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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.

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At least 253 records · Page 14

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NASA NTRS1983

Improved spatial mapping of rainfall events with spaceborne SAR imagery

The Seasat satellite acquired the first spaceborne synthetic-aperture radar (SAR) images of the earth's surface, in 1978, at a frequency of 1.275 GHz (L-band) in a like-polarization mode at incidence angles of 23 + or - 3 deg. Although this may not be the optimum system configuration for radar remote sensing of soil moisture, interpretation of two Seasat images of Iowa demonstrates the sensitivity of microwave backscatter to soil moisture content. In both scenes, increased image brightness, which represents more radar backscatter, can be related to previous rainfall activity in the two areas. Comparison of these images with ground-based rainfall observations illustrates the increased spatial coverage of the rainfall event that can be obtained from the satellite SAR data. These data can then be color-enhanced by a digital computer to produce aesthetically pleasing output products for the user community.

Ulaby, F. T.↗

NASA NTRS1982

A statistical model for radar images of agricultural scenes

The presently derived and validated statistical model for radar images containing many different homogeneous fields predicts the probability density functions of radar images of entire agricultural scenes, thereby allowing histograms of large scenes composed of a variety of crops to be described. Seasat-A SAR images of agricultural scenes are accurately predicted by the model on the basis of three assumptions: each field has the same SNR, all target classes cover approximately the same area, and the true reflectivity characterizing each individual target class is a uniformly distributed random variable. The model is expected to be useful in the design of data processing algorithms and for scene analysis using radar images.

Frost, V. S.↗

NASA NTRS1981

Seasat SAR cross-section modulation by surface winds - GOASEX observations

Seasat radar observations of the Gulf of Alaska by the Synthetic Aperture Radar (SAR) and the Wind Speed Scatterometer (SASS) indicate that L-band backscatter is modulated by wind speed and possibly by wind direction. It is noted that the L-band backscatter is approximately proportional to the square root of surface winds and that upwind/crosswind differences in backscatter can be as large as 10% in the range of these wind speeds. It is suggested that Seasat SAR images, in conjunction with Seasat Scatterometer data may provide fine-scale mapping of ocean winds and directions. The need for further Seasat SAR-SASS comparisons in order to extend the range of wind speeds is stressed.

Thompson, T. W.↗

NASA NTRS1987

Observing rotation and deformation of sea ice with synthetic aperture radar

The ESA's ERS-1 satellite will carry SARs over the polar regions; an important component in the use of these data is an automated scheme for the extraction of sea ice velocity fields from a sequence of SAR images of the same geographical region. The image pyramid area-correlation hierarchical method is noted to be vulnerable to uncertainties for sea ice rotations greater than 10-15 deg between SAR observations. Rotation-invariant methods can successfully track isolated floes in the marginal ice zone. Hu's (1962) invariant moments are also worth considering as a possible basis for rotation-invariant tracking methods. Feature tracking is inherently robust for tracking rotating sea ice, but is limited when features are floe-lead boundaries. A variety of techniques appears neccessary.

Vesecky, J. F.↗

NASA NTRS1992

Image processing and products for the Magellan mission to Venus

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.

Clark, Jerry↗

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 NTRS1991

Observation of wave refraction at an ice edge by synthetic aperture radar

In this note the refraction of waves at the ice edge is studied by using aircraft synthesis aperture radar (SAR). Penetration of a dominant swell from open ocean into the ice cover was observed by SAR during the Labrador Ice Margin Experiment (LIMEX), conducted on the marginal ice zone (MIZ) off the east coast of Newfoundland, Canada, in March 1987. At an ice edge with a large curvature, the dominant swell component disappeared locally in the SAR imagery. Six subscenes of waves in the MIZ from the SAR image have been processed, revealing total reflection, refraction, and energy reduction of the ocean waves by the ice cover. The observed variations of wave spectra from SAR near the ice edge are consistent with the model prediction of wave refraction at the ice edge due to the change of wave dispersion relation in ice developed by Liu and Mollo-Christensen (1988).

Liu, Antony K.↗

NASA NTRS1993

Topographic mapping using a monopulse SAR system

Terrain height variations in mountainous areas cause two problems in the radiometric correction of SAR images: the first being that the wrong elevation angle may be used in correcting for the radiometric variation of the antenna pattern; the second that the local incidence angle used in correcting the projection of the pixel area from slant range to ground range coordinates may vary from that given by the flat earth assumption. We propose a novel design of a SAR system which exploits the monopulse principle to determine the elevation angle and thus the height at the different parts of the image. The key element of such a phase monopulse system is an antenna, which can be divided into a lower and upper half in elevation using a monopulse comparator. In addition to the usual sum pattern, the elevation difference pattern can be generated by a -pi phase shift on one half of the antenna. From the ratios of images radiometrically modulated by the difference and sum antenna pattern in cross-track direction, we can derive the appropriate elevation angle at any point in the image. Together with the slant range we can calculate the height of the platform above this point using information on the antenna pointing and the platform attitude. This operation, repeated at many locations throughout the image, allows us to build up a topographic map of the height of the aircraft above each location. Inversion of this map, using the precisely determined aircraft altitude and the accurate flight path, leads to the actual topography of the imaged surface. The precise elevation of one point in the image could also be used to convert the height map to a topographic map. In this paper, we present design considerations for a corresponding airborne SAR system in X-Band and give estimates of the error due to system noise and azimuth ambiguities as well as the expected performance and precision in topographic mapping.

Zink, M.↗

NASA NTRS1981

A model for simulation and processing of radar images

A model for recording, processing, presentation, and analysis of radar images in digital form is presented. The observed image is represented as having two random components, one which models the variation due to the coherent addition of electromagnetic energy scattered from different objects in the illuminated areas. This component is referred to as fading. The other component is a representation of the terrain variation which can be described as the actual signal which the radar is attempting to measure. The combination of these two components provides a description of radar images as being the output of a linear space-variant filter operating on the product of the fading and terrain random processes. In addition, the model is applied to a digital image processing problem using the design and implementation of enhancement scene. Finally, parallel approaches are being employed as possible means of solving other processing problems such as SAR image map-matching, data compression, and pattern recognition.

Stiles, J. A.↗

NASA NTRS1983

The potential of SAR directional spectra in operational wave forecasting

Digitally processed Seasat SAR ocean wave imagery, when digitally transformed, smoothed, and corrected for known instrument biases, can accurately track multiple (at least three) wave systems in the open ocean, across major currents, and into shallow water. Furthermore, the relative backscatterer of the digitally processed SAR image, when sampled within a single pass and along a constant range, responds to the local wind through a simple power law relationship. The results indicate that SAR spectra, if obtained from a low altitude satellite, could be an important supplement to global winds and non-directional wave heights obtained through other methods.

Beal, R. C.↗

NASA NTRS2019

Comprehensive Severe Weather Impact Assessment and Monitoring using Synthetic Aperture Radar and Auxiliary Data

Remote sensing datasets, particularly acquired by Synthetic Aperture Radar (SAR) sensors, have become increasingly important in severe weather disaster impact studies given their ability to observe the Earth largely irrespective of weather and sunlight conditions. The reliability of existing SAR change detection products applied on a pair of SAR images is constrained by the limitation of current methods to differentiate and classify disaster specific changes from anthropogenic surface alterations. Moreover, the inherent properties of the sensors, variations in SAR backscatter due to changes in surface conditions, and other factors exacerbate these limitations. We proposed a novel procedure expanding on earlier SAR-based change detection methods to exclude anthropogenic alterations and other sources of ambiguity that might lead to inaccurate mapping of the impacts of severe weather disasters. We applied the proposed procedure that is based on long term interferometric and amplitude-based change detection analyses of Sentinel- 1 SAR imagery to two study sites recently impacted by severe weather disasters (Flooding post severe weather events in urban centers; Hailstorm damage on crops). For the first case study, Sentinel-1 SLC scenes from two flood events in the Houston area (April 2016 flooding event and Hurricane Harvey of August-September 2017) were used to construct a flood map depicting areas repeatedly affected by the flood. Pixels with consistent coherence values in the pre-disaster coherence stack were retained for comparison with the pre- and post-disaster coherence stack and pixels with significant decline (greater than 60%) in coherence values were retained in the final flood map. The findings of the applied technique were calibrated and validated through datasets from NOAA/NWS Service storm reports, aerial imaging (NOAA and Civil Air Patrol), Federal Emergency Management Agency (FEMA) reporting, and targeted collections of NASA’s L-band UAVSAR data. Findings and products derived from the adopted methodology can be useful in disaster response and mitigation activities.

Gebremichael, Esayas↗

NASA NTRS1994

(abstract) Monitoring the Freeze/Thaw Transitions in Taiga Forests Using ERS-1 SAR

Automated recording stations have been installed at the Bonanza Creek Experimental Forest, a Long Term Ecological Research (LTER) site located near Fairbanks, Alaska, in a forest stand of the Tanana River floodplain underlain by discontinuous permafrost. These stations provide a continuous record of dielectric constant and temperature of tree trunks, and soil moisture and temperature profiles down to the root zone. Along with the weather stations deployed at the same location, these measurements provide a continuous record of the environmental and phenologic conditions of the forest during a complete seasonal cycle. At the same time, ERS-1 SAR imaged the study site repeatedly from space to provide radar backscatter measurements of the forest approximately three times a month. Here, we examine the temporal dynamic of ERS-1 SAR measurements in relation with the changing environmental and phenologic state of the forest canopy and of the forest ground layers during the winter/spring and fall/winter transitions of 1992 and 1993. During these transitions, we examine whether changes in radar backscatter observed by ERS-1 may be related to freezing or thawing of the soil and vegetation in order to determine the start and end of the growing season for the forest. The results of this analysis are used in turn to determine whether similar changes are observed over larger regions. Mosaics of SAR data generated along three different North-South Alaskan ERS-1 transects that intercept with our study site are used in combination with hourly air temperature and daily precipitation rates gathered at airport weather stations by the National Weather Service. Results obtained using ERS-1 data collected from January 1992 to mid-1993 will be discussed.

permafrost temporal dynamics Alaska ecology radar ↗

NASA NTRS1993

Multifrequency observations

Analyses of synthetic aperture radar (SAR) image data were performed at DLR to classify various kinds of vegetation and different terrain types. The data were collected both with the DLR experimental synthetic aperture radar (E-SAR) in X-band, C-band, and L-band and with the NASA/JPL DC-8 SAR in C-band, L-band, and P-band. E-SAR is a single frequency and single polarization system (both parameters can be selected) but several flights were used to collect multifrequency/multipolarization data which were geometrically matched after processing. Classification of different crop types was based on comparison of the backscatter coefficients of calibrated SAR data in different frequency bands and polarizations. The DC-8 STAR collects polarimetric data in different bands simultaneously. Data acquired with the NASA/JPL DC-8 STAR are qualified for scientific investigations by reducing the cross-talk and channel imbalance to a tolerable extent. The data are absolutely calibrated by using reference targets with known backscattering cross-sections. The signatures and polarimetric features of terrain types, such as grassland, concrete, sea, forest (coniferous; deciduous) and urban areas, are extracted and discussed with respect to frequency and incidence angle dependence. A multifrequency polarimetric feature vector was applied for classification. The results of this new approach for separating and classifying different object classes are presented.

Glitz, R.↗

NASA NTRS1982

Spaceborne scanner imaging system errors

The individual sensor system design elements which are the priori components in the registration and rectification process, and the potential impact of error budgets on multitemporal registration and side-lap registration are analyzed. The properties of scanner, MLA, and SAR imaging systems are reviewed. Each sensor displays internal distortion properties which to varying degrees make it difficult to generate on orthophoto projection of the data acceptable for multiple pass registration or meeting national map accuracy standards and is also affected to varying degrees by relief displacements in moderate to hilly terrain. Nonsensor related distortions, associated with the accuracy of ephemeris determination and platform stability, have a major impact on local geometric distortions. Platform stability improvements expected from the new multi mission spacecraft series and improved ephemeris and ground control point determination from the NAVSTAR/global positioning satellite systems are reviewed.

Prakash, A.↗

NASA NTRS1978

SAR/LANDSAT image registration study

The author has identified the following significant results. Temporal registration of synthetic aperture radar data with LANDSAT-MSS data is both feasible (from a technical standpoint) and useful (from an information-content viewpoint). The greatest difficulty in registering aircraft SAR data to corrected LANDSAT-MSS data is control-point location. The differences in SAR and MSS data impact the selection of features that will serve as a good control points. The SAR and MSS data are unsuitable for automatic computer correlation of digital control-point data. The gray-level data can not be compared by the computer because of the different response characteristics of the MSS and SAR images.

Murphrey, S. W.↗

NASA NTRS1995

Regional mapping of forest canopy water content and biomass using AIRSAR images over BOREAS study area

In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne Synthetic Aperture Radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity to structural and moisture characteristics of vegetation canopies. Even though the sensitivity of SAR data to total aboveground biomass has been successfully demonstrated in many controlled experiments over boreal forests and forest plantations, so far, no biomass estimation algorithm has been developed. This is mainly due to the fact that the SAR data, even at lowest frequency (P-band) saturates at biomass levels of about 200 tons/ha, and the structure and moisture information in the SAR signal forces the estimation algorithm to be forest type dependent. In this paper, we discuss the development of a hybrid forest biomass algorithm which uses a SAR derived land cover map in conjunction with a forest backscatter model and an inversion algorithm to estimate forest canopy water content. It is shown that unlike the direct biomass estimation from SAR data, the estimation of water content does not depend on the seasonal and/or environmental conditions. The total aboveground biomass can then be derived from canopy water content for each type of forest by incorporating other ecological information. Preliminary results from this technique over several boreal forest stands indicate that (1) the forest biomass can be estimated with reasonable accuracy, and (2) the saturation level of the SAR signal can be enhanced by separating the crown and trunk biomass in the inversion algorithm. We have used the JPL AIRSAR data over BOREAS southern study area to test the algorithm and to generate regional scale water content and biomass maps. The results are compared with ground data and the sources of errors are discussed. Several SAR images in synoptic modes are used to generate the parameter maps. The maps are then combined to generate mosaic maps over the BOREAS modeling grid.

Saatchi, Sasan↗

NASA NTRS2001

Identification of Surface and Near Surface Defects and Damage Evaluation by Laser Speckle Techniques

As a part of the grant activity, a laboratory was established within the Department of Electrical Engineering for the study for measurements of surface defects and damage evaluation. This facility has been utilized for implementing several algorithms for accurate measurements of defects. Experiments were conducted using simulated images and multiple images were fused to achieve accurate measurements. During the nine months of the grants when the principal investigator was transferred in my name, experiments were conducted using simulated synthetic aperture radar (SAR) images. This proved useful when several algorithms were used on images of smooth objects with minor deformalities. Given the time constraint, the derived algorithms could not be applied to actual images of smooth objects with minor abnormalities.

Gowda, Chandrakanth H.↗

NASA NTRSDate not supplied

Mapping Inundation from Hurricane Florence (2018) with L-Band Synthetic Aperture Radar, Commercial Imagery, and Ancillary Data via Random Forest Classification

Mapping the extent of floodwaters following extreme rainfall aids in the distribution of resources, recovery efforts, and damage assessment practices. Development of a land cover classification system focused on mapping inundation after major hurricane events using synthetic aperture radar (SAR) data could allow for the production of near-real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of a developing situation. In response to Hurricane Florence of 2018, NASA JPL collected numerous swaths of quad-pol L-band SAR data with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) instrument observing the record-setting river stages across North and South Carolina. The resulting fully-polarized SAR images allow for mapping of inundation extent at a high spatial resolution with a unique advantage over optical imaging stemming from the sensor’s ability to penetrate cloud cover and dense vegetation. This study seeks to determine how accurately maps of inundation can be generated from L-band SAR imagery through Random Forest classification. Once the extent of water and inundated vegetation is classified, cleanup operations are performed using fuzzy logic to reduce false detections. Estimates of water extent are then combined with datasets describing the distribution of population, buildings, and roads throughout the domain to evaluate societal impacts. Results from the Hurricane Florence case study will be discussed along with the limitations of available validation data for assessment of the classifier’s accuracy.

Alexander Melancon↗