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NASA NTRS1987

Automated rectification and geocoding of SAR imagery

An automated post-processing system has been developed for rectification and geocoding of SAR (Synthetic Aperture Radar) imagery. The system uses as input a raw uncorrected image from the operational SAR correlator, and produces as a standard output a rectified and geocoded product. The accurate geolocation of SAR image pixels is provided by a spatial transformation model which maps the slant range-azimuth SAR image pixels into their location on a prespecified map grid. This model predicts the geodetic location of each pixel by utilizing: the sensor platform position; a geoid model; the parameters of the data collection system and the processing parameters used in the SAR correlator. Based on their geodetic locations, the pixels are mapped by using the desired cartographic projection equations. This rectification and geocoding technique has been tested with Seasat and SIR-B images. The test results demonstrate absolute location uncertainty of less than 50 m and relative distortion (scale factor and skew) of less than 0.1 percent relative to local variations from the assumed geoid.

Kwok, R.↗

NASA NTRS1988

SAR imagery of the Grand Banks (Newfoundland) pack ice pack and its relationship to surface features

Synthetic Aperture Radar (SAR) data and aerial photographs were obtained over pack ice off the East Coast of Canada in March 1987 as part of the Labrador Ice Margin Experiment (LIMEX) pilot project. Examination of this data shows that although the pack ice off the Canadian East Coast appears essentially homogeneous to visible light imagery, two clearly defined zones of ice are apparent on C-band SAR imagery. To identify factors that create the zones seen on the radar image, aerial photographs were compared to the SAR imagery. Floe size data from the aerial photographs was compared to digital number values taken from SAR imagery of the same ice. The SAR data of the inner zone acquired three days apart over the melt period was also examined. The studies indicate that the radar response is governed by floe size and meltwater distribution.

Argus, S. D.↗

NASA NTRS1987

SAR image data compression for an on-line archive system

This paper summarizes the investigation of SAR image data compression for an on-line archive data distribution system. This system is planned for the ground processing system of Alaska SAR Facility (ASF) and Shuttle Imaging Radar (SIR-C). The objective of the SAR image data compression is to enable the data archive system to provide the remote users a large data base with good image quality, short response time, low transfer cost, and minimal decoding complexity. The requirements and limitations of the on-line archive data distribution system are presented. The effects of SAR image data characteristics on data compression are addressed. The users' survey results suggest that compression ratios between 10:1 and 20:1 appear suitable. Based on the algorithm evaluation results, the two-level tree-searched vector quantization technique has been recommended as the SAR image data compression algorithm for the on-line archive data distribution system.

Chang, C. Y.↗

NASA NTRS1991

Integration of SAR and DEM data: Geometrical considerations

General principles for integrating data from different sources are derived from the experience of registration of SAR images with digital elevation models (DEM) data. The integration consists of establishing geometrical relations between the data sets that allow us to accumulate information from both data sets for any given object point (e.g., elevation, slope, backscatter of ground cover, etc.). Since the geometries of the two data are completely different they cannot be compared on a pixel by pixel basis. The presented approach detects instances of higher level features in both data sets independently and performs the matching at the high level. Besides the efficiency of this general strategy it further allows the integration of additional knowledge sources: world knowledge and sensor characteristics are also useful sources of information. The SAR features layover and shadow can be detected easily in SAR images. An analytical method to find such regions also in a DEM needs in addition the parameters of the flight path of the SAR sensor and the range projection model. The generation of the SAR layover and shadow maps is summarized and new extensions to this method are proposed.

Kropatsch, Walter G.↗

NASA NTRS1991

Automated extraction of pressure ridges from SAR images of sea ice - Comparison with surface truth

The authors estimate the characteristics of ridges and leads in sea ice from SAR (synthetic aperture radar) images. Such estimates are based on the hypothesis that bright filamentary features in SAR sea ice images correspond with pressure ridges. A data set collected in the Greenland Sea in 1987 allows this hypothesis to be evaluated for X-band SAR images. A preliminary analysis of data collected from SAR images and ice elevation (from a laser altimeter) is presented. It is found that SAR image brightness and ice elevation are clearly related. However, the correlation, using the data and techniques applied, is not strong.

Vesecky, J. F.↗

NASA NTRS1992

Interpretation of SAR imagery of the Greenland ice sheet using coregistered TM imagery

Landsat TM images are coregistered with a Seasat SAR image of the margin of the Greenland ice sheet and used in the interpretation of features in the SAR data. A winter TM image is used to provide topographic information while a summer TM image provides information on the pattern of melt and the location of lakes. It is shown that: (1) the snow line is easily detectable in SAR imagery; (2) areas of higher radar backscatter in the bare-ice zone most often correspond to areas full of crevasses too small to resolve in the SAR images; (3) subsurface scattering causes significant blurring of features in SAR imagery; and (4) the band of surface lakes occurring above the snow line corresponds to at least a portion of the wet-snow zone.

Bindschadler, Robert↗

NASA NTRS1992

Using calibrated SAR data

A number of approaches for calibrating SAR imaging data including data from multipolarization and multifrequency systems developed at the Jet Propulsion Laboratory are discussed. It is shown how calibrated SAR data can be used to improve the understanding of the physical properties of the earth's surface layer and how calibration uncertainties and system noise should be handled by the SAR data user. Examples of calibrated SAR data from the NASA/JPL DC-8 SAR are used to demonstrate use of calibrated data to monitor temporal change and to improve the classification of land cover type.

Freeman, Anthony↗

NASA NTRS1993

Arctic coastal polynya observations with ERS-1 SAR and DMSP SSM/I

Work to improve the characterization of the distribution of new and young sea ice types and open water amount within Arctic coastal polynyas through the combined use of ERS-1 SAR (Synthetic Aperture Radar) and DMSP SSM/I (Defense Meteorological Satellite Program Special Sensor Microwave/Imager) data is described. Two St. Lawrence Island polynya events are studied using low resolution, geocoded SAR images and coincident SSM/I data. The SAR images are analyzed in terms of polarization and spectral gradient ratios. Results of the combined analysis show that the SAR ice type classification is consistent with that from SSM/I and that the combined use of SAR and SSM/I can improve the characterization of thin ice better than either data set can do alone.

Cavalieri, D. J.↗

NASA NTRS1993

A general rough-surface inversion algorithm: Theory and application to SAR data

Rough-surface inversion has significant applications in interpretation of SAR data obtained over bare soil surfaces and agricultural lands. Due to the sparsity of data and the large pixel size in SAR applications, it is not feasible to carry out inversions based on numerical scattering models. The alternative is to use parameter estimation techniques based on approximate analytical or empirical models. Hence, there are two issues to be addressed, namely, what model to choose and what estimation algorithm to apply. Here, a small perturbation model (SPM) is used to express the backscattering coefficients of the rough surface in terms of three surface parameters. The algorithm used to estimate these parameters is based on a nonlinear least-squares criterion. The least-squares optimization methods are widely used in estimation theory, but the distinguishing factor for SAR applications is incorporating the stochastic nature of both the unknown parameters and the data into formulation, which will be discussed in detail. The algorithm is tested with synthetic data, and several Newton-type least-squares minimization methods are discussed to compare their convergence characteristics. Finally, the algorithm is applied to multifrequency polarimetric SAR data obtained over some bare soil and agricultural fields. Results will be shown and compared to ground-truth measurements obtained from these areas. The strength of this general approach to inversion of SAR data is that it can be easily modified for use with any scattering model without changing any of the inversion steps. Note also that, for the same reason it is not limited to inversion of rough surfaces, and can be applied to any parameterized scattering process.

Moghaddam, M.↗

NASA NTRS1998

The "Myth" of the Minimum SAR Antenna Area Constraint

A design constraint traceable ot the early days of spaceborne Synthetic Aperture Radar (SAR) is known as the minimum antenna area constraint for SAR. In this paper, it is confirmed that this constraint strictly applies only to the case where both the best possible resolution and the widest possible swath are the design goals. SAR antennas with area smaller than the constraint allows are shown to be possible, have been used on spaceborne SAR missions in the past, and should permit further, lower-cost SAR mission in the future.

Freeman, A.↗

NASA NTRS1997

On the Implementation of a Land Cover Classification System for SAR Images Using Khoros

The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.

Medina Revera, Edwin J.↗

NASA NTRS1993

(abstract) The EOS SAR Mission: A New Approach

The goal of the Earth Orbiting System Synthetic Aperture Radar (EOS SAR) program is to help develop the modeling and observational capabilities to predict and monitor terrestrial and oceanic processes that are either causing global change or resulting from global change. Specifically, the EOS SAR will provide important geophysical products to the EOS data set to improve our understanding of the state and functioning of the Earth system. The strategy for the EOS SAR program is to define the instrument requirements based on required input to geophysical algorithms, provide the processing capability and algorithms to generate such products on the required spatial (global) and temporal (3-5 days) scales, and to provide the spaceborne instrumentation with international partnerships. Initially this partnership has been with Germany; currently we are exploring broader international partnerships. A MultiSAR approach to the EOS SAR which includes a number of SARs provided by Japan, ESA, Germany, Canada, and the US in synergistic orbits could be used to attain a truly global monitoring capability using multifrequency polarimetric signatures. These concepts and several options for mission scenarios will be presented.

Earth Observing System radar imaging international↗

NASA NTRS2006

Three-Dimensional Human Bronchial-Tracheal Epithelial Tissue-Like Assemblies (TLAs) as Hosts for Severe Acute Respiratory Syndrome (SARS)-CoV Infection

A three-dimensional (3-D) tissue-like assembly (TLA) of human bronchial-tracheal mesenchymal (HBTC) cells with an overlay of human bronchial epithelial (BEAS-2B) cells was constructed using a NASA Bioreactor to survey the infectivity of SARS-CoV. This TLA was inoculated with a low passage number Urbani strain of SARS-CoV. At selected intervals over a 10-day period, media and cell aliquots of the 3-D TLA were harvested for viral titer assay and for light and electron microscopy examination. All viral titer assays were negative in both BEAS-2B two-dimensional monolayer and TLA. Light microscopy immunohistochemistry demonstrated antigen-antibody reactivity with anti-SARS-CoV polyclonal antibody to spike and nuclear proteins on cell membranes and cytoplasm. Coronavirus Group 2 cross-reactivity was demonstrated by positive reaction to anti-FIPV 1 and anti-FIPV 1 and 2 antibodies. TLA examination by transmission electron microscopy indicated increasing cytoplasmic vacuolation with numerous electron-dense bodies measuring 45 to 270 nm from days 4 through 10. There was no evidence of membrane blebbing, membrane duplication, or fragmentation of organelles in the TLAs. However, progressive disruption of endoplasmic reticulum was observed throughout the cells. Antibody response to SARS-CoV specific spike and nucleocapsid glycoproteins, cross-reactivity with FIPV antibodies, and the cytoplasmic pathology suggests this HBTE TLA model is permissive to SARS-CoV infection.

Suderman, M. T.↗

NASA NTRS2005

Single-Chip FPGA Azimuth Pre-Filter for SAR

A field-programmable gate array (FPGA) on a single lightweight, low-power integrated-circuit chip has been developed to implement an azimuth pre-filter (AzPF) for a synthetic-aperture radar (SAR) system. The AzPF is needed to enable more efficient use of data-transmission and data-processing resources: In broad terms, the AzPF reduces the volume of SAR data by effectively reducing the azimuth resolution, without loss of range resolution, during times when end users are willing to accept lower azimuth resolution as the price of rapid access to SAR imagery. The data-reduction factor is selectable at a decimation factor, M, of 2, 4, 8, 16, or 32 so that users can trade resolution against processing and transmission delays. In principle, azimuth filtering could be performed in the frequency domain by use of fast-Fourier-transform processors. However, in the AzPF, azimuth filtering is performed in the time domain by use of finite-impulse-response filters. The reason for choosing the time-domain approach over the frequency-domain approach is that the time-domain approach demands less memory and a lower memory-access rate. The AzPF operates on the raw digitized SAR data. The AzPF includes a digital in-phase/quadrature (I/Q) demodulator. In general, an I/Q demodulator effects a complex down-conversion of its input signal followed by low-pass filtering, which eliminates undesired sidebands. In the AzPF case, the I/Q demodulator takes offset video range echo data to the complex baseband domain, ensuring preservation of signal phase through the azimuth pre-filtering process. In general, in an SAR I/Q demodulator, the intermediate frequency (fI) is chosen to be a quarter of the range-sampling frequency and the pulse-repetition frequency (fPR) is chosen to be a multiple of fI. The AzPF also includes a polyphase spatial-domain pre-filter comprising four weighted integrate-and-dump filters with programmable decimation factors and overlapping phases. To prevent aliasing of signals, the bandwidth of the AzPF is made 80 percent of fPR/M. The choice of four as the number of overlapping phases is justified by prior research in which it was shown that a filter of length 4M can effect an acceptable transfer function. The figure depicts prototype hardware comprising the AzPF and ancillary electronic circuits. The hardware was found to satisfy performance requirements in real-time tests at a sampling rate of 100 MHz.

Gudim, Mimi↗

NASA NTRS2003

Modified Polar-Format Software for Processing SAR Data

HMPF is a computer program that implements a modified polar-format algorithm for processing data from spaceborne synthetic-aperture radar (SAR) systems. Unlike prior polar-format processing algorithms, this algorithm is based on the assumption that the radar signal wavefronts are spherical rather than planar. The algorithm provides for resampling of SAR pulse data from slant range to radial distance from the center of a reference sphere that is nominally the local Earth surface. Then, invoking the projection-slice theorem, the resampled pulse data are Fourier-transformed over radial distance, arranged in the wavenumber domain according to the acquisition geometry, resampled to a Cartesian grid, and inverse-Fourier-transformed. The result of this process is the focused SAR image. HMPF, and perhaps other programs that implement variants of the algorithm, may give better accuracy than do prior algorithms for processing strip-map SAR data from high altitudes and may give better phase preservation relative to prior polar-format algorithms for processing spotlight-mode SAR data.

Chen, Curtis↗

NASA NTRS2011

Improved Calibration of Modeled Discharge and Storage Change in the Atchafalaya Floodplain Using SAR Interferometry

This study focuses on the feasibility of using SAR interferometry to support 2D hydrodynamic model calibration and provide water storage change in the floodplain. Two-dimensional (2D) flood inundation modeling has been widely studied using storage cell approaches with the availability of high resolution, remotely sensed floodplain topography. The development of coupled 1D/2D flood modeling has shown improved calculation of 2D floodplain inundation as well as channel water elevation. Most floodplain model results have been validated using remote sensing methods for inundation extent. However, few studies show the quantitative validation of spatial variations in floodplain water elevations in the 2D modeling since most of the gauges are located along main river channels and traditional single track satellite altimetry over the floodplain are limited. Synthetic Aperture Radar (SAR) interferometry recently has been proven to be useful for measuring centimeter-scale water elevation changes over the floodplain. In the current study, we apply the LISFLOOD hydrodynamic model to the central Atchafalaya River Basin, Louisiana, during a 62 day period from 1 April to 1 June 2008 using two different calibration schemes for Manning's n. First, the model is calibrated in terms of water elevations from a single in situ gauge that represents a more traditional approach. Due to the gauge location in the channel, the calibration shows more sensitivity to channel roughness relative to floodplain roughness. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. Since SAR interferometry receives strongly scatters in floodplain due to double bounce effect as compared to specular scattering of open water, the calibration shows more dependency to floodplain roughness. An iterative approach is used to determine the best-fit Manning's n for the two different calibration approaches. Results suggest similar floodplain roughness but slightly different channel roughness. However, application of SAR interferometry provides a unique view of the floodplain flow gradients, not possible with a single gauge calibration. These gradients, allow improved computation of water storage change over the 46-day simulation period. Overall, the results suggest that the use of 2D SAR water elevation changes in the Atchafalaya basin offers improved understanding and modeling of floodplain hydrodynamics.

Jung, Hahn Chul↗

NASA NTRSDate not supplied

HydroSAR: A Cloud-based SAR Data Analysis Service to Monitor Hydrological Disasters and their Impact on Population and Agriculture

Weather-related hazards are ubiquitous around the world including: 1) hurricane storm surges, 2) rapid snowmelt and heavy rainfall, 3) severe weather leading to flash floods, and 4) seasonal freeze and thaw of rivers that may lead to ice jams. Each of these hazards affects human settlements and has the potential to impact agricultural productivity. In each setting, end-users in disaster management need access to data processing tools helpful in mapping past and current disasters. Analysis of past events supports risk mitigation by understanding what has already occurred and how to alleviate those impacts in the future. Having capabilities to generate the same products in a response setting means that lessons learned from risk analysis will carry forward to event response. Synthetic aperture radar (SAR) data are particularly useful for these activities due to their all-weather 24/7 monitoring capabilities. In this effort we present HydroSAR, a cloud-based SAR data analysis service for the mapping of meteorological and hydrological disasters as well as their impact on population and agriculture. As part of this project we have developed a series of SAR-based value added products for the monitoring of surface hydrology (image time series, change detection, flood extent, flood depth) and the assessment of impacts on population (flood depth) and agriculture (active agriculture, inundated agriculture, flood duration). We also developed a cloud-based platform for generating these products over affected areas and are working with end-users to integrate derived product into decision-making workflows The paper will briefly introduce the SAR-based products that were developed for this effort. We describe the cloud-based production pipeline that was built to automatically generate these products in near-real time over extended regions. The integration of SAR-based information into hazard preparation and response activities is described for a number of recent disasters including the 2019 forest fires in Alaska, 2019 flooding in the U.S. Midwest, the 2020 U.S. severe weather easter outbreak, 2020 tropical storm Christobal, 2020 cyclone Amphan, 2020, Alaska Spring breakup flooding, and the 2020 flood season in Eastern India, Bangladesh, and Nepal.

Franz Josef Meyer↗

NASA NTRS2017

Comparative View of Antenna/RF Subsystems between SIR-C and NISAR L-band SAR Systems for Wide-Swath Imaging

In 1994, SIR-C demonstrated ScanSAR, a mode of operating the SAR system that has become the “standard” implementation for wide-swath spaceborne imaging SAR systems. The NISAR SAR instruments introducing a new SAR architecture for wide-swath imaging call SweepSAR which is expected to have similar success. This paper compares the Antenna and RF subsystem design and the technology utilization considerations between the SIR-C planar phased array SAR system using the ScanSAR technique and NISAR off-set reflector with phased array feed using the SweepSAR technique.

Shaffer, Scott↗