SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
In this paper, an algorithm is described which allows derivation of three fundamental parameters from SAR data: Soil moisture, soil roughness and canopy water content...
In this paper, we will briefly describe the instrument characteristics, the evolution of the various radar modes, the instrument performance and improvement in the knowledge of the positioning and attitude of information of the radar.
The mixed hardwood and conifer forests of northern Michigan were overflown by a 3-frequency airborne imaging radar in Apr. and Jul. 1990. A set of 10 x 10 km test sites near the University of Michigan Biological Station at Douglas Lake and within the Hiawatha National Forest in the upper peninsula of Michigan contained training stands representing the various forest species typical of forest communities across the ecotone between the coniferous boreal forest and mid-latitude hardwood and coniferous forests. The polarimetric radar data were externally calibrated to allow interdate comparisons. The Apr. flight was prior to bud-break of deciduous species and patchy snowcover was present. The Jul. flights occurred during and 2 days after heavy rain showers, and provide a unique opportunity to examine the differences in radar backscatter attributable to intercepted precipitation. Analyses show that there are significant changes in backscattering between biophysically dissimilar forest stands on any given date and also between dates for a given forest stand. These differences in backscattering can be related to moisture properties of the forest floor and the overlying canopy and also to the quantity and organizational structure of the above-ground biomass.
A multi-sensor aircraft campaign called the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 resulted in acquisition of high quality multispectral images in the visible, near infrared, shortwave infrared, thermal infrared, and microwave regions of the electromagnetic spectrum. The airborne data sets include the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the Thermal Infrared Multispectral Scanner (TIMS), and the Airborne Synthetic Aperture Radar (SAR). Ancillary data include Landsat Thematic Mapper, laboratory and field spectral measurements, and traditional geologic mapping. The GRSFE data for a site in the northern Death Valley, (California and Nevada) region were calibrated to physical units and geometrically registered to a map base. Various aspects of this experiment are briefly discussed.
Explore the source record for details and available documents.
A technique is presented to physically characterize changes in radar backscatter with frequency in multifrequency single polarization radar images that can be used as a first step in the analysis of the data and the retrieval of geophysical parameters. The technique is automatic, relatively independent of the incidence angle, and only requires a good calibration accuracy between the different frequencies. The technique reveals large areas where scattering changes significantly with frequency and whether the surface has the characteristics of a smooth, slightly rough, rough, or very rough surface.
During the last several years, significant efforts in microwave remote sensing were devoted to relating forest parameters to radar backscattering coefficients. These and other studies showed that in most cases, the longer wavelength (i.e. P band) and cross-polarization (HV) backscattering had higher sensitivity and better correlation to forest biomass. This research examines this relationship in a northern forest area through both backscatter modeling and synthetic aperture radar (SAR) data analysis. The field measurements were used to estimate stand biomass from forest weight tables. The backscatter model described by Sun et al. was modified to simulate the backscattering coefficients with respect to stand biomass. The average number of trees per square meter or radar resolution cell, and the average tree height or diameter breast height (dbh) in the forest stand are the driving parameters of the model. The rest of the soil surface, orientation, and size distributions of leaves and branches, remain unchanged in the simulations.
The part of the troposphere influenced by the surface of the earth is termed the atmospheric boundary layer. Flow within this layer is influenced by the roughness of the surface; rougher surfaces induce more turbulence than smoother surfaces and, hence, higher atmospheric transfer rates across the surface. Roughness elements also shield erodible particles, thus decreasing the transport of windblown particles. Therefore, the aerodynamic roughness length (z(sub 0)) is an important parameter in aeolian and atmospheric boundary layer processes as it describes the aerodynamic properties of the underlying surface. z(sub 0) is assumed to be independent of wind velocity or height, and dependent only on the surface topography. It is determined using in situ measurements of the wind speed distribution as a function of height. For dry, unvegetated soils the intensity of the radar backscatter (sigma(sup 0)) is affected primarily by surface roughness at a scale comparable with the radar wavelength. Thus, both wind and radar respond to surface roughness variations on a scale of a few meters or less. Greeley showed the existence of a correlation between z(sub 0) and sigma(sup 0). This correlation was based on measurements over lava flows, alluvial fans, and playas in the southwest deserts of the United States. It is shown that the two parameters behave similarly also when there are small changes over a relatively homogeneous surface.
Based on symmetry properties, polarimetric remote sensing of geophysical media is studied. From the viewpoint of symmetry groups, media with reflection, rotation, azimuthal, and centrical symmetries are considered. The symmetries impose relations among polarimetric scattering coefficients, which are valid to all scattering mechanisms in the symmetrical configurations. Various orientation distributions of non-spherical scatterers can be identified from the scattering coefficients by a comparison with the symmetry calculations. Experimental observations are then analyzed for many geophysical scenes acquired with the Jet Propulsion Laboratory (JPL) airborne polarimetric SAR at microwave frequencies over sea ice and vegetation. Polarimetric characteristics of different ice types are compared with symmetry behaviors. The polarimetric response of a tropical rain forest reveals characteristics close to the centrical symmetry properties, which can be used as a distributed target to relatively calibrate polarimetric radars without any deployment of manmade calibration targets.
We investigate how multifrequency and polarimetric synthetic aperture radar (SAR) imagery enhances present capability to discriminate different ice conditions in single-frequency, single-polarization satellite SAR data. Frequencies considered are C- (lambda = 5.6cm), L- (lambda = 24cm) and P- (lambda = 68cm) band. Radar backscatter characteristics of six radiometrically and polarimetrically distinct ice types are selected from a cluster analysis of the multifrequency polarimetric SAR data and used to classify SAR images. Validation of these ice conditions is based on information provided by aerial photos, weather and ice surface measurements acquired at an ice camp, together with airborne passive microwave imagery, and visual analysis of the SAR data. The six identified sea-ice types are: (1) multiyear sea-ice; (2) compressed first year ice; (3) first year rubble and ridges; (4) first year rough ice; (5) first year smooth ice; and (6) thin ice. Open water is absent in all analyzed data. Classification of the SAR imagery into those six ice types is performed using a Bayesian Maximum A Posteriori classifier. Two complete scenes acquired at different dates in different locations are classified. The scenes were chosen such that they are representative of typical ice conditions in the Beaufort Sea in March 1988 and because ancillary information is available for validating the segmentation of various ice surface conditions.
The Stovepipe Wells Dune Field provides a unique opportunity to observe several dune forms in one scene. These forms include reverse dunes, star dunes, transverse, and linear dunes. A sand mantle surrounds the dune field and can also be observed in the radar image. Dune types were discriminated best in co-polarized channels. Three major wind directions are responsible for the various dune forms. Winds from the north and south are responsible for the reverse dunes, winds from north for the transverse dunes, and the north - south and westerly winds for the star dunes. The winds also reflect the topographic configuration of this part of Death Valley. Vegetation over the dunes was most pronounced in the cross-polarized images. Lancaster et al. (1992) find that cross-polarized images are most useful in differentiating active from inactive dunes. This is because the vegetation backscatter signature is present over inactive dunes. Future studies should include multiple look and incidence angles to determine if the dune forms can still be seen at other angles.
A polarimetric technique for improving the visibility of waves, whose propagation direction has an azimuthal component, in RAR (real aperture radar) or SAR (synthetic aperture radar) images has been investigated. The technique shows promise as a means of producing more accurate 2-D polarimetric RAR ocean wave spectra. For SAR applications domination by velocity-bunching effects may limit its usefulness to long ocean swell. A modification of this technique involving measurement of polarization signature modulations in the image is useful for detecting waves in SAR images and, potentially, estimating RMS wave slopes.
In this paper an algorithm is described that allows derivation of three fundamental parameters from synthetic aperture radar (SAR) data: soil moisture, soil roughness, and canopy water content, accounting for the effects of vegetation cover by using optical (Landsat) data as auxiliary. The capabilities and limitations of the data and algorithms are discussed, as well as possibilities to use these data in energy/water balance modeling studies. All of the data used in this study was acquired as part of the European Field Experiment in a Desertification Threatened Area.
Here we discuss an indirect approach for measuring ocean features from synthetic aperture radar (SAR) imagery. The approach is based on the refraction of swell that can be seen in the SAR imagery. Locally, swell refraction is due only to changes in bathymetry and surface current shear and it is easy to separate these two effects. It has been shown that linear energetic shears can be detected and measured from high resolution images of the ocean. A simple approach to measuring surface velocity and shear is to divide the imagery into smaller segments where the shear in each segment is approximately linear. The known linear algorithm would then be applied to each segment and the velocity/shear distribution can then be determined by assembling the segments with linear shear into an estimate of the actual shear/velocity distribution.
Explore the source record for details and available documents.
In this paper, we present the results of raw echo data analysis with data error recovery, data processing, and the calibration results of the je Propulsion Laboratory's airborne synthetic aperature radar for the pacific Rim II mission.
Explore the source record for details and available documents.
Polarimetric and multifrequency SAR data are used to construct a multi-tier estimation algorithm for successive derivation of the variables describing the entire forest canopy.