnitude. Noise models are given by additive Gaussian for the phase and multiplicative non-unit-mean gamma for the magnitude. Experiments with simulated and real L-band data show that the proposed method considerably improves DEM accuracy and simultaneously suppresses speckle and phase noise.

Failure of semiclassical models to describe resistivity of nanometric, polycrystalline tungsten films

The impact of electron scattering at surfaces and grain boundaries in nanometric polycrystalline tungsten (W) films was studied. A series of polycrystalline W films ranging in thickness from 10 to 310 nm and lateral grain size from 74 to 133 nm were prepared on thermally oxidized Si. The Fuchs-Sondheimer surface-scattering model and Mayadas-Shatzkes grain-boundary scattering model were employed for quantitative analyses. Predictions from the theoretical models were found to deviate systematically from the experimental data. Possible reasons for the failure of the theoretical models to describe the experimental data are explored. Finally, a discussion of the crucial features lacking from existing models is presented, along with possible avenues for improving the models to result in better agreement with experimental data.

Linear systems formulation of scattering theory for rough surfaces with arbitrary incident and scattering angles

Scattering effects from microtopographic surface roughness are merely nonparaxial diffraction phenomena resulting from random phase variations in the reflected or transmitted wavefront. Rayleigh-Rice, Beckmann-Kirchhoff. or Harvey-Shack surface scatter theories are commonly used to predict surface scatter effects. Smooth-surface and/or paraxial approximations have severely limited the range of applicability of each of the above theoretical treatments. A recent linear systems formulation of nonparaxial scalar diffraction theory applied to surface scatter phenomena resulted first in an empirically modified Beckmann-Kirchhoff surface scatter model, then a generalized Harvey-Shack theory that produces accurate results for rougher surfaces than the Rayleigh-Rice theory and for larger incident and scattered angles than the classical Beckmann-Kirchhoff and the original Harvey-Shack theories. These new developments simplify the analysis and understanding of nonintuitive scattering behavior from rough surfaces illuminated at arbitrary incident angles.

Sea-Ice thickness retrieval in the Sea of Okhotsk using dual-polarization SAR data

AbstractWe investigated the feasibility of using multi-polarization Synthetic aperture radar (SAR) data to estimate the thickness of undeformed first-year ice. Analysis of the radar Signatures for the C- and L-bands Showed that the correlation between the ice thickness and VV-to-HH backscattering ratio is larger than the correlation between the ice thicknesses and the backscattering coefficients. This is in part because the ice Surface Salinity and hence the Surface reflection coefficient decreases as the ice thickens. The backscattering ratio had low Sensitivity to the Small-scale ice Surface roughness for the C-band and is almost independent of roughness at L-band. Given that the ratio is most Sensitive to ice Surface dielectric constants, which depend on Salinity, we developed an algorithm for retrieving the ice thickness that is based on the backscattering ratio and on the integral-equation-method (IEM) Surface Scattering model. Comparison of the observed and estimated ice thicknesses Showed that the correlation was much better when the thicknesses were estimated using the backscattering ratio than when the backscattering coefficient was used directly. The algorithm also performed better than previous retrievals using an empirical technique.

Extraction of Surface Roughness Parameters by Using SAR Data and Theoretical Surface-Scattering Models

Spatial surface roughness information is very important to estimate a spatial distribution of surface fluxes. In this study, by using theoretical surface-scattering models, surface roughness parameters are extracted from the backscattering coefficients observed by JERS-1 and ERS-1 and surface soil moisture volumetric content, and sensitivity analysis of backscattering coefficients and soil moisture content to the extracted surface roughness parameters are performed. In the Biwako Project area, the extracted surface roughness parameters are compared with observed ones. The extracted values and observed ones correspond well at the dry paddy fields.

Retrieving Soil Moisture Over Bare Soil from ERS 1 Synthetic Aperture Radar Data: Sensitivity Analysis Based on a Theoretical Surface Scattering Model and Field Data

In order to assess the retrieval of soil moisture from ERS 1 (European Remote Sensing Satellite) synthetic aperture radar (SAR) data, an inversion procedure based oft the integral equation model (IEM) [Fung et al., 1992] is developed. First, the IEM is used to analyze the sensitivity of radar echoes (in terms of the backscattering coefficient σ0) to the surface parameters (roughness and dielectric constant) under ERS 1 SAR configuration. Results obtained for random rough bare soil fields show that the effect of surface roughness is very strong, particularly in the case of smooth surfaces, and that the sensitivity of σ0 to dielectric constant is independent of the radar configuration and the roughness conditions. This means that the range of variation of backscattering with respect to the dielectric constant variation of dry to wet soil remains the same (about 5 dB) for any roughness condition and radar configuration. The possibility of applying the inversion procedure to retrieve soil moisture is investigated using a set of data collected in a test site situated near Naples, Italy, during the SeIe Synthetic Aperture Radar experiment (SESAR) campaign (November 1993). Simultaneous with ERS 1 overpasses, dielectric constant and roughness measurements were taken over two flat bare fields. From this analysis it is found that the inversion of backscattering from ERS 1 SAR into soil moisture is not reliable without accurate information on roughness if the surface is smooth. In this case it is observed that the sensitivity to the roughness parameters is much higher than the sensitivity to dielectric constant, so that even a small error in the measurement of this parameter can affect the retrieved value of soil moisture significantly. The inversion procedure provides more reliable soil moisture estimates when surfaces rougher than those analyzed in the field experiment are considered.

Measuring geophysical parameters of the Greenland ice sheet using airborne radar altimetry

AbstractThis paper presents radar-altimeter scattering models for each of the diagenetic zones of the Greenland ice sheet. AAFE radar-altimeter waveforms obtained during the 1991 and 1993 NASA multi-sensor airborne altimetry experiments over Greenland reveal that the Ku-band return pulse changes significantly with the different diagenetic zones. These changes are due to varying amounts of surface and volume scattering in the return waveform.In the ablation and soaked zones, where surface scattering dominates the AAFE return, geophysical parameters such as rms surface height and rms surface slope are obtained by fitting the waveforms to a surface-scattering model. Waveforms from the percolation zone show that sub-sruface ice features have a much more significant effect on the return pulse than the surrounding snowpack. Model percolation waveforms, created using a combined surface- and volume-scattering model and an ice-feature distribution obtained during the 1993 field season, agree well with actual AAFE waveforms taken in the same time period. Using a combined surface- and volume-scattering model for the dry-snow-zone return waveforms, the rms surface height and slope and the attenuation coefficient of the snowpack are obtained. These scattering models not only allow geophysical parameters of the ice sheet to he measured but also help in the understanding of satellite radar-altimeter data.

Measuring geophysical parameters of the Greenland ice sheet using airborne radar altimetry

AbstractThis paper presents radar-altimeter scattering models for each of the diagenetic zones of the Greenland ice sheet. AAFE radar-altimeter waveforms obtained during the 1991 and 1993 NASA multi-sensor airborne altimetry experiments over Greenland reveal that the Ku-band return pulse changes significantly with the different diagenetic zones. These changes are due to varying amounts of surface and volume scattering in the return waveform.In the ablation and soaked zones, where surface scattering dominates the AAFE return, geophysical parameters such as rms surface height and rms surface slope are obtained by fitting the waveforms to a surface-scattering model. Waveforms from the percolation zone show that sub-sruface ice features have a much more significant effect on the return pulse than the surrounding snowpack. Model percolation waveforms, created using a combined surface- and volume-scattering model and an ice-feature distribution obtained during the 1993 field season, agree well with actual AAFE waveforms taken in the same time period. Using a combined surface- and volume-scattering model for the dry-snow-zone return waveforms, the rms surface height and slope and the attenuation coefficient of the snowpack are obtained. These scattering models not only allow geophysical parameters of the ice sheet to he measured but also help in the understanding of satellite radar-altimeter data.

A combined surface-and volume-scattering model for ice-sheet radar altimetry

AbstractOver the last 15 years, satellite-altimeter data have been used to produce surface-elevation maps of the Greenland and Antarctic ice sheets with a 2 m accuracy. Analysis of Seasat and Geosat cross-over points showed that satellite altimeters can measure changes in the mass balance of the ice sheets. The retracking algorithm used to extract surface elevations from Seasat and Geosat return wave forms is based upon a modified form of the Brown surface-scattering model. Recent work has shown that altimeter wave forms over higher-altitude regions of the ice sheets are affected by sub-surface volume-scattering. Here, we develop a theoretical model for altimeter return wave forms over the ice sheets that is based on a combination of surface-and volume-scattering. By approximating the altimeter’s antenna pattern and transmitted pulse shape with Gaussian functions, we derive a closed-form analytical solution for the return-power volume-scattered from beneath the ice-sheet surface. We then combine the volume-scattering model with the Brown model and apply it to average wave forms from the Greenland and Antarctic ice sheets. The results show that the combined model accurately describes variations in altimeter wave-form shapes that are produced by differing contributions of surface-and volume-scattering to the received power. The combined model is then used to simulate return wave forms from a dual-frequency altimeter. The simulation shows that a two-frequency system can provide quantitative estimates of the absorption and scattering coefficients for near-surface snow.

A combined surface-and volume-scattering model for ice-sheet radar altimetry

AbstractOver the last 15 years, satellite-altimeter data have been used to produce surface-elevation maps of the Greenland and Antarctic ice sheets with a 2 m accuracy. Analysis of Seasat and Geosat cross-over points showed that satellite altimeters can measure changes in the mass balance of the ice sheets. The retracking algorithm used to extract surface elevations from Seasat and Geosat return wave forms is based upon a modified form of the Brown surface-scattering model. Recent work has shown that altimeter wave forms over higher-altitude regions of the ice sheets are affected by sub-surface volume-scattering. Here, we develop a theoretical model for altimeter return wave forms over the ice sheets that is based on a combination of surface-and volume-scattering. By approximating the altimeter’s antenna pattern and transmitted pulse shape with Gaussian functions, we derive a closed-form analytical solution for the return-power volume-scattered from beneath the ice-sheet surface. We then combine the volume-scattering model with the Brown model and apply it to average wave forms from the Greenland and Antarctic ice sheets. The results show that the combined model accurately describes variations in altimeter wave-form shapes that are produced by differing contributions of surface-and volume-scattering to the received power. The combined model is then used to simulate return wave forms from a dual-frequency altimeter. The simulation shows that a two-frequency system can provide quantitative estimates of the absorption and scattering coefficients for near-surface snow.