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Vegetation growth observations by microwave scattering was investigated. The purpose of the study was: (1) to develop scattering models for an inhomogeneous medium; (2) to develop scattering models for an irregular surface; (3) to combine volume and surface scattering to obtain useful scattering and emission models for terrains; and (4) to apply the developed model to the interpretation of measured data and the design of future experiments.
A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).
A high frequency correction to the Kirchhoff approximation is developed for application to rough surface scattering. An approximate solution to the magnetic field integral equation for perfect conductivity and plane wave excitation yields a perturbed surface current expressed as a linear function of the second derivatives of surface height. The corrected surface current vector is substituted into the far field Stratton-Chu integral and average backscattered powers for the four polarization combinations are computed on the assumption that the surface is describable as a stationary Gaussian random process. The strength of this scattering solution is that it can account for height curvature correlation without requiring small height and slope.
Electromagnetic wave scattering by sea surfaces relevant to geodetic satellite altimeter design
Compact polarimetry has been shown to be an interesting alternative mode to full polarimetry when global coverage and revisit time are key issues. It consists on transmitting a single polarization, while receiving on two. Several critical points have been identified, one being the Faraday rotation (FR) correction and the other the calibration. When a low frequency electromagnetic wave travels through the ionosphere, it undergoes a rotation of the polarization plane about the radar line of sight for a linearly polarized wave, and a simple phase shift for a circularly polarized wave. In a low frequency radar, the only possible choice of the transmit polarization is the circular one, in order to guaranty that the scattering element on the ground is illuminated with a constant polarization independently of the ionosphere state. This will allow meaningful time series analysis, interferometry as long as the Faraday rotation effect is corrected for the return path. In full-polarimetric (FP) mode, two techniques allow to estimate the FR: Freeman method using linearly polarized data, and Bickel and Bates theory based on the transformation of the measured scattering matrix to a circular basis. In CP mode, an alternate procedure is presented which relies on the bare surface scattering properties. These bare surfaces are selected by the conformity coefficient, invariant with FR. This coefficient is compared to other published classifications to show its potential in distinguishing three different scattering types: surface, doublebounce and volume. The performances of the bare surfaces selection and FR estimation are evaluated on PALSAR and airborne data. Once the bare surfaces are selected and Faraday angle estimated over them, the correction can be applied over the whole scene. The algorithm is compared with both FP techniques. In the last part of the paper, the calibration of a CP system from the point of view of classical matrix transformation methods in polarimetry is proposed.
An electride may provide surface enhanced Raman scattering (SERS). The electride, a compound where the electrons serve as anions, may be a ceramic electride, such as a conductive ceramic derived from mayenite, or an organic electride, for example. The textured electride surface or electride particles may strongly enhance the Raman scattering of organic or other Raman active analytes. This may also provide a sensitive method for monitoring the chemistry and electronic environment at the electride surface. The results are evidence of a new class of polariton (i.e., a surface electride-polariton resonance mechanism) that is analogous to the surface plasmon-polariton resonance that mediates conventional SERS.
The Compact Reconnaissance Imaging Spectral Mapper (CRISM) onboard the Mars Reconnaissance Orbiter (MRO) obtains pole-to-pole observations (i.e., full MRO orbits) of vertical profiles for visible/near-IR spectra (λ=0.4–4.0 μm), which are ideally suited to identifying the composition and particle sizes of Mars ice and dust aerosols over 50–100 km altitudes in the Mars mesosphere. Within the coverage limitations of the CRISM limb data set, a distinct compositional dichotomy is found in Mars mesospheric ice aerosols. CO2 ice clouds appear during the aphelion period of Mars orbit (Solar Longitudes, Ls∼0–160°) at low latitudes (∼20S–10N) over specific longitude regions (Meridiani, Valles Marineris) and at typical altitudes of 55–75 km. Apart from faint water ice hazes below 55 km, mesospheric H2O ice clouds are primarily restricted to the perihelion orbital range (Ls∼160 – 350°) at northern and southern mid-to-low latitudes with less apparent longitudinal dependences. Mars mesospheric CO2 clouds are presented in CRISM spectra with a surprisingly large range of particle sizes (cross section weighted radii, Reff=0.3 to 2.2 μm). The smaller particle sizes (Reff ≤1 μm) appear concentrated near the spatial (latitude and altitude) boundaries of their global occurrences. CRISM spectra of mesospheric CO2 clouds also show evidence of iridescence, indicating very narrow particle size distributions (effective variance, Veff∼0.03) and so very abrupt CO2 cloud nucleation. Furthermore, these clouds are sometimes accompanied by altitude coincident peaks in 1.27 μm O2 dayglow, which indicates very dry, cold regions of formation. Mesospheric water ice clouds generally exhibit small particle sizes (Reff=0.1–0.3 μm), although larger particle sizes (Reff=0.4–0.7 μm) appear infrequently. On average, water ice cloud particle sizes decrease with altitude over 50–80 km in the perihelion mesosphere. Water ice mass appears similar in clouds over a large range of observed cloud particle sizes, with particle number densities increasing to ∼10 cm−3 for Reff=0.2 μm. Near coincident Mars Climate Sounder (MCS) temperature and aerosol profile measurements for a subset of CRISM mesospheric aerosol measurements indicate near saturation (H2O and CO2) conditions for ice clouds and distinct mesospheric temperature increases associated with mesospheric dust loading. Dayside (3 pm) mesospheric CO2 clouds with larger particle sizes (Reff ≥0.5 μm) scatter surface infrared emission in MCS limb infrared radiances, as well as solar irradiance in the MCS solar band channel. Scattering of surface infrared emission is most strikingly presented in nighttime (3 am) MCS observations at 55–60 km altitudes, indicating extensive mesospheric nighttime CO2 clouds with considerably larger particle sizes (Reff∼7 μm). Mesospheric CO2 ice clouds present cirrus-like waveforms over extensive latitude and longitude regions (10°×10°), as revealed in coincident Mars Color Imager (MARCI) nadir imaging. Solar tides, gravity waves, and the large orbital variation of the extended thermal structure of the Mars atmosphere influence all of these behaviors. Mesospheric dust aerosols appear infrequently over the non-global (planet encircling) dust storm era of the CRISM limb data set (2009–2016), and exhibit smaller particle sizes (Reff=0.2–0.7 μm) relative to dust in the lower atmosphere. One isolated case of an aphelion (Ls=96°) mesospheric dust layer with large dust particle sizes (Reff ∼2 μm) over Syria Planum may reflect high altitude, non-local transport of dust over elevated regions.
The Compact Reconnaissance Imaging Spectral Mapper (CRISM) onboard the Mars Reconnaissance Orbiter (MRO) obtains pole-to-pole observations (i.e., full MRO orbits) of vertical profiles for visible/near-IR spectra (λ= 0.4–4.0 μm), which are ideally suited to identifying the composition and particle sizes of Mars ice and dust aerosols over 50–100 km altitudes in the Mars mesosphere. Within the coverage limitations of the CRISM limb data set, a distinct compositional dichotomy is found in Mars mesospheric ice aerosols. CO2 ice clouds appear during the aphelion period of Mars orbit (Solar Longitudes, L(s )∼ 0–160°) at low latitudes (∼20S–10N) over specific longitude regions (Meridiani, Valles Marineris) and at typical altitudes of 55–75 km. Apart from faint water ice hazes below 55 km, mesospheric H2O ice clouds are primarily restricted to the perihelion orbital range (L(s)∼160 – 350°) at northern and southern mid-to-low latitudes with less apparent longitudinal dependences. Mars mesospheric CO2 clouds are presented in CRISM spectra with a surprisingly large range of particle sizes (cross section weighted radii, R(eff) = 0.3 to 2.2 μm). The smaller particle sizes (R(eff) ≤1 μm) appear concentrated near the spatial (latitude and altitude) boundaries of their global occurrences. CRISM spectra of mesospheric CO2 clouds also show evidence of iridescence, indicating very narrow particle size distributions (effective variance, V(eff) ∼ 0.03) and so very abrupt CO2 cloud nucleation. Furthermore, these clouds are sometimes accompanied by altitude coincident peaks in 1.27 μm O2 dayglow, which indicates very dry, cold regions of formation. Mesospheric water ice clouds generally exhibit small particle sizes (R(eff) = 0.1–0.3 μm), although larger particle sizes (R(eff) = 0.4–0.7 μm) appear infrequently. On average, water ice cloud particle sizes decrease with altitude over 50–80 km in the perihelion mesosphere. Water ice mass appears similar in clouds over a large range of observed cloud particle sizes, with particle number densities increasing to ∼10 per cu. cm for R(eff) = 0.2 μm. Near coincident Mars Climate Sounder (MCS) temperature and aerosol profile measurements for a subset of CRISM mesospheric aerosol measurements indicate near saturation (H2O and CO2) conditions for ice clouds and distinct mesospheric temperature increases associated with mesospheric dust loading. Dayside (3 pm) mesospheric CO2 clouds with larger particle sizes (R(eff) ≥0.5 μm) scatter surface infrared emission in MCS limb infrared radiances, as well as solar irradiance in the MCS solar band channel. Scattering of surface infrared emission is most strikingly presented in nighttime (3 am) MCS observations at 55–60 km altitudes, indicating extensive mesospheric nighttime CO2 clouds with considerably larger particle sizes (R(eff)∼7 μm). Mesospheric CO2 ice clouds present cirrus-like waveforms over extensive latitude and longitude regions (10°×10°), as revealed in coincident Mars Color Imager (MARCI) nadir imaging. Solar tides, gravity waves, and the large orbital variation of the extended thermal structure of the Mars atmosphere influence all of these behaviors. Mesospheric dust aerosols appear infrequently over the non-global (planet encircling) dust storm era of the CRISM limb data set (2009–2016), and exhibit smaller particle sizes (R(eff) = 0.2–0.7 μm) relative to dust in the lower atmosphere. One isolated case of an aphelion (L(s) = 96°) mesospheric dust layer with large dust particle sizes (R(eff) ∼2 μm) over Syria Planum may reflect high altitude, non-local transport of dust over elevated regions.
A new technique for fitting a three-component scattering mechanism model to the polarimetric synthetic aperture radar (SAR) data itself, without utilizing any ground truth measurements, is presented. The three scattering mechanism components included in the model are volume scatter from randomly oriented dipoles, first-order Bragg surface scatter and a dihedral scattering mechanism for two surfaces with different dielectric constants. The model fit yields an estimate of the contribution to the total backscatter of each of the three components. The backscatter contributions can also be compared to give the relative percentage weight of each. The model fit has an equal number of input parameters (the polarimetric radar backscatter measurements) and output parameters (the backscatter parameters describing them). The model can be applied to entire images or to small areas within an image to give a first-order estimate of the relevant scattering mechanisms. The model was applied to many C-, L- and P-band Airborne SAR (AIRSAR) images of different types of terrain. Results were presented at the workshop.
A scatter model is developed based on the matrix doubling method for volume scattering and the Kirchhoff method in rough surface scattering. Scattering from vegetation is assumed to be dominated by leaves and a single leaf is modeled by a thin dielectric disk. In developing the phase matrix for the disk, field within the disk is taken to be constant over the disk thickness, but phase changes across the surface of the disk are accounted for. Comparisons of this scatter model with radar measurements indicate good agreements in polarization, angular trends, and frequency up to Ku-band. This represents a considerable improvement over low-frequency scatter models which are valid up to S-band.
Goldstone radar observations of the equatorial plains of Venus provide complementary information to that obtained by Magellan. Different radar scattering mechanisms dominate each system, leading to sampling of different surface properties. Comparison of image data and derived parameters indicate that: (1) relatively high dielectric constants on impact-related parabolic features are detected in Goldstone backscatter, Magellan reflectivity, and Magellan emissivity data; the dielectric effects are overwhelmed by roughness-related signatures in Magellan synthetic aperture radar (SAR) data; (2) lava flows in Navka Planitia show dielectric variations both among and within flows; higher dielectric constants on the perimeter of some flows may by due to a decrease in vesicularity; (3) some volcanic domes are relatively smooth at the wavelength scale and probably consist of low-density deposits; (4) comparisons of Magellan SAR data with rough surface scattering models and SAR data of terrestrial surfaces indicate that the roughness characteristics of the equatorial plains surfaces are comparable to modified terrestrial lava flows; and (5) scattering properties of an equatorial 'ridge belt' structure suggest highly weathered or soil-dominated surfaces.
Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0° (nadir) and 50°. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the air–snow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous air–snow interfaces, buried beneath newly deposited snow. The additional scattering from previous air–snow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the air–snow interface decreases, and the snow–sea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8 dB (Ka-band) and 5 dB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice.
The S-193 Radscat made extensive measurements of many sea conditions. Measurements were taken in a tropical hurricane (Ava), a tropical storm (Christine), and in portions of extratropical cyclones. Approximately 200 scans of ocean data at 105 kilometer spacings were taken during the first two Skylab missions and another 200 during the final mission when the characteristics of the measurements changed due to damage of the antenna. Backscatter with four transmit/receive polarization combinations and emissions with horizontal and vertical receive polarizations were measured. Other surface parameters investigated for correlation with the measurements included sea temperature, air/sea temperature difference, and gravity-wave spectrum. Methods were developed to correct the microwave measurements for atmospheric effects. The radiometric data were corrected accurately for clear sky and light cloud conditions only. The radiometer measurements were used to recover the surface scattering characteristics for all atmospheric conditions excluding rain. The radiometer measurements also detected the presence of rain which signaled when the scattering measurement should not be used for surface wind estimation. Regression analysis was used to determine empirically the relation between surface parameters and the microwave measurements, after correction for atmospheric effects. Results indicate a relationship approaching square-law at 50 deg between differential scattering coefficient and wind speed with horizontally polarized scattering data showing slightly more sensitivity to wind speed than vertically polarized data.
Satellite remote sensing has provided powerful tools for constructing long-term records of observations of many of Earth's geophysical processes. Geophysicists studying climage change would like to construct time series of data which are as long, accurate, and consistent as possible. While technological advances continue to improve the quality of observations from space, they also present consistency problems. The scanning multichannel microwave radiometer (SMMR), which operated from October 1978 to August 1987, and the special sensor microwave imager (SSMI), which overlapped with the SMMR for nearly two months in 1987, have provided microwave radiances which have been used to monitor long-term changes in sea ice concentration and snow accumulation, among other things. Inspection has shown, however, that brightness temperatures from the two sensors over the same polar firn-covered scene can differ by as much as 14 K. Calibration corrections for polar firn have been derived; in this paper, we present calculations addressing the physics of the small frequency and viewing angle differences between the SMMR and the SSMI on microwave emission from polar scenes containing free water. We focus here only on surface emission. We use a surface scattering model and study the effects of surface roughness, snow wetness, snow density, and young sea ice concentration. We also compare data from Antarctica with our modeled results. We find that for most scenes, surface roughness dominates over the effects of frequency and viewing angle differences, but that for open long-term times series, data must be calibrated and constructed at the geophysical product level rather than at the level of measured radiances.
This talk will focus first on the information contained in the surface-scattered light from leaves, plant canopies and surface waters. This light is in general polarized and depends upon surface roughness. Thus, for example, - The surface reflection from shiny green leaves measured in the specular direction shows no chlorophyll absorption bands, no 'red edge.' - Conversely, the degree of linear polarization of such light displays marked variation with wavelength having local maxima in the chlorophyll absorption bands and an inverted red edge. - Plant canopies with shiny leaves distributed in angle like the area on a sphere, specularly reflect sunlight in the subsolar or specular direction- but also in every other view direction. - Canopies of green plants may appear white not green when viewed obliquely toward the sun. - In a light to moderate wind, the often blindingly bright glitter of sunlight off smooth water surfaces provides a strong, angularly narrow signature reflection characteristic of inundated vegetated areas that are big sources of atmospheric methane, a climatically important greenhouse gas. (Conversely, a blindingly bright glitter-type reflection is uncharacteristic of upland or wind ruffled open water areas that are poor sources of atmospheric methane.) Because some of these results may be 'head scratchers,' it's always important to properly calibrate ones instruments. Indeed, as the second portion of the talk will show, the characteristics of the light measuring instrument, particularly its entrance aperture, may affect the results and should be taken into account during across-instrument data comparisons.
The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The seasonal evolution of albedo for the MOSAiC year was constructed from spatially averaged broadband albedo values for each line. Specific locations were identified as representative of individual ice surface types, including accumulated dry snow, melting snow, bare and melting ice, melting and refreezing ponded ice, and sediment-laden ice. The area-averaged seasonal progression of total albedo recorded during MOSAiC showed remarkable similarity to that recorded 22 years prior on multiyear sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) expedition. In accord with these and other previous field efforts, the spectral albedo of relatively thick, snow-free, melting sea ice shows invariance across location, decade, and ice type. In particular, the albedo of snow-free, melting seasonal ice was indistinguishable from that of snow-free, melting second-year ice, suggesting that the highly scattering surface layer that forms on sea ice during the summer is robust and stabilizing. In contrast, the albedo of ponded ice was observed to be highly variable at visible wavelengths. Notable temporal changes in albedo were documented during melt and freeze onset, formation and deepening of melt ponds, and during melt evolution of sediment-laden ice. While model simulations show considerable agreement with the observed seasonal albedo progression, disparities suggest the need to improve how the albedo of both ponded ice and thin, melting ice are simulated.
Estimation of path attenuation is a critical part of retrieving precipitation parameters using measurements from the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement Mission (GPM) satellite. In this paper, we describe the latest implementation of the Surface Reference Technique that uses surface scattering properties to infer path attenuation through the precipitation. Both single- and dual-frequency versions of this method are available and while the dual-frequency version appears to be more accurate at moderate rain rates, the single-frequency approach at Ku-band is needed when the Ka-band data are not available. Despite improvements afforded by the dual-frequency version of the method, other methods such as the Hitschfeld-Bordan and standard dual-frequency approaches offer advantages particularly at lighter rain rates and at near-nadir incidence angles over land. Weighted averages of the results from these methods appear to offer the best estimate of path attenuation presently available.
U-6Nb is a uranium alloy containing 6 wt% niobium that possesses high corrosion resistance. The structure and composition of the passivating oxide layer formed on air-aged U-6Nb, which gives the material its corrosion resistant properties, was characterized using surface scattering techniques. Stable oxide layers formed on the surface of a set of U-6Nb alloy thin films under ambient conditions were investigated using neutron reflectometry (NR), x-ray reflectometry (XRR) and grazing incidence x-ray diffraction (GIXD). The passivating oxide was composed of approximately 27% U, 5% Nb, and 68% O, primarily consisting of a thin niobium oxide layer (5.5 ± 0.4 nm) separating a thicker UO2 layer (27.1 ± 2.3 nm) from the underlying U-6Nb alloy. A critical density of enriched niobium oxide at the metal-oxide interface is hypothesized to limit oxygen diffusion and confer high corrosion resistance to the alloy.