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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Three-frequency, polarimetric, airborne SAR observations of the Greenland ice sheet

Synthetic aperture radar (SAR) images of the Greenland ice sheet collected by an airborne system clearly reveal the four melting facies of this sheet defined 30 years ago from snow stratigraphy studies by glaciologists. In particular, the radar echoes from the percolation facies have radiometric and polarimetric characteristics that are unique among terrestrial surfaces, but that resemble the exotic radar echoes recorded from the icy Galilean satellites. There, the radar signals interact with subsurface, massive ice features created in the cold, dry snow by seasonal melting and refreezing events. The subsurface features act as efficient reflectors of the incident radiation most likely via internal reflections. In the soaked-snow facies, the radar reflectivity is much lower because radar signals are attenuated by the wetter snow before they can interact with subsurface structures. Inversion algorithms to derive geophysical information from the SAR data are developed in both cases to estimate snow wetness in the soaked-snow facies and the mass of ice water retained in the percolation facies.

Rignot, E.↗
NASA NTRS1995

Ice flow dynamics of the Greenland ice sheet from SAR interferometry

Synthetic-aperture radar (SAR) interferograms produced from ESA's ERS-1 satellite, provide the first synoptic view of ice flow dynamics of the western sector of the Greenland Ice Sheet. Glacial motion is detected in the radar ranging direction at millimetric scales, across a complete sequence of snow accumulation and melting regimes, despite significant varations in their radar scattering properties. Ice flow evolves from a slow, regular motion at the higher elevations. At lower elevations, motion is strongly convoluted by meter-scale undulations in surface topography, which have a unique interferometric signature that enables a novel approach for retrieving flow direction. Inferred flow directions, combined with surface displacements in the radar ranging direction, yield ice velocity estimates that are within 6% of in-situ measurements gathered along a 40 km survey line. Application of repeat-pass SAR interferometry to the entire Greenland Ice Sheet should enable precise mapping of its ice flow dynamics at an unprecedented level of spatial detail.

Rignot, E.↗
NASA NTRS1995

Computing Thickness Of Sea Ice From Polarimetric SAR Data

Artificial neural network developed for computing thickness of sea ice from polarimetric synthetic-aperture-radar (SAR) data. Once neural network trained, no further intervention needed: when stimulated with SAR scattering data, quickly responds with estimate of thickness of sea ice.

Huynh, Dave D.↗
NASA NTRS1995

Software For Tie-Point Registration Of SAR Data

SAR-REG software package registers synthetic-aperture-radar (SAR) image data to common reference frame based on manual tie-pointing. Image data can be in binary, integer, floating-point, or AIRSAR compressed format. For example, with map of soil characteristics, vegetation map, digital elevation map, or SPOT multispectral image, as long as user can generate binary image to be used by tie-pointing routine and data are available in one of the previously mentioned formats. Written in FORTRAN 77.

Rignot, Eric↗
NASA NTRS1995

SAR investigations of glaciers in northwestern North America

The objective of this project was to investigate the utility of satellite synthetic aperture radar (SAR) imagery for measurement of geophysical parameters on Alaskan glaciers relevant to their mass balance and dynamics, including: (1) the positions of firn lines (late-summer snow lines); (2) surface velocities on fast-flowing (surging) glaciers, and also on slower steady-flow glaciers; and (3) the positions and changes in the positions of glacier termini. Preliminary studies of topography and glacier surface velocity with SAR interferometry have also been carried out. This project was motivated by the relationships of multi-year to decadal changes in glacier geometry to changing climate, and the probable significant contribution of Alaskan glaciers to rising sea level.

Lingle, Craig S.↗
NASA NTRS1993

ERS-1 SAR backscatter changes associated with ice growing on shallow lakes in Arctic Alaska

Spatial and temporal backscatter intensity (sigma(sup o)) variations from ice growing on shallow lakes during winter 1991-92 near Barrow, NW Alaska, have been quantified for the first time using ERS-I C-band SAR data acquired at the Alaska SAR Facility. A field and laboratory validation program, including measurements of the thickness and structure-stratigraphy of the ice, indicates that sigma(sup o) values are strongly dependent on whether the ice freezes to the lake bottom, or remains afloat. Backscatter intensity decreases significantly when the ice grounds on the bottom. Strong backscatter from floating ice is attributed to a specular ice-water interface and vertically oriented tubular bubbles. During the spring thaw, backscatter undergoes a reversal; sigma(sup o) values from ice that was grounded increase, while sigma(sup o) values from ice that was afloat decrease. This phenomenon has not previously been reported.

Jeffries, M. O.↗
NASA NTRS1996

ERS-1 SAR monitoring of ice growth on shallow lakes to determine water depth and availability in north west Alaska

Images taken by the ERS-1 synthetic aperture radar (SAR) were used to identify and to differentiate between the lakes that freeze completely to the bottom and those that do not, on the North Slope, in northwestern Alaska. The ice thickness at the time each lake froze completely is determined with numerical ice growth model that gives a maximum simulated thickness of 2.2 m. A method combining the ERS-1 SAR images and numerical ice growth model was used to determine the ice growth and the water availability in these regions.

Jeffries, Martin↗
NASA NTRS1996

Geocoding of AIRSAR/TOPSAR SAR Data

It has been demonstrated that radar interferometry is a promising method for determination of digital elevation information and terrain slope from synthetic aperture radar (SAR) data. A multipolarimetric radar AIRSAR operates in the P, L, and C bands on board the NASA DC-8 aircraft. The TOPSAR, a special mode of the AIRSAR system, is able to collect single pass interferometric C and/or L band VV polarized data. A possible configuration of the AIRSAR/TOPSAR system is to acquire single pass interferometric data at C-band VV polarization and polarimetric radar data at the two other lower frequencies. The advantage of this configuration is to acquire digital topographic information at the same time the radar data is collected. The digital elevation information can therefore be used to correctly calibrate the SAR data. In this paper, a procedure to geocode the new AIRSAR/TOPSAR data is presented and an earlier AIRSAR/TOPSAR image is geocoded and evaluated in terms of geometric accuracy.

Holecz, Francesco↗
NASA NTRS1996

An Automated Mapping Processor using C-Band Interferometric SAR Data

We describe a processor which has been implemented to generate map products starting from C-band interferometric data. The first stage of the processor consists of the conventional interferometric synthetic aperture radar (SAR) processing producing a digital elevation model (DEM) and a SAR brightness image in sensor coordinates. In the second stage of processing, a land use classification map is obtained by using the DEM, brightness, and interferometric correlation layers. Auxiliary layers which include a drainage layer, a height gradient layer, a height error layer, an estimated penetration layer, and a shaded relief layer are also computed. In the final step, all UTM collocated layers are combined in a geographical information system (GIS) which allows for both hard copy map products and digital applications.

Rodriguez, E.↗
NASA NTRS1996

Performance of Polarimetric Processing Techniques using NAWC P-3 SAR Imagery

The use of synthetic aperture radar (SAR) polarimetric processing for enhancing the detection, classification, and/or identification of scene scattering features is described. This paper describes and compares the results obtained from applying the polarimetric techniques that have been developed and/or advanced by researchers at MIT Lincoln Laboratory, and basic polarimetric match filter (PMF) techniques that have been modified to treat distributed scatterers. The paper describes the individual polarimetric processing techniques and the formulation used fro their application to polarimetric imagery obtained from the NAWC P-3 SAR. In all cases, the polarimetric techniques have been applied to enhance the detection of distributed scatterers in clutter The emphasis arises from considering most complex scatterers of interest (either man made or natural) as distributed scatterers consisting of multiple scattering centers, and many modern polarimetric radar systems have the resolution performance to resolve the multiple scattering centers. Furthermore, the individual scattering centers of a distributed target can often exhibit different polarimetric scattering characteristics, and consequently do not respond favorably to polarimetric processing techniques derived for individual point scatterers. The treatment of distributed scatterers also includes concepts for tuning the polarimetric ensemble response of individual scattering centers.

Teti, J. G., Jr.↗
NASA NTRS1996

An Automated Mapping Processor Using C-Band Interferometric SAR Data

We present the description of a processor which has been implemented to generate map products starting from C-band interferometric data. The first stage of the processor consists of the conventional interferometric SAR processing producing a Digital Elevation Model (DEMs) and a SAR brightness image in sensor coordinates. In the second stage of processing, a land use classification map is obtained by using the DEM, brightness, and interferometric correlation layers. Auxiliary layers which include a drainage layer, a height gradient layer, a height error layer, an estimated penetration layer, and a shaded relief layer are also computed. In the final step, all UTM collocated layers are combined in a GIS system which allows for both hard copy map products and for digital applications.

Rodriguez, E.↗
NASA NTRS1997

Monitoring of the effects of fire in North American boreal forests using ERS SAR imagery

ERS synthetic aperture radar (SAR) imagery represents a tool for monitoring the effects of fires in boreal regions. Fire-scar signatures from ERS SAR collected over Canada and Alaska are presented. The temporal variability exhibited throughout the growing season is underlined. The investigation showed that these signatures have a seasonal trend related to the patterns of soil moisture originating from snow melts in the spring and precipitation during the growing season. These signatures appear in all the regions of the North American boreal forest and remain visible for up to 13 years after a fire.

Kasischke, E. S.↗
NASA NTRS1997

Dynamic behavior of the Bering Glacier-Bagley icefield system during a surge, and other measurements of Alaskan glaciers with ERS SAR imagery

ERS-1 synthetic aperture radar (SAR) imagery was employed for the measurement of the dynamics of the Bagley icefield during a major surge in 1993-1994, the measurement of ice velocities on the Malaspina piedmont glacier during a quiescent phase between surges, and for mapping the snow lines and the position of the terminus of Nabesna glacier on Mount Wrangell (a 4317 m andesitic shield volcano) in the heavily glacierized Saint Elias and Wrangell Mountains of Alaska. An overview and summary of results is given. The methods used include interferometry, cross-correlation of sequential images, and digitization of boundaries using terrain-corrected SAR imagery.

Lingle, Craig S.↗
NASA NTRS1998

Characteristics of Forests in Western Sayani Mountains, Siberia from SAR Data

This paper investigated the possibility of using spaceborne radar data to map forest types and logging in the mountainous Western Sayani area in Siberia. L and C band HH, HV, and VV polarized images from the Shuttle Imaging Radar-C instrument were used in the study. Techniques to reduce topographic effects in the radar images were investigated. These included radiometric correction using illumination angle inferred from a digital elevation model, and reducing apparent effects of topography through band ratios. Forest classification was performed after terrain correction utilizing typical supervised techniques and principal component analyses. An ancillary data set of local elevations was also used to improve the forest classification. Map accuracy for each technique was estimated for training sites based on Russian forestry maps, satellite imagery and field measurements. The results indicate that it is necessary to correct for topography when attempting to classify forests in mountainous terrain. Radiometric correction based on a DEM (Digital Elevation Model) improved classification results but required reducing the SAR (Synthetic Aperture Radar) resolution to match the DEM. Using ratios of SAR channels that include cross-polarization improved classification and

Ranson, K. Jon↗
NASA NTRS1997

Tracking of Ice Edges and Ice Floes by Wavelet Analysis of SAR Images

This paper demonstrates the use of wavelet transforms in the tracking of sequential ice features in the ERS-1 synthetic aperture radar (SAR) imagery, especially in situations where feature correlation techniques fail to yield reasonable results. Examples include the evolution of the St. Lawrence polynya and summer sea ice change in the Beaufort Sea. For the polynya, the evolution of the region of young ice growth surrounding a polynya can be easily tracked by wavelet analysis due to the large backscatter difference between the young and old ice. Also within the polynya, a 2D fast Fourier transform (FFT) is used to identify the extent of the Langmuir circulation region, which is coincident with the wave-agitated frazil ice growth region, where the sea ice experiences its fastest growth. Therefore, the combination of wavelet and FFT analysis of SAR images provides for the large-scale monitoring of different polynya features. For summer ice, previous work shows that this is the most difficult period for ice trackers due to the lack of features on the sea ice cover. The multiscale wavelet analysis shows that this method delineates the detailed floe shapes during this period, so that between consecutive images, the floe translation and rotation can be estimated.

Liu, Antony K.↗
NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗
NASA NTRS2000

Classification of the Gabon SAR Mosaic Using a Wavelet Based Rule Classifier

A method is developed for semi-automated classification of SAR images of the tropical forest. Information is extracted using the wavelet transform (WT). The transform allows for extraction of structural information in the image as a function of scale. In order to classify the SAR image, a Desicion Tree Classifier is used. The method of pruning is used to optimize classification rate versus tree size. The results give explicit insight on the type of information useful for a given class.

Simard, Marc↗
NASA NTRS2000

Orbital SAR and Ground-Penetrating Radar for Mars: Complementary Tools in the Search for Water

The physical structure and compositional variability of the upper martian crust is poorly understood. Optical and infrared measurements probe at most the top few cm of the surface layer and indicate the presence of layered volcanics and sediments, but it is likely that permafrost, hydrothermal deposits, and transient liquid water pockets occur at depths of meters to kilometers within the crust. An orbital synthetic aperture radar (SAR) can provide constraints on surface roughness, the depth of fine-grained aeolian or volcanic deposits, and the presence of strongly absorbing near-surface deposits such as carbonates. This information is crucial to the successful landing and operation of any rover designed to search for subsurface water. A rover-based ground-penetrating radar (GPR) can reveal layering in the upper crust, the presence of erosional or other subsurface horizons, depth to a permafrost layer, and direct detection of near-surface transient liquid water. We detail here the radar design parameters likely to provide the best information for Mars, based on experience with SAR and GPR in analogous terrestrial or planetary environments.

Campbell, B. A.↗