Parallel Computing Implementation for ScanCAR Mode Data
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In June 1991, the NASA/JPL airborne SAR (AIRSAR) acquired C- (lambda = 5.6cm), L- (lambda = 24cm), and P- (lambda = 68m) band polarimetric SAR data over the Greenland ice sheet. These data are processed using version 3.55 of the AIRSAR processor which provides radiometrically and polarimetrically calibrated images. The internal calibration of the AIRSAR data is cross-checked using the radar response from corner reflectors deployed prior to flight in one of the scenes. In addition, a quantitative assessment of the noise power level at various frequencies and polarizations is made in all the scenes. Synoptic SAR data corresponding to a swath width of about 12 by 50 km in length (compared to the standard 12 x 12 km size of high-resolution scenes) are also processed and calibrated to study transitions in radar backscatter as a function of snow facies at selected frequencies and polarizations. The snow facies on the Greenland ice sheet are traditionally categorized based on differences in melting regime during the summer months. The interior of Greenland corresponds to the dry snow zone where terrain elevation is the highest and no snow melt occurs. The lowest elevation boundary of the dry snow zone is known traditionally as the dry snow line. Beneath it is the percolation zone where melting occurs in the summer and water percolates through the snow freezing at depth to form massive ice lenses and ice pipes. At the downslope margin of this zone is the wet snow line. Below it, the wet snow zone corresponds to the lowest elevations where snow remains at the end of the summer. Ablation produces enough meltwater to create areas of snow saturated with water, together with ponds and lakes. The lowest altitude zone of ablation sees enough summer melt to remove all traces of seasonal snow accumulation, such that the surface comprises bare glacier ice.
This paper discusses SAR imaging with emphasis on radar backscatter properties. In studying how planetary surfaces modulate the radar cross-section, it is determined that both the amount of and variation in backscattered microwave energy provide the necessary cues (i.e., object shading and boundary information) for stereointerpretation. While past research into automated reconstruction of topography from radar stereopairs has concentrated on the use of shading, it is shown that boundary information may also be used successfully. How these attributes can be potentially misleading are discussed. This work suggests a process for generating high-quality topography maps from SAR imagery.
The Jurassicprok Interferometric Calibration Software (also called "Calibration Processor" or simply "CP") estimates the calibration parameters of an airborne synthetic-aperture-radar (SAR) system, the raw measurement data of which are processed by the Jurassicprok software described in the preceding article. Calibration parameters estimated by CP include time delays, baseline offsets, phase screens, and radiometric offsets. CP examines raw radar-pulse data, single-look complex image data, and digital elevation map data. For each type of data, CP compares the actual values with values expected on the basis of ground-truth data. CP then converts the differences between the actual and expected values into updates for the calibration parameters in an interferometric calibration file (ICF) and a radiometric calibration file (RCF) for the particular SAR system. The updated ICF and RCF are used as inputs to both Jurassicprok and to the companion Motion Measurement Processor software (described in the following article) for use in generating calibrated digital elevation maps.
The primary objective of this study is to estimate the flux of heat and freshwater resulting from sea ice melt in the polar seas. The approach taken is to examine the decay of sea ice in the summer months primarily through the use of spaceborne Synthetic Aperture Radar (SAR) imagery. The improved understanding of the dynamics of the melt process can be usefully combined with ice thermodynamic and upper ocean models to form more complete models of ice melt. Models indicate that more heat is absorbed in the upper ocean when the ice cover is composed of smaller rather than larger floes and when there is more open water. Over the course of the summer, floes disintegrate by physical forcing and heating, melting into smaller and smaller sizes. By measuring the change in distribution of floes together with open water over a summer period, we can make estimates of the amount of heating by region and time. In a climatic sense, these studies are intended to improve the understanding of the Arctic heat budget which can then be eventually incorporated into improved global climate models. This work has two focus areas. The first is examining the detailed effect of storms on floe size and open water. A strong Arctic low pressure storm has been shown to loosen up the pack ice, increase the open water concentration well into the pack ice, and change the distribution of floes toward fewer and smaller floes. This suggests episodic melting and the increased importance of horizontal (lateral) melt during storms. The second focus area is related to an extensive ship-based experiment that recently took place in the Arctic called Surface Heat Budget of the Arctic (SHEBA). An icebreaker was placed purposely into the older pack ice north of Alaska in September 1997. The ship served as the base for experimenters who deployed extensive instrumentation to measure the atmosphere, ocean, and ice during a one-year period. My experiment will be to derive similar measurements (floe size, open water, temporal change) using spaceborne SAR data obtained during the summer of 1998, and compare these results with an ocean and ice model of summer melt. Additional information is contained in the original.
Linear-estimator subalgorithm optimized for local terrain. Algorithm processes some of information in synthetic-aperture-radar echoes from quasi-homogeneous targets, yielding optimal estimates of Doppler frequency shifts. Differs from one described in article, "Estimating SAR Doppler Shifts From Homogeneous Targets", NPO-17869, though offers similar advantages for measurements of wind shears and speeds of ocean currents. Derivation of algorithm involves some of same terminology and simplifying assumptions, however, target area considered quasi-homogeneous in sense it consists of patchwork of subareas, each of which is homogeneous target differing from its neighbors. This assumption more realistic than assumption of homogeneity.
Science objectives, opportunities and requirements are discussed for the utilization of data from the Synthetic Aperture Radar (SAR) on the European First Remote Sensing Satellite, to be flown by the European Space Agency in the early 1990s. The principal applications of the imaging data are in studies of geophysical processes taking place within the direct-reception area of the Alaska SAR Facility in Fairbanks, Alaska, essentially the area within 2000 km of the receiver. The primary research that will be supported by these data include studies of the oceanography and sea ice phenomena of Alaskan and adjacent polar waters and the geology, glaciology, hydrology, and ecology of the region. These studies focus on the area within the reception mask of ASF, and numerous connections are made to global processes and thus to the observation and understanding of global change. Processes within the station reception area both affect and are affected by global phenomena, in some cases quite critically. Requirements for data processing and archiving systems, prelaunch research, and image processing for geophysical product generation are discussed.
We examine the sensitivity of ERS-1 C-band synthetic aperture radar (SAR) backscatter to springtime snow and vegetation thaw dynamics for boreal forest stands within the BOREAS Southern Study Area (SSA) in Canada during the 1994 winter-spring thaw transition.
The Magellan mission to Venus is providing planetary scientists with massive amounts of new data about the surface geology of Venus. Digital image processing is an integral part of the ground data system that provides data products to the investigators. The mosaicking of synthetic aperture radar (SAR) image data from the spacecraft is being performed at JPL's Multimission Image Processing Laboratory (MIPL). MIPL hosts and supports the Image Data Processing Subsystem (IDPS), which was developed in a VAXcluster environment of hardware and software that includes optical disk jukeboxes and the TAE-VICAR (Transportable Applications Executive-Video Image Communication and Retrieval) system. The IDPS is being used by processing analysts of the Image Data Processing Team to produce the Magellan image data products. Various aspects of the image processing procedure are discussed.
Radar remote sensing data provide a unique perspective of the earth's crust and the processes that have influenced its evolution. Physically based models are required, however, to relate the geophysical quantities being measured by the radar sensor to useful geologic information. In this study, synthetic aperture radar (SAR) data over the Cima volcanic field in the Mojave Desert of California are quantitatively connected with microtopography through inversion of a radar backscatter model. Changes in surface roughness inferred from the derived microtopography are modeled and found to be consistent with aeolian mantling as surfaces age. Estimated rates of aeolian deposition for the Cima area are compared to the Lunar Crater volcanic field in Nevada. Rates of deposition appear to be higher at Cima volcanic field, most likely because of its proximity to Soda Lake, the main source of the aeolian material.
Model results indicate that understanding summer heat balance and freshwater balance in the polar oceans requires knowledge of how much goes into vertical and lateral sea ice melt. In addition to thickness, two of the key ice parameters that affect melt rate are ice concentration and floe size. Smaller ice floes and more open water enables more heat to go into lateral melt preferentially to vertical melt, thereby enhancing warming up the upper ocean and increasing stratification. Using ERS-1 SAR imagery along two areas, one in the Beaufort Sea and another in the Chukchi Sea, floe size distributions were obtained during the summer period in 1992. Comparisons will be made of floe distributions, together with meteorological and buoy measurements, to examine the differences between an ice sink region (Chukchi) and a multiyear ice region (Beaufort) in the summer melt process.
One of the sensors of the Seasat satellite was a synthetic aperture radar (SAR), which was operated over both oceanic and land areas. The Seasat SAR was an active imaging microwave system which transmitted and received horizontally polarized radiation at L-band frequency (1.275 GHz, 23-cm wavelength). Extensive coverage was obtained over North America, Europe, the Eastern Pacific Ocean, the Western and Northern Atlantic Ocean, and the Beaufort Sea. Surface coverage was also acquired over limited portions of Central America, the Gulf of Mexico, and the Caribbean Sea. The majority of the data has been optically processed in a so-called survey mode. Each optically processed Seasat pass has a swath width of 100 km at a scale of 1:500,000. A subset of the SAR data has been digitally processed in a so-called high-resolution mode. Digital processing has been performed upon selected scenes with dimensions of 100 x 100 km. Digitally processed imagery has a nominal ground resolution of 25 m.
The digital data recording system (DDRS) was designed, fabricated, tested, and delivered. This unit is the interface between the synthetic aperture radar (SAR) and the recording system. The SAR data are formatted in the DDRS for data processing on the ground.
Results of digital processing of airborne X-band synthetic aperture radar (SAR) data acquired over Dade County, Florida, and Acadia Parish, Louisiana are presented. The goal was to investigate the utility of SAR data for land cover mapping and area estimation under the AgRISTARS Domestic Crops and Land Cover Project. In the case of the Acadia Paris study area, LANDSAT multispectral scanner (MSS) data were also used to form a combined SAR and MSS data set. The results of accuracy evaluation for the SAR, MSS, and SAR/MSS data using supervised classification show that the combined SAR/MSS data set results in an improved classification accuracy of the five land cover classes as compared with SAR-only and MSS-only data sets. In the case of the Dade County study area, the results indicate that both HH and VV polarization data are highly responsive to the row orientation of the row crop but not to the specific vegetation which forms the row structure. On the other hand, the HV polarization data are relatively insensitive to the orientation of row crop. Therefore, the HV polarization data may be used to discriminate the specific vegetation that forms the row structure.
Quantitative techniques are available which allow the analysis of SAR images for the derivation of geological surface and process data. In conjunction with calibrated radar sensors operating at several incidence angles, wavelengths, and polarizations, the compilation of multiparameter radar signatures of lithological and geomorphic units can accordingly proceed for geological mapping in unknown areas. While radar image tone can be used in arid zones to derive surface micromorphology, heavily vegetated tropical regions require the analysis of radar image texture by means of Fourier techniques which decompose the image into bandpasses that represent different scales of texture.
The Magellan synthetic aperture radar (SAR) produces Venus surface images from data collected by the SAR carried on board the Magellan spacecraft. The core of the primary Magellan SAR processor is the digital correlator subsystem (DCS). The pipeline DSC architecture enables the Magellan primary SAR processor (PSP) to achieve real-time data processing capability. The implementation and performance of the DSC are described. Hardware (H/W) constraints that influenced the processing algorithm design are highlighted.
The ISSI software package is designed to image the ionosphere from space by calibrating and processing polarimetric synthetic aperture radar (PolSAR) data collected from low Earth orbit satellites. Signals transmitted and received by a PolSAR are subject to the Faraday rotation effect as they traverse the magnetized ionosphere. The ISSI algorithms combine the horizontally and vertically polarized (with respect to the radar system) SAR signals to estimate Faraday rotation and ionospheric total electron content (TEC) with spatial resolutions of sub-kilometers to kilometers, and to derive radar system calibration parameters. The ISSI software package has been designed and developed to integrate the algorithms, process PolSAR data, and image as well as visualize the ionospheric measurements. A number of tests have been conducted using ISSI with PolSAR data collected from various latitude regions using the phase array-type L-band synthetic aperture radar (PALSAR) onboard Japan Aerospace Exploration Agency's Advanced Land Observing Satellite mission, and also with Global Positioning System data. These tests have demonstrated and validated SAR-derived ionospheric images and data correction algorithms.
RIG is a modeling system which creates synthetic aperture radar (SAR) and inverse SAR images from 3-D faceted data bases. RIG is based on a physical optics model and includes the effects of multiple reflections. Both conducting and dielectric surfaces can be modeled; each surface is labeled with a material code which is an index into a data base of electromagnetic properties. The inputs to the program include the radar processing parameters, the target orientation, the sensor velocity, and (for inverse SAR) the target angle rates. The current version of RIG can be run on any workstation, however, it is not a real-time model. We are considering several approaches to enable the program to generate realtime radar imagery. In addition to its image generation function, RIG can also generate radar cross-section (RCS) plots as well as range and doppler radar return profiles.