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Procedures developed to obtain both raw measured and surface roughness statistics for radar backscatter modeling are described. A comprehensive and highly flexible software package for terrain analysis is introduced.
Radar backscatter measurements collected at both C- and Ku-Band during the recent SurfaceWaves Dynamics Experiment (SWADE) on 1 March 1991 show dramatic variabilities of thenormalized radar cross section (sigma degree) of the ocean surface at low wind speed. Additionally,measurements of the sigma degree in the cross wind direction fluctuated much more than the sigmadegree in the upwind direction. The C- and Ku-band data are quite similar, both exhibiting a morepronounced roll off of sigma degree with decreasing neutral stability wind than indicated bypreviously published empirical model functions. The data show extremely large azimuthalmodulations, in some cases greater than 20 dB, and show good qualitative agreement with theazimuthal modulation predicted.
The aim of the research was to investigate the relationship between wind, waves, and radar backscatter from water surface. To this end, three field experiments with periods of 2 to 4 weeks were carried out during summer months in 1988, 1989 and 1990. For these periods, the University of Washington group provided (1) environmental parameters such as wind speed, wind stress, and atmospheric stratification through measurements of surface fluxes (of momentum, sensible heat and latent heat) and of air and water temperatures; and (2) wave height spectra including both the dominant waves and the short gravity-capillary waves. Surface flux measurements were performed by using our well tested instruments: a K-Gill twin propeller-vane anemometer and a fast response thermocouple psychrometer. Wave heights were measured by a resistance wire wave gauge. The University of Kansas group was responsible for the operation of the microwave radars.
Ocean radar backscatter in the presence of large waves is investigated using data acquired with the Jet Propulsion Laboratory NUSCAT radar at Ku band for horizontal and vertical polarizations and the University of Massachusetts CSCAT radar at C band for vertical polarization during the Surface Wave Dynamics Experiment. Off-nadir backscatter data of ocean surfaces were obtained in the presence of large waves with significant wave height up to 5.6 m. In moderate-wind cases, effects of large waves are not detectable within the measurement uncertainty and no noticeable correlation between backscatter coefficients and wave height is found. Under high-wave light-wind conditions, backscatter is enhanced significantly at large incidence angles with a weaker effect at small incidence angles. Backscatter coefficients in the wind speed range under consideration are compared with SASS-2 (Ku band), CMOD3-H1 (C band), and Plant's model results which confirm the experimental observations. Variations of the friction velocity, which can give rise to the observed backscatter behaviors in the presence of large waves, are presented.
Ocean surface condition correlation to radar backscattering cross sections and wind velocity from scatterometer data
The normalized standard deviation, Kp, of radar backscatter measurements using digital Doppler processors in spaceborne scatterometers is derived. The Kp expression for analog Doppler filter processors, such as that used in the Seasat scatterometer is shown to be a special case of the derived Kp expression. A connection to Welch's (1967) power spectrum estimation rsults is also made. Tradeoff studies in digital filter design such as hardware complexity, computational speed, and system performance can be performed based on this Kp expression. A current application in the design of the NASA scatterometer to be flown in 1990 is discussed. This derivation should be useful for system design and analysis of other radar remote-sensing instruments.
The use of dual-frequency data of backscattering coefficients at a fixed angle to estimate surface roughness parameters is evaluated. Radar backscattering coefficients at 1.5 and 4.25 GHz are calculated using a model based on Kirchhoff approximation of electromagnetic wave scatttering from a rough soil surface. Plots of the calculated backscattering coefficients for Kansas soil moisture contents at the C- and L-band frequencies and HH polarization are analyzed. The effects of changes in correlation length on the backscattering coefficients are investigated. The calculated backscattering coefficients are compared with scatterometer data collected at 1.5 and 4.25 GHz, and it is detected that the model and field data correlate well. The data reveal that it is possible to retrieve the surface roughness parameters from measured radar data.
Minima offset from nominal crosswind directions. Report describes experimental and theoretical study of azimuthal anisotropy in radar backscatter from surface of ocean. Important objective of this and related studies to enhance ability to sense speed and direction of surface wind remotely by use of airborne or spaceborne radar.
Ongoing mapping of the Ganiki Planitia (V14) quadrangle of Venus and definition of material units has involved an integrated but qualitative analysis of Magellan radar backscatter images and topography using standard geomorphological mapping techniques. However, such analyses do not take full advantage of the quantitative information contained within the images. Analysis of the backscatter coefficient allows a much more rigorous statistical comparison between mapped units, permitting first order selfsimilarity tests of geographically separated materials assigned identical geomorphological labels. Such analyses cannot be performed directly on pixel (DN) values from Magellan backscatter images, because the pixels are scaled to the Muhleman law for radar echoes on Venus and are not corrected for latitudinal variations in incidence angle. Therefore, DN values must be converted based on pixel latitude back to their backscatter coefficient values before accurate statistical analysis can occur. Here we present a method for performing the conversions and analysis of Magellan backscatter data using commonly available ArcGIS software and illustrate the advantages of the process for geological mapping.
The relationships between the gas exchange, wind speed, friction velocity, and radar backscatter from the water surface was investigated using data obtained in a large water tank in the Delft (Netherlands) wind-wave tunnel, filled with water supersaturated with SF6, N2O, and CH4. Results indicate that the gas-transfer velocities of these substances were related to the wind speed with a power law dependence. Microwave backscatter from water surface was found to be related to gas transfer velocities by a relationship in the form k(gas) = a 10 exp (b A0), where k is the gas transfer velocity for the particular gas, the values of a and b are obtained from a least squares fit of the average backscatter cross section and gas transfer at 80 m, and A0 is the directional (azimuthal) averaged return.
The study of the collective effects of radar scattering from an aggregation of discrete scatterers randomly distributed in a space is important for better understanding the origin of the backscatter from spatially extended geophysical targets (SEGT). We consider the microstructure irregularities of a SEGT as the essential factor that affect radar backscatter. To evaluate their contribution this study uses the "slice" approach: particles close to the front of incident radar wave are considered to reflect incident electromagnetic wave coherently. The radar equation for a SEGT is derived. The equation includes contributions to the total backscatter from correlated small-scale fluctuations of the slice's reflectivity. The correlation contribution changes in accordance with an earlier proposed idea by Smith (1964) based on physical consideration. The slice approach applied allows parameterizing the features of the SEGT's inhomogeneities.
Several algorithms to calculate a rain-rate profile from a single-frequency air-or spaceborne radar backscatter profile and a given path-integrated attenuation have been proposed. The accuracy of any such algorithm is limited by the ambiguities between the (multiple) exact solutions, which depend on the variability of the parameters in the Z-R and k-R relations used. In this study, coupled Z-R and k-R relations are derived based on the drop size distribution. It is then shown that, because of the coupling, the relative difference between the multiple mutually ambiguous rain-rate profiles solving the problem must remain acceptably low, provided the available path-integrated attenuation value is known to within 0.5 dB.
The present investigation has the objective to develop a simple 'user's' model for simulating the measured radar backscattering coefficients from vegetation-covered fields in conjunction with the data obtained by Jackson et al. (1980, 1982). The theoretical work reported by Fung and Eom (1981) provides the basis for the model. Certain modifications are related to a consideration of the effect of a vegetation canopy. The first part of the model is concerned with a description of scatter from rough bare soil, while the second part takes into account the effect of a vegetation cover. It is shown that the measured angular distribution of the backscattering coefficient of vegetation-covered fields can be satisfactory reproduced by using the developed model.
The scattering properties of second-year ice were studied in an experiment at Mould Bay in April 1983. Radar backscattering measurements were made at frequencies of 5.2, 9.6, 13.6, and 16.6 GHz for vertical polarization, horizontal polarization and cross polarizations, with incidence angles ranging from 15 to 70 deg. The results indicate that the second-year ice scattering characteristics were different from first-year ice and also different from multiyear ice. The fading properties of radar signals were studied and compared with experimental data. The influence of snow cover on sea ice can be evaluated by accounting for the increase in the number of independent samples from snow volume with respect to that for bare ice surface. A technique for calculating the snow depth was established by this principle and a reasonable agreement has been observed. It appears that this is a usable way to measure depth in snow or other snow-like media using radar.
Results of an experimental program is reviewed which over the past five years has succeeded in documenting the variations of the radar backscattering coefficient of a variety of crop types as a function of time, signal frequency (1-18 GHz), angular range (nadir to 80 deg) and polarization (HH, VV and HV). The systems were the microwave active spectrometers (MAS); one MAS system covers the 1-8 GHz band and the other system covers the 8-18 GHz band. Each MAS system was mounted on a mobile truck-mounted boom and was operated by a computer controller. To date, these two systems have acquired over 3 million data points from agricultural crops, bare ground and trees.
We describe the calibration and analysis of multi-frequency, multi-polarization radar backscatter signatures over an agriculture test site in the Netherlands. The calibration procedure involved two stages: in the first stage, polarimetric and radiometric calibrations (ignoring noise) were carried out using square-base trihedral corner reflector signatures and some properties of the clutter background. In the second stage, a novel algorithm was used to estimate the noise level in the polarimetric data channels by using the measured signature of an idealized rough surface with Bragg scattering (the ocean in this case). This estimated noise level was then used to correct the measured backscatter signatures from the agriculture fields. We examine the significance of several key parameters extracted from the calibrated and noise-corrected backscatter signatures. The significance is assessed in terms of the ability to uniquely separate among classes from 13 different backscatter types selected from the test site data, including eleven different crops, one forest and one ocean area. Using the parameters with the highest separation for a given class, we use a hierarchical algorithm to classify the entire image. We find that many classes, including ocean, forest, potato, and beet, can be identified with high reliability, while the classes for which no single parameter exhibits sufficient separation have higher rates of misclassification. We expect that modified decision criteria involving simultaneous consideration of several parameters increase performance for these classes.
The initial results of an experiment to examine the dependence of radar image intensity on total above-ground biomass in a southern US pine forest ecosystem are presented. Two sets of data are discussed. First, we examine two L-band (VV-polarization) data sets which were collected 5 years apart. These data sets clearly illustrate the change in backscatter resulting from the growth of a young pine stand. Second, we examine the dependence between radar backscatter and biomass as a function of radar frequency using data from the JPL Airborne Synthetic Aperture Radar (AIRSAR) and ERIM/NADC P-3 SAR systems. These results show that there is a positive correlation between above-ground biomass and radar backscatter and at C-, L-, and P-bands, but very little correlation at C-band. The biomass level for which this positive correlation holds decreases as radar frequency increases. This positive correlation is stronger at HH and HV polarizations that VV polarization at L- and P-bands, but strongest at VV polarization for C-band.
Several regression models were tested to explain the wind direction dependence of the 1975 JONSWAP (Joint North Sea Wave Project) scatterometer data. The models consider the radar backscatter as a harmonic function of wind direction. The constant term accounts for the major effect of wind speed and the sinusoidal terms for the effects of direction. The fundamental accounts for the difference in upwind and downwind returns, while the second harmonic explains the upwind-crosswind difference. It is shown that a second harmonic model appears to adequately explain the angular variation. A simple inversion technique, which uses two orthogonal scattering measurements, is also described which eliminates the effect of wind speed and direction. Vertical polarization was shown to be more effective in determining both wind speed and direction than horizontal polarization.