Search NASA⌕ Search

SEARCH · Search NASA

Results for “SAR SAR imaging algorithms algorithms”

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.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Amazon Rain Forest Classification Using J-ERS-1 SAR Data

The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.

J-ERS-1↗
NASA NTRS1990

Magellan radar to reveal secrets of enshrouded Venus

Imaging Venus with a synthetic aperture radar (SAR) with 70 percent global coverage at 1-km optical line-pair resolution to provide a detailed global characterization of the volcanic land-forms on Venus by an integration of image data with altimetry is discussed. The Magellan radar system uses navigation predictions to preset the radar data collection parameters. The data are collected in such a way as to preserve the Doppler signature of surface elements and later they are transmitted to the earth for processing into high-resolution radar images. To maintain high accuracy, a complex on-board filter algorithm allows the altitude control logic to respond only to a narrow range of expected photon intensity levels and only to signals that occur within a small predicted interval of time. Each mapping pass images a swath of the planet that varies in width from 20 to 25 km. Since the orbital plane of the spacecraft remains fixed in the inertial space, the slow rotation of Venus continually brings new areas into view of the spacecraft.

Saunders, R. Stephen↗
NASA NTRS1997

Active Microwave Remote Sensing Observations of Weddell Sea Ice

Since July 1991, the European Space Agency's ERS-1 and ERS-2 satellites have acquired radar data of the Weddell Sea, Antarctica. The Active Microwave Instrument on board ERS has two modes; SAR and Scatterometer. Two receiving stations enable direct downlink and recording of high bit-rate, high resolution SAR image data of this region. When not in an imaging mode, when direct SAR downlink is not possible, or when a receiving station is inoperable, the latter mode allows normalized radar cross-section data to be acquired. These low bit-rate ERS scatterometer data are tape recorded, downlinked and processed off-line. Recent advances in image generation from Scatterometer backscatter measurements enable complementary medium-scale resolution images to be made during periods when SAR images cannot be acquired. Together, these combined C-band microwave image data have for the first time enabled uninterrupted night and day coverage of the Weddell Sea region at both high (25 m) and medium-scale (-20 km) resolutions. C-band ERS-1 radar data are analyzed in conjunction with field data from two simultaneous field experiments in 1992. Satellite radar signature data are compared with shipborne radar data to extract a regional and seasonal signature database for recognition of ice types in the images. Performance of automated sea-ice tracking algorithms is tested on Antarctic data to evaluate their success. Examples demonstrate that both winter and summer ice can be effectively tracked. The kinematics of the main ice zones within the Weddell Sea are illustrated, together with the complementary time-dependencies in their radar signatures. Time-series of satellite images are used to illustrate the development of the Weddell Sea ice cover from its austral summer minimum (February) to its winter maximum (September). The combination of time-dependent microwave signatures and ice dynamics tracking enable various drift regimes to be defined which relate closely to the circulation of the sea ice in response to current and wind forcing and iceberg barriers. These are closely related to continental-shelf or central basin regimes, in which tidal forcing or barotropic circulation patterns appear to influence the sea-ice motion, respectively. These regimes provide valuable information about the regions of most prolific ice growth and influence of ice conditions upon air-sea-ice exchange processes in the Weddell Sea.

Drinkwater, Mark R.↗
NASA NTRS1989

The Alaska SAR processor - Operations and control

The Alaska SAR (synthetic-aperture radar) Facility (ASF) will be capable of receiving, processing, archiving, and producing a variety of SAR image products from three satellite-borne SARs: E-ERS-1 (ESA), J-ERS-1 (NASDA) and Radarsat (Canada). Crucial to the success of the ASF is the Alaska SAR processor (ASP), which will be capable of processing over 200 100-km x 100-km (Seasat-like) frames per day from the raw SAR data, at a ground resolution of about 30 m x 30 m. The processed imagery is of high geometric and radiometric accuracy, and is geolocated to within 500 m. Special-purpose hardware has been designed to execute a SAR processing algorithm to achieve this performance. This hardware is currently undergoing acceptance testing for delivery to the University of Alaska. Particular attention has been devoted to making the operations semi-automated and to providing a friendly operator interface via a computer workstation. The operations and control of the Alaska SAR processor are described.

Carande, Richard E.↗
NASA NTRS2021

Northern Great Plains Disasters: Using Earth Observations to Enhance Flood Monitoring on Tribal Lands in the Northern Great Plains

In 2019, the Great Plains experienced unprecedented catastrophic flooding. Large flood events are predicted to increase in frequency and severity, posing risks to communities in this region, particularly Tribal Nations. We used data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), imagery from the Sentinel-2 MultiSpectral Instrument (MSI), and digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM) within Google Earth Engine to map historical floods in the region beginning in 2014 with particular attention to the Rosebud Sioux Reservation and the tribal lands of other Great Plains Tribal Water Alliance members. This historical mapping used C-SAR for a combined method approach with a Z-score algorithm in addition to an index for flooded short vegetation. We also developed a flood risk map by weighting different flood predictor variables according to flood risk literature. These variables included soil drainage from the Soil Survey Geographic Database (SSURGO); elevation, slope, and Topographic Wetness Index (TWI) derived from digital elevation models; precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS); land cover from the National Land Cover Database (NLDC); and Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 Operational Land Imager (OLI). From the flood extent and risk maps, we identified widespread flooding in short vegetation (including cropland) and noted flood susceptibility in regions exhibiting high social vulnerability and low community resilience (FEMA indices). We created an ArcGIS Online StoryMap to share project background, results, and data. Additionally, we provided a written tutorial so partners may replicate the flood mapping for future flood events.

Anna Ballasiotes↗
NASA NTRS2000

TE/TM Simulations of Interferometric Measurements

Interferometric synthetic aperture radar (IFSAR) measurements at X-, C-, L-, and P-band are used to derive ground topography at meter level resolution. Interpretation of the derived topography requires attention due to the complex interaction of the radar signal with ground cover. The presence of penetrable surfaces such as vegetation, and tree canopies poses a challenge since the depth of penetration depends on a number of parameters such as the operating radar frequency, polarization, incident angle, as well as terrain structure. The dependence of the reconstructed topography on polarization may lead to the characterization of the ground cover. Simulation of interferometric measurements is useful for interpretation of the derived topography (B. Houshmand, Proceedings of URSI, 314, 1997). In this talk , time domain simulations for interferometric measurement for TE- and TM- polarization are presented. Time domain simulation includes the effects of the surface material property as well geometry comparable the radar signal wavelength (B. Houshmand, Proceedings of the URSI, 25, 1998). The IFSAR simulation is carried out in two steps. First, the forward scattering data is generated based on full wave analysis. Next, the electromagnetic information is inverted to generate surface topography. This inversion is based on the well known IFSAR processing technique which is composed of signal compression, and formation of an interferogram. The full wave forward scattering data is generated by the scattered-field formulation of the FDTD algorithm. The simulation is carried out by exciting the computational domain by a radar signal. The scattered field is then computed and translated to the receiving interferometric antennas using the time-domain Huygen's principle. The inversion process starts by compressing the time-domain data. The range compressed data from both receivers are then coregistered to form an interferogram. The resulting interferogram is then related to the ground topography using the radar imaging geometry. In this talk, the simulation results are compared with the C-band TM IFSAR derived topography, and the TE/TM SAR images at L-Band.

Houshmand, Bijan↗
NASA NTRS1992

Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

Ranson, K. J.↗
NASA NTRS1992

Multi-frequency multi-polarization processing for spaceborne SAR

The Shuttle Imaging Radar-C (SIR-C) is the third in a series of space shuttle based synthetic aperture radars (SAR) sponsored by the National Aeronautics and Space Administration (NASA). The SIR-C ground data processing system is to process the playbacked SAR signal data into a variety of data products for distribution to the science community. An overview of the end-to-end ground data processing system with emphasis on the unique characteristics involved in the system design is presented. Included in the discussion are science requirements, radar system specifications, input data format specifications, system operations design, data products design, processing algorithm design, hardware architecture design, and software design.

Curlander, John C.↗
NASA NTRS1992

Alaska SAR processor implementation of E-ERS-1

The synthetic aperture radar (SAR) data processing algorithm used by the Alaska SAR Facility (ASF) for the European Space Agency's first Remote-Sensing Satellite (E-ERS-1) SAR data are examined. Preprocessing highlights two features: signal measurement, which includes signal-to-noise ratio, replica measurement, and noise measurement; and Doppler measurement, which includes clutter lock and autofocus. The custom pipeline architecture performs the main processing with controls at the input interface, range correlator, corner-turn memory, azimuth correlator, and multi-look memory. The control software employs a flexible control scheme. The Committee on Earth Observation Satellites (CEOS) format encapsulates the ASF products. System performance for SAR image processing of E-ERS-1 data is reviewed.

Cuddy, David↗
NASA NTRS2020

Rocky Mountain Disasters - Using NASA Earth Observations to Monitor Post-Fire Vegetation Recovery in the Colorado Front Range

Forest composition and structure in the Colorado Front Range has been altered by changing wildfire regimes. In particular, increased moderate- and high-severity fire significantly reduces forest cover following fire and often results in reduced seedling regeneration. Reduced tree canopy regrowth has chronic effects on upland ecological function and downstream water quality. This project partnered with the US Forest Service to estimate long-term vegetation recovery following four Colorado Front Range fires between 1996 and 2002—the Bobcat, Buffalo Creek, Hayman, and High Meadows fires—using Landsat 5 Thematic Mapper (TM),Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI). The random forest algorithm was applied to produce maps of percent forest canopy cover for coniferous trees, deciduous trees, and all trees using time-series variables for pre- and post-fire as inputs. Similarly, maps of post-fire seedling regeneration were produced using random forest for coniferous trees,deciduous trees, and all trees using ecological drivers (soil, climate, fire, and topography) and pre-fire remote sensing predictors. Relationships between ecological drivers of post-fire vegetation trajectories were also evaluated. Additional analyses were conducted to (1) assess whether seedlings could be detected by Landsat or synthetic aperture radar (SAR) time-series analysis (2) assess pre-fire and post-fire Landsat variables against pre-fire and post-fire tree cover estimates to evaluate whether magnitude of forest change can be detected. Understanding variables that influence vegetative recovery, vegetation type conversion, and watershed characteristics will aid forest restoration efforts and water quality management.

Eric Jensen↗
NASA NTRS1988

The Alaska SAR processor

The Alaska SAR processor was designed to process over 200 100 km x 100 km (Seasat like) frames per day from the raw SAR data, at a ground resolution of 30 m x 30 m from ERS-1, J-ERS-1, and Radarsat. The near real time processor is a set of custom hardware modules operating in a pipelined architecture, controlled by a general purpose computer. Input to the processor is provided from a high density digital cassette recording of the raw data stream as received by the ground station. A two pass processing is performed. During the first pass clutter-lock and auto-focus measurements are made. The second pass uses the results to accomplish final image formation which is recorded on a high density digital cassette. The processing algorithm uses fast correlation techniques for range and azimuth compression. Radiometric compensation, interpolation and deskewing is also performed by the processor. The standard product of the ASP is a high resolution four-look image, with a low resolution (100 to 200 m) many look image provided simultaneously.

Carande, R. E.↗
NASA NTRS2004

Software for Generating Strip Maps from SAR Data

Jurassicprok is a computer program that generates strip-map digital elevation models and other data products from raw data acquired by an airborne synthetic-aperture radar (SAR) system. This software can process data from a variety of airborne SAR systems but is designed especially for the GeoSAR system, which is a dual-frequency (P- and X-band), single-pass interferometric SAR system for measuring elevation both at the bare ground surface and top of the vegetation canopy. Jurassicprok is a modified version of software developed previously for airborne-interferometric- SAR applications. The modifications were made to accommodate P-band interferometric processing, remove approximations that are not generally valid, and reduce processor-induced mapping errors to the centimeter level. Major additions and other improvements over the prior software include the following: a) A new, highly efficient multi-stage-modified wave-domain processing algorithm for accurately motion compensating ultra-wideband data; b) Adaptive regridding algorithms based on estimated noise and actual measured topography to reduce noise while maintaining spatial resolution; c) Exact expressions for height determination from interferogram data; d) Fully calibrated volumetric correlation data based on rigorous removal of geometric and signal-to-noise decorrelation terms; e) Strip range-Doppler image output in user-specified Doppler coordinates; f) An improved phase-unwrapping and absolute-phase-determination algorithm; g) A more flexible user interface with many additional processing options; h) Increased interferogram filtering options; and i) Ability to use disk space instead of random- access memory for some processing steps.

Hensley, Scott↗
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 NTRS1990

Multiband radar characterization of forest biomes

The utility of airborne and orbital SAR in classification, assessment, and monitoring of forest biomes is investigated through analysis of orbital synthetic aperature radar (SAR) and multifrequency and multipolarized airborne SAR imagery relying on image tone and texture. Preliminary airborne SAR experiments and truck-mounted scatterometer observations demonstrated that the three dimensional structural complexity of a forest, and the various scales of temporal dynamics in the microwave dielectric properties of both trees and the underlying substrate would severely limit empirical or semi-empirical approaches. As a consequence, it became necessary to develop a more profound understanding of the electromagnetic properties of a forest scene and their temporal dynamics through controlled experimentation coupled with theoretical development and verification. The concatenation of various models into a physically-based composite model treating the entire forest scene became the major objective of the study as this is the key to development of a series of robust retrieval algorithms for forest biophysical properties. In order to verify the performance of the component elements of the composite model, a series of controlled laboratory and field experiments were undertaken to: (1) develop techniques to measure the microwave dielectric properties of vegetation; (2) relate the microwave dielectric properties of vegetation to more readily measured characteristics such as density and moisture content; (3) calculate the radar cross-section of leaves, and cylinders; (4) improve backscatter models for rough surfaces; and (5) relate attenuation and phase delays during propagation through canopies to canopy properties. These modeling efforts, as validated by the measurements, were incorporated within a larger model known as the Michigan Microwave Canopy Scattering (MIMICS) Model.

Dobson, M. Craig↗
NASA NTRS1995

Satellite Snow-Cover Mapping: A Brief Review

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow and ice cover using Earth Algorithms to map global snow cover using passive-microwave data have also cover and of snow grain size, globally, limits the utility of a single algorithm to map global snow cover.

Hall, Dorothy K.↗
NASA NTRS2010

Spotlight-Mode Synthetic Aperture Radar Processing for High-Resolution Lunar Mapping

During the 2008-2009 year, the Goldstone Solar System Radar was upgraded to support radar mapping of the lunar poles at 4 m resolution. The finer resolution of the new system and the accompanying migration through resolution cells called for spotlight, rather than delay-Doppler, imaging techniques. A new pre-processing system supports fast-time Doppler removal and motion compensation to a point. Two spotlight imaging techniques which compensate for phase errors due to i) out of focus-plane motion of the radar and ii) local topography, have been implemented and tested. One is based on the polar format algorithm followed by a unique autofocus technique, the other is a full bistatic time-domain backprojection technique. The processing system yields imagery of the specified resolution. Products enabled by this new system include topographic mapping through radar interferometry, and change detection techniques (amplitude and coherent change) for geolocation of the NASA LCROSS mission impact site.

SAR↗
NASA NTRS2013

UAVSAR Program: Initial Results from New Instrument Capabilities

UAVSAR is an imaging radar instrument suite that serves as NASA's airborne facility instrument to acquire scientific data for Principal Investigators as well as a radar test-bed for new radar observation techniques and radar technology demonstration. Since commencing operational science observations in January 2009, the compact, reconfigurable, pod-based radar has been acquiring L-band fully polarimetric SAR (POLSAR) data with repeat-pass interferometric (RPI) observations underneath NASA Dryden's Gulfstream-III jet to provide measurements for science investigations in solid earth and cryospheric studies, vegetation mapping and land use classification, archaeological research, soil moisture mapping, geology and cold land processes. In the past year, we have made significant upgrades to add new instrument capabilities and new platform options to accommodate the increasing demand for UAVSAR to support scientific campaigns to measure subsurface soil moisture, acquire data in the polar regions, and for algorithm development, verification, and cross-calibration with other airborne/spaceborne instruments.

P-band polarimetry↗
NASA NTRS1995

Evaluating the Type and State of Alaska Taiga Forests with Imaging Radar for Use in Ecosystem Models

Changes in the seasonal CO2 flux of the boreal forests may result from increased atmospheric CO2 concentrations and associated global warming patterns. To monitor this potential change, a combination of information derived from remote sensing data, including forest type and growing season length, and ecophysiological models which predict the CO2 flux and its seasonal amplitude based on meteorological data, are required. In this paper we address the use of synthetic aperture radar (SAR) to map fores type and monitor canopy and soil freeze/thaw, which define the growing season for conifers, and leaf on/off, which defines the growing season for deciduous species. Aircraft SAR (AIRSAR) data collected in March 1988 during a freeze/thaw event are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off transitions and soil freeze/thaw. Finally, a CO2 flux algorithm is presented which utilizes SAR data and an ecophysiological model to estimate CO2 flux. CO2 flux maps are generated, from which areal estimates of CO2 flux are derived.

Alaska↗