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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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NASA NTRS2015

NASA's Meteoroid Environments Office's Response to Three Significant Bolide Events Over North America

Being the only U.S. Government entity charged with monitoring the meteor environment, the Meteoroid Environment Office has deployed a network of all sky and wide field meteor cameras, along with the appropriate software tools to quickly analyze data from these systems. However, the coverage of this network is still quite limited, forcing the incorporation of data from other cameras posted to the internet in analyzing many of the fireballs reported by the public and media. A procedure has been developed that determines the analysis process for a given fireball event based on the types and amount of data available. The differences between these analysis process will be explained and outlined by looking at three bolide events, all of which were large enough to produce meteorites. The first example is an ideal event - a bright meteor that occurred over NASA's All Sky Camera Network on August 2, 2014. With clear video of the event from various angles, a high-accuracy trajectory, beginning and end heights, orbit and approximate brightness/size of the event are able to be found very quickly using custom software. The bolide had the potential to have dropped meteorites, so dark flight analysis and modeling was performed, allowing potential fall locations to be mapped as a function of meteorite mass. The second case study was a bright bolide that occurred November 3, 2014 over West Virginia. This was just north of the NASA southeastern all-sky network, and just south of the Ohio-Pennsylvania network. This case study showcases the MEO's ability to use social media and various internet sources to locate videos of the event from obscure sources (including the Washington Monument) for anything that will permit a determination of a basic trajectory and fireball light curve The third case study will highlight the ability to use doppler weather radar in helping locate meteorites, which enable a definitive classification of the impactor. The input data and analysis steps differ for each case study, but the goals remain the same - a trajectory, orbit, and mass estimate for the bolide within hours of the event, and, for events with a high probability of producing meteorites, a location of the strewn field within a day.

Blaauw, Rhiannon C.↗
NASA NTRS2025

Describing Seasonal Mixtures of Cloud Regimes Via “Regimes of Regimes”

We propose a new type of cloud classification, relevant to monthly or longer time scales, but which inherently still encompasses cloud subgrid variability information at ~100 km scales. Our proposed classification partitions frequencies of occurrence over these scales of previously defined cloud regimes (CRs). We call the resulting distinct cloud entities regimes of regimes (RORs). While the CRs have been previously shown to successfully classify daily mesoscale subgrid variability via distributions of cloud fraction within distinct combinations of cloud top pressure and cloud optical thickness, the RORs essentially represent the prevalent seasonal mixtures of these CRs. RORs thus embody the seasonal cloudiness of a mesoscale region. We show that each ROR can still be associated with more traditional cloud classifications via composites of coincident active (lidar and cloud radar) cloud views. In a first application that gauges the potential utility of RORs, we pair them with CERES EBAF radiative fluxes to gain insight into recent trends of the cloud radiative effect. The ROR corresponding to an environment of shallow convection stands out in this analysis largely because of its declining population. Our study demonstrates the potential of RORs to categorize globally mesoscale cloudiness at monthly/seasonal scales and to serve as proxies of different atmospheric states at these scales.

Nayeong Cho↗
NASA NTRS1993

On evaluating the accuracy of SAR sea-ice classification using multifrequency polarimetric AIRSAR data

We investigate how multifrequency and polarimetric synthetic aperture radar (SAR) imagery enhances present capability to discriminate different ice conditions in single-frequency, single-polarization satellite SAR data. Frequencies considered are C- (lambda = 5.6cm), L- (lambda = 24cm) and P- (lambda = 68cm) band. Radar backscatter characteristics of six radiometrically and polarimetrically distinct ice types are selected from a cluster analysis of the multifrequency polarimetric SAR data and used to classify SAR images. Validation of these ice conditions is based on information provided by aerial photos, weather and ice surface measurements acquired at an ice camp, together with airborne passive microwave imagery, and visual analysis of the SAR data. The six identified sea-ice types are: (1) multiyear sea-ice; (2) compressed first year ice; (3) first year rubble and ridges; (4) first year rough ice; (5) first year smooth ice; and (6) thin ice. Open water is absent in all analyzed data. Classification of the SAR imagery into those six ice types is performed using a Bayesian Maximum A Posteriori classifier. Two complete scenes acquired at different dates in different locations are classified. The scenes were chosen such that they are representative of typical ice conditions in the Beaufort Sea in March 1988 and because ancillary information is available for validating the segmentation of various ice surface conditions.

Drinkwater, Mark R.↗
NASA NTRS1982

Geologic interpretation of texture in Seasat and SIR-A radar images

Geological information in radar images of heavily vegetated areas is contained mainly in the depiction of topography as image texture. This paper describes three techniques for the analysis of texture in radar images: the split-spectrum technique, Fourier transforms of subareas, and spatial frequency bandpass classification. These techniques were applied to a heavily vegetated area of Belize in Central America in order to evaluate their utility for geological mapping; Seasat and Shuttle Imaging Radar (SIR-A) images were considered.

Farr, T. G.↗
NASA NTRS1977

Fisheries imaging radar surveillance test /FIRST/ - Bering Sea test

A joint NOAA, U.S. Coast Guard and NASA program is being conducted to determine if a synthetic aperture radar (SAR) system, such as planned for NASA's SEASAT, can be useful in monitoring fishing vessels within the newly established 200-mile fishing limit. As part of this program, data gathering field operations were conducted over concentrations of foreign fishing vessels in the Bering Sea off Alaska in April 1976. The Jet Propulsion Laboratory developed synthetic aperture L-band radar which was flown aboard the NASA Convair 990 aircraft, with a Coast Guard cutter and C-130 aircraft simultaneously gathering data to provide both radar imagery and sea truth information on the vessels being imaged. Results indicate that synthetic aperture radar systems have potential for all weather detection, enumeration and classification of fishing vessels.

Woods, E. G.↗
NASA NTRS1989

Geology of the Venus equatorial region from Pioneer Venus radar imaging

The surface characteristics and morphology of the equatorial region of Venus were first described by Masursky et al. who showed this part of the planet to be characterized by two topographic provinces, rolling plains and highlands, and more recently by Schaber who described and interpreted tectonic zones in the highlands. Using Pioneer Venus (PV) radar image data (15 deg S to 45 deg N), Senske and Head examined the distribution, characteristics, and deposits of individual volcanic features in the equatorial region, and in addition classified major equatorial physiographic and tectonic units on the basis of morphology, topographic signature, and radar properties derived from the PV data. Included in this classification are: plains (undivided), inter-highland tectonic zones, tectonically segmented linear highlands, upland rises, tectonic junctions, dark halo plains, and upland plateaus. In addition to the physiographic units, features interpreted as coronae and volcanic mountains have also been mapped. The latter four of the physiographic units along with features interpreted to be coronae.

Senske, D. A.↗
NASA NTRS1992

Signal processing for airborne doppler radar detection of hazardous wind shear as applied to NASA 1991 radar flight experiment data

Radar data collected during the 1991 NASA flight tests have been selectively analyzed to support research directed at developing both improved as well as new algorithms for detecting hazardous low-altitude windshear. Analysis of aircraft attitude data from several flights indicated that platform stability bandwidths were small compared to the data rate bandwidths which should support an assumption that radar returns can be treated as short time stationary. Various approaches at detection of weather returns in the presence of ground clutter are being investigated. Non-coventional clutter rejection through spectrum mode tracking and classification algorithms is a subject of continuing research. Based upon autoregressive modeling of the radar return time sequence, this approach may offer an alternative to overcome errors in conventional pulse-pair estimates. Adaptive filtering is being evaluated as a means of rejecting clutter with emphasis on low signal-to-clutter ratio situations, particularly in the presence of discrete clutter interference. An analysis of out-of-range clutter returns is included to illustrate effects of ground clutter interference due to range aliasing for aircraft on final approach. Data are presented to indicate how aircraft groundspeed might be corrected from the radar data as well as point to an observed problem of groundspeed estimate bias variation with radar antenna scan angle. A description of how recorded clutter return data are mixed with simulated weather returns is included. This enables the researcher to run controlled experiments to test signal processing algorithms. In the summary research efforts involving improved modelling of radar ground clutter returns and a Bayesian approach at hazard factor estimation are mentioned.

Baxa, Ernest G., Jr.↗
NASA NTRS1995

Program Classifies Multiple-Frequency Polarimetric SAR Data

POLMAP computer program classifies multifrequency, polarimetric synthetic-aperture-radar (SAR) data into homogeneous classes of radar back-scatter. Software implements maximum-a-posteriori classification scheme. Performs by use of simulated-annealing procedure, takes much longer to compute than ICM solution, but it maximizes posteriori distribution of classes for whole scene. Input statistics of image classes must be created by some independent means, and supplied as input to POLMAP. Used as input to image processing application program. Written in FORTRAN 77.

Rignot, Eric↗
NASA NTRS2018

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗
NASA NTRS1996

(abstract) Topographic Signatures in Geology

Topographic information is required for many Earth Science investigations. For example, topography is an important element in regional and global geomorphic studies because it reflects the interplay between the climate-driven processes of erosion and the tectonic processes of uplift. A number of techniques have been developed to analyze digital topographic data, including Fourier texture analysis. A Fourier transform of the topography of an area allows the spatial frequency content of the topography to be analyzed. Band-pass filtering of the transform produces images representing the amplitude of different spatial wavelengths. These are then used in a multi-band classification to map units based on their spatial frequency content. The results using a radar image instead of digital topography showed good correspondence to a geologic map, however brightness variations in the image unrelated to topography caused errors. An additional benefit to the use of Fourier band-pass images for the classification is that the textural signatures of the units are quantative measures of the spatial characteristics of the units that may be used to map similar units in similar environments.

topography geology texture Fourier analysis↗
NASA NTRS1992

A system for verifying models and classification maps by extraction of information from a variety of data sources

Recent updates to a geographical information system (GIS) called VICAR (Video Image Communication and Retrieval)/IBIS are described. The system is designed to handle data from many different formats (vector, raster, tabular) and many different sources (models, radar images, ground truth surveys, optical images). All the data are referenced to a single georeference plane, and average or typical values for parameters defined within a polygonal region are stored in a tabular file, called an info file. The info file format allows tracking of data in time, maintenance of links between component data sets and the georeference image, conversion of pixel values to `actual' values (e.g., radar cross-section, luminance, temperature), graph plotting, data manipulation, generation of training vectors for classification algorithms, and comparison between actual measurements and model predictions (with ground truth data as input).

Norikane, L.↗
NASA NTRS1981

Texture measurements from Seasat - SAR images for urban land use interpretation

Different grey tones in Seasat Synthetic Aperture Radar (SAR) images for the same type of urban land cover considerably impair the possibilities of establishing automatic classification procedures for these types of data. Since the orientation of the main features like street patterns and buildings with respect to the azimuth angle of the radar antenna is the crucial factor for the observed differences in grey tone, prior information on these elements and special processing of the data would be required to eliminate this effect. Another approach suggested in this paper is to make use of the textural information in the image rather than of its grey tone. For different study sites within the Los Angeles urbanized area texture measures could be derived which result in characteristic values for specific types of land cover and are largely independent of the azimuth angle effect. At the same time the results for the study area indicate an improvement of the overall separability for the different land cover types included in the analysis.

Fasler, F.↗
NASA NTRS1985

Microwave remote sensing from space

Spaceborne microwave remote sensors provide perspectives of the earth surface and atmosphere which are of unique value in scientific studies of geomorphology, oceanic waves and topography, atmospheric water vapor and temperatures, vegetation classification and stress, ice types and dynamics, and hydrological characteristics. Microwave radars and radiometers offer enhanced sensitivities to the geometrical characteristics of the earth's surface and its cover, to water in all its forms - soil and vegetation moisture, ice, wetlands, oceans, and atmospheric water vapor, and can provide high-resolution imagery of the earth's surface independent of cloud cover or sun angle. A brief review of the historical development and principles of active and passive microwave remote sensing is presented, with emphasis on the unique characteristics of the information obtainable in the microwave spectrum and the value of this information to global geoscientific studies. Various spaceborne microwave remote sensors are described, with applications to geology, planetology, oceanography, glaciology, land biology, meteorology, and hydrology. A discussion of future microwave remote sensor technological developments and challenges is presented, along with a summary of future missions being planned by several countries.

Carver, K. R.↗
NASA NTRS1975

Radar characteristics of cloud fields

Relations of several statistical parameters of the radio echo field to the types of cloud systems and weather phenomena in the cloud field are studied. Combinations of the statistical characteristics of radio echo are found which in certain cases permit the unique classification of cloud field according to the types of phenomena. The space-time variability of the radar characteristic was examined in connection with the transformation of the cloud field, and the question of the variation of the statistical characteristics of the echoes from cloud field was examined in connection with changes in the dimensions of the quantization cell.

Divinskaya, B. S.↗
NASA NTRS1995

Bayes classification of interferometric TOPSAR data

We report the Bayes classification of terrain types at different sites using airborne interferometric synthetic aperture radar (INSAR) data. A Gaussian maximum likelihood classifier was applied on multidimensional observations derived from the SAR intensity, the terrain elevation model, and the magnitude of the interferometric correlation. Training sets for forested, urban, agricultural, or bare areas were obtained either by selecting samples with known ground truth, or by k-means clustering of random sets of samples uniformly distributed across all sites, and subsequent assignments of these clusters using ground truth. The accuracy of the classifier was used to optimize the discriminating efficiency of the set of features that was chosen. The most important features include the SAR intensity, a canopy penetration depth model, and the terrain slope. We demonstrate the classifier's performance across sites using a unique set of training classes for the four main terrain categories. The scenes examined include San Francisco (CA) (predominantly urban and water), Mount Adams (WA) (forested with clear cuts), Pasadena (CA) (urban with mountains), and Antioch Hills (CA) (water, swamps, fields). Issues related to the effects of image calibration and the robustness of the classification to calibration errors are explored. The relative performance of single polarization Interferometric data classification is contrasted against classification schemes based on polarimetric SAR data.

Michel, T. R.↗
NASA NTRS2021

Testing the Drop-Size Distribution-Based Separation of Stratiform and Convective Rain Using Radar and Disdrometer Data from a Mid-Latitude Coastal Region

Stratiform and convective rain are associated with different microphysical processes and generally produce drop-size distributions (DSDs) with different characteristics. Previous studies using data from (a) a tropical coastal location, (b) a mid-latitude continental location with semi-arid climate, and (c) a sub-tropical continental location, found that the two rain types could be separated in the NW–Dm space, where Dm is the mass-weighted mean diameter and NW is the normalized intercept parameter. In this paper, we investigate the same separation technique using data and observations from a mid-latitude coastal region. Three-minute DSDs from disdrometer measurements are used for the NW- versus Dm-based classification and are compared with simultaneous observations from an S-band polarimetric radar 38 km away from the disdrometer site. Specifically, RHI (range-height indicator) scans over the disdrometer were used for confirmation. Results show that there was no need to modify the separation criteria from previous studies. Three-minute DSDs from the same location were used as input to scattering calculations to derive retrieval equations for NW and Dm for the S-band radar using an improved technique and applied to the RHI scans to identify convective and stratiform rain regions. Two events are shown as illustrative examples.

Merhala Thurai↗
NASA NTRS2004

An Orbital "Virtual Radar" from TRMM Passive Microwave and Lightning Observations

The retrieval of vertical structure from joint passive microwave and lightning observations is demonstrated. Three years of data from the TRMM (Tropical Rainfall Measuring Mission) are used as a training dataset for regression and classification neural networks; the TMI (TRMM Microwave Imager) and LIS (Lightning Imaging Sensor) provide the inputs, the PR (Precipitation Radar) provides the training targets. Both vertical reflectivity profile categorization (into 9 convective, 7 stratiform, 2 mixed and 6 anvil types) and geophysical parameters (surface rainfall, vertically integrated liquid (VIL), ice water content (IWC) and echo tops) are retrieved. Retrievals are successful over both land and ocean surfaces. The benefit of using lightning observations as inputs to these retrievals is quantitatively demonstrated; lightning essentially provides an additional convective/stratiform discriminator, and is most important for isolation of midlevel (tops in the mixed phase region) convective profile types (this is because high frequency passive microwave observations already provide good convective/stratiform discrimination for deep convective profiles). This is highly relevant as midlevel convective profiles account for an extremely large fraction of tropical rainfall, and yet are most difficult to discriminate from comparable-depth stratiform profile types using passive microwave observations alone.

Boccippio, Dennis J.↗
NASA NTRS1981

Spaceborne radar observation of the earth surface

Seasat SAR images are being analyzed to determine the potential of spaceborne radars for earth resources and ocean surface observation. Examples are presented for a variety of applications in structural mapping, lithological classification, soil moisture detection, polar ice motion monitoring and ocean features observation. These examples are briefly discussed with emphasis on the future research needed to further the capability of radar sensors, by themselves or in combination with other sensors. A brief discussion is then given on the spaceborne sensors which are required and planned to meet these needs.

Elachi, C.↗