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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 3

Topics discussed include: Characterization of Non-Organized Soils at Gusev Crater with the Spirit Rover Data; Searching for Life with Rovers: Exploration Methods & Science Results from the 2004 Field Campaign of the "Life in the Atacama" Project and Applications to Future Mars Missions; Analysis of the Lunar Surface with Global Mineral and Mg-Number Maps ALH77005: The Magmatic History from Rehomogenized Melt Inclusions; New 70-cm Radar Mapping of the Moon; Cryptomare Deposits Revealed by 70-cm Radar; Construction of a PZT Sensor Network for Low and Hypervelocity Impact Detection; Palmer Quest: A Feasible Nuclear Fission "Vision Mission" to the Mars Polar Caps; Physical Properties of Volcanic Deposits on Venus from Radar Polarimetry; Science Alert Demonstration with a Rover Traverse Science Data Analysis System; Earth and Mars, Similar Features and Parallel Lives? Didactic Activities; Expected Constraints on Rhea s Interior from Cassini; Microbially Induced Precipitates: Examples from CO3, Si-, Mn- and Fe-rich Deposits; Li, B - Behavior in Lunar Basalts During Shock and Thermal Metamorphism: Implications for H2O in Martian Magmas; Evaluation of CO Self-Shielding as a Possible Mechanism for Anomalous Oxygen Isotopic Composition of Early Solar System Materials; Effect of Ground Ice on Apparent Thermal Inertia on Mars; Utah Marbles and Mars Blueberries: Comparative Terrestrial Analogs for Hematite Concretions on Mars; Newly Discovered Meteor Crater Metallic Impact Spherules: Report and Implications; and Evidence of Very Young Glacial Processes in Central Candor Chasma, Mars.

Source record↗
NASA NTRS2010

DSD Characteristics of a Mid-Winter Tornadic Storm Using C-Band Polarimetric Radar and Two 2D-Video Disdrometers

Drop size distributions in an evolving tornadic storm are examined using C-band polarimetric radar observations and two 2D-video disdrometers. The E-F2 storm occurred in mid-winter (21 January 2010) in northern Alabama, USA, and caused widespread damage. The evolution of the storm occurred within the C-band radar coverage and moreover, several minutes prior to touch down, the storm passed over a site where several disdrometers including two 2D video disdrometers (2DVD) had been installed. One of the 2DVDs is a low profile unit and the other is a new next generation compact unit currently undergoing performance evaluation. Analyses of the radar data indicate that the main region of precipitation should be treated as a "big-drop" regime case. Even the measured differential reflectivity values (i.e. without attenuation correction) were as high as 6-7 dB within regions of high reflectivity. Standard attenuation-correction methods using differential propagation phase have been "fine tuned" to be applicable to the "big drop" regime. The corrected reflectivity and differential reflectivity data are combined with the co-polar correlation coefficient and specific differential phase to determine the mass-weighted mean diameter, Dm, and the width of the mass spectrum, (sigma)M, as well as the intercept parameter , Nw. Significant areas of high Dm (3-4 mm) were retrieved within the main precipitation areas of the tornadic storm. The "big drop" regime assumption is substantiated by the two sets of 2DVD measurements. The Dm values calculated from 1-minute drop size distributions reached nearly 4 mm, whilst the maximum drop diameters were over 6 mm. The fall velocity measurements from the 2DVD indicate almost all hydrometeors to be fully melted at ground level. Drop shapes for this event are also being investigated from the 2DVD camera data.

Thurai, M.↗
NASA NTRS2023

Optimal Estimation Inversion of Ionospheric Electron Density from GNSS-POD Limb Measurements: Part II-Validation and Comparison Using NmF2 and hmF2

A growing number of SmallSat/CubeSat constellations with high-rate (50–100 Hz) global navigation satellite system radio occultations (GNSS-RO) as well as low-rate (1 Hz) precise orbit determination (GNSS-POD) limb-viewing capabilities provide unprecedented spatial and temporal sampling rates for ionospheric studies. In the F-region electron density (N 𝑒 ) retrieval process, instead of the conventional onion-peeling (OP) inversion, an optimal estimation (OE) inversion technique was recently developed using total electron content measurements acquired by GNSS-POD link. The new technique is applied to data acquired from the COSMIC-1, COSMIC-2, and Spire constellations. Although both OE and OP techniques use the Abel weighting function in N 𝑒 inversion, OE significantly differs in its performance, especially in the lower F- and E-regions. In this work, we evaluate and compare newly derived data sets using F2 peak properties with other space-based and ground-based observations. We determine the F2 peak N 𝑒 (NmF2) and its altitude (hmF2), and compare them with the OP-retrieved values. Good agreement is observed between the two techniques for both NmF2 and hmF2. In addition, we also utilize autoscaled F2 peak measurements from a number of worldwide Digisonde stations (∼30). The diurnal sensitivity and latitudinal variability of the F2 peak between the two techniques are carefully studied at these locations. Good agreement is observed between OE-retrieved NmF2 and Digisonde-measured NmF2. However, significant differences appear between OE-retrieved hmF2 and Digisonde-measured hmF2. During the daytime, Digisonde-measured hmF2 remains ∼25–45 km below the OE-retrieved hmF2, especially at mid and high latitudes. We also incorporate F-region N 𝑒 measurements from two incoherent scatter radar observations at high latitudes, located in the North American (Millstone Hill) and European (EISCAT at Tromso) sectors. The radar measurements show good agreement with OE-retrieved values. Although there are several possible sources of error in the ionogram-derived N 𝑒 profiles, our further analysis on F1 and F2 layers indicates that the low Digisonde hmF2 is caused by the autoscaled method, which tends to detect a height systematically below the F2 peak when the F1 layer is present.

GNSS radio occultation↗
NASA NTRS1999

A TRMM Microwave Radiometer Rain Rate Estimation Method with Convective and Stratiform Discrimination

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima (T85min) in a regional map containing a Mesoscale Convective System (MCS). This is because of relatively small footprint size (approximately 5.5 km) and strong extinction properties in this channel of the TMI. A map of surface rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85(sub min), produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we infer empirically from TMI data the presence of three different kinds of thunderstorms or Cbs. These Cbs are classified as young, mature, and decaying types, and are assumed to have a scale of about 20 km on the average. Two parameters are used to classify these three kinds of Cbs based on the T85 data: a) the magnitude of scattering depression deduced from local T85(sub min) and b) the mean horizontal gradient of T85 around such minima. Knowing the category of a given Cb, we can estimate the rain rate associated with it. Such estimation is done with the help of relationships linking T85min to rain rate in each Cb type. Similarly, a weak background rain rate in all the areas where T85 is less than 260 K is deduced with another relationship linking T85 to rain rate. In our rain retrieval model, this background rain constitutes stratiform rain where the Cbs are absent. Initially, these relationships are optimized or tuned utilizing the PR and TMI data of a few MCS events. After such tuning, the model is applied to independent MCS cases. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (>= 20 mm/hr) rain rates are retrieved satisfactorily. Accuracy in the estimates of the light, moderate, and intense rain areas and the mean rain rates associated with such areas in these independent MCS cases is on the average about 15 %. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

Prabhakara, C.↗
DOE OSTI2019

Spatio–Temporal Analysis of Deformation at San Emidio Geothermal Field, Nevada, USA Between 1992 and 2010

Although subsidence has been observed at the San Emidio geothermal field in Nevada using interferometric synthetic aperture radar since the early 1990s, the spatial extent and temporal evolution of the subsidence have not heretofore been quantified. Furthermore, the weather conditions and geographic location of San Emidio negatively affect interferometric image quality, causing low correlation amongst pairs. To address this, we introduce a new method for selecting pairs in areas of low correlation and small deformation signal using a minimum spanning tree method with a measure of image quality as the weighting criterion. We validate our pair selection approach by comparing our data products to SqueeSAR TM data products from a previous study at San Emidio. We also develop a deformation model which characterizes the spatial extent of subsidence at San Emidio in terms of volume change of the reservoir. After applying this deformation model to our data set of interferometric pairs, we examine the temporal relationship of the observed deformation with production and injection operations associated with geothermal power production.

Reinisch, Elena C. (ORCID:0000000252211921)↗
NASA NTRS1980

A variational technique for smoothing flight-test and accident data

The problem of determining aircraft motions along a trajectory is solved using a variational algorithm that generates unmeasured states and forcing functions, and estimates instrument bias and scale-factor errors. The problem is formulated as a nonlinear fixed-interval smoothing problem, and is solved as a sequence of linear two-point boundary value problems, using a sweep method. The algorithm has been implemented for use in flight-test and accident analysis. Aircraft motions are assumed to be governed by a six-degree-of-freedom kinematic model; forcing functions consist of body accelerations and winds, and the measurement model includes aerodynamic and radar data. Examples of the determination of aircraft motions from typical flight-test and accident data are presented.

Bach, R. E., Jr.↗
NASA NTRS1988

Mapping electrodynamic features of the high-latitude ionosphere from localized observations - Technique

This paper describes a novel procedure for mapping high-latitude electric fields and currents and their associated magnetic variations, using sets of localized observational data derived from different types of measurements. The technique provides a formalism for incorporating simultaneously such different classes of data as electric fields from radars and satellites, electric currents from radars, and magnetic perturbations at the ground and at satellite heights; the technique also uses available statistical information on the averages and variances of electrodynamic fields. The technique provides a more rigorous way of quantitatively estimating high-latitude electric field and current patterns than other methods and has a capability to quantify the errors in the mapped fields, based on the distribution of available data, their errors, and the statistical variances of the fields. The technique is illustrated by an application to a substorm which was analyzed by Kamide et al. (1982) by an earlier technique.

Richmond, A. D.↗
NASA NTRS1982

A Variational Technique for Smoothing Flight-Test and Accident Data

The problem of determining aircraft motions along a trajectory is solved using a variational algorithm that generates unmeasured states and forcing functions, and estimates instrument bias and scale-factor errors. The problem is formulated as a nonlinear fixed-interval smoothing problem, and is solved as a sequence or linear two-point boundary value problems, using a sweep method. The algorithm has been implemented for use in flight-test and accident analysis. Aircraft motions are assumed to be governed by a six-degree-of-freedom kinematic model; forcing functions consist of body accelerations and winds, and the measurement model includes aerodynamic and radar data. Examples of the determination of aircraft motions from typical flight-test and accident data are presented.

Bach, Ralph E. , Jr.↗
NASA NTRS2001

Hydrogeology of Basins on Mars

This document summarizes the work accomplished under NASA Grant NAG5-3870. Emphasis was put on the development of the FIDO rover, a prototype for the twin-Mers which will be operating on the surface of Mars in 2004, specifically the primary work was the analysis of FIDO field trials. The grantees also analyzed VIKING Lander 1 XRFS and Pathfinder APXS data. Results show that the Viking site chemistry is consistent with an andesite, and the Pathfinder site is consistent with a basaltic andesite. The grantees also worked to demonstrate the capability to simulate annealing methods to apply to the inversion of remote sensing data. They performed an initial analyses of Sojourner engineering telemetry and imaging data. They performed initial analyses of Viking Lander Stereo Images, and of Hematite deposits in Terra Meridiani. They also acquired and analyzed the New Goldstone radar data.

Arvidson, Raymond E.↗
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 NTRS2014

Lightning Jump Algorithm Development for the GOES·R Geostationary Lightning Mapper

Current work on the lightning jump algorithm to be used in GOES‐R Geostationary Lightning Mapper (GLM)'s data stream is multifaceted due to the intricate interplay between the storm tracking, GLM proxy data, and the performance of the lightning jump itself. This work outlines the progress of the last year, where analysis and performance of the lightning jump algorithm with automated storm tracking and GLM proxy data were assessed using over 700 storms from North Alabama. The cases analyzed coincide with previous semi‐objective work performed using total lightning mapping array (LMA) measurements in Schultz et al. (2011). Analysis shows that key components of the algorithm (flash rate and sigma thresholds) have the greatest influence on the performance of the algorithm when validating using severe storm reports. Automated objective analysis using the GLM proxy data has shown probability of detection (POD) values around 60% with false alarm rates (FAR) around 73% using similar methodology to Schultz et al. (2011). However, when applying verification methods similar to those employed by the National Weather Service, POD values increase slightly (69%) and FAR values decrease (63%). The relationship between storm tracking and lightning jump has also been tested in a real‐time framework at NSSL. This system includes fully automated tracking by radar alone, real‐time LMA and radar observations and the lightning jump. Results indicate that the POD is strong at 65%. However, the FAR is significantly higher than in Schultz et al. (2011) (50‐80% depending on various tracking/lightning jump parameters) when using storm reports for verification. Given known issues with Storm Data, the performance of the real‐time jump algorithm is also being tested with high density radar and surface observations from the NSSL Severe Hazards Analysis & Verification Experiment (SHAVE).

Schultz. E.↗
NASA NTRS2011

3D Vegetation Mapping Using UAVSAR, LVIS, and LIDAR Data Acquisition Methods

The overarching objective of this ongoing project is to assess the role of vegetation within climate change. Forests capture carbon, a green house gas, from the atmosphere. Thus, any change, whether, natural (e.g. growth, fire, death) or due to anthropogenic activity (e.g. logging, burning, urbanization) may have a significant impact on the Earth's carbon cycle. Through the use of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and NASA's Laser Vegetation Imaging Sensor (LVIS), which are airborne Light Detection and Ranging (LIDAR) remote sensing technologies, we gather data to estimate the amount of carbon contained in forests and how the content changes over time. UAVSAR and LVIS sensors were sent all over the world with the objective of mapping out terrain to gather tree canopy height and biomass data; This data is in turn used to correlate vegetation with the global carbon cycle around the world.

Uninhabited Aerial Vehicle Synthetic Aperture Rada↗
DOE OSTI2021

Coherent microwave scattering from resonance enhanced multi-photon ionization (Radar REMPI): A review

Coherent microwave scattering from laser-induced plasmas, including weakly ionized plasma, laser sparks, Multiphoton Ionization (MPI), and Resonance Enhanced Multi-Photon Ionizations (Radar REMPI) has achieved much successes in plasma, reactive and nonreactive flow diagnostics. Under illumination of microwaves (Radar), electrons inside the laser-induced plasma oscillate with the electric field of the microwave and re-radiate from the electrons forming coherent scattering. In the far-field approximation, the microwave scattering from the small volume plasma reflects the generation and evolution of unbounded electrons inside the plasma, when the microwave wavelength is much greater than the size of the plasma and the skin layer depth at the microwave frequency is larger than the size of the plasma. Laser excitation schemes, microwave detection methods, calibration of microwave scattering, and the novel applications of the technique have been significantly expanded and improved. Furthermore, this review paper summarizes physical principles, various REMPI excitation schemes for atomic and molecular species, and temperature measurements in plasma and reactive flows. Discussions on new research directions and applications are given at the end.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

SpaceNet 9—Cross-Sensor Alignment of Optical and SAR Imagery

Precise registration of high-resolution synthetic aperture radar (SAR) and optical imagery is necessary for realizing the full potential and benefits of multimodal image analysis. However, two significant challenges presently exist. First, there is a lack of annotated datasets and benchmarks available for high-resolution SAR–optical image registration. Second, an assessment of efficient and reliable image registration methods that can precisely align these modalities is lacking. Here, we present a holistic description of the SpaceNet 9 Challenge and its results. We present a description of the dataset and baseline algorithm along with the results of the challenge, including a description of the winning algorithms. We release the SpaceNet 9 dataset along with open-sourcing the winning algorithms and baseline. The objective of SpaceNet 9 was to compute a dense displacement map that indicates the shift needed to align pixels in an optical image to the pixels in a SAR image. The challenge launched in April 2025 and was active for approximately two months. The top five solutions reduced image alignment error from approximately 34 m to under 13 m for public and private test data, with the best results obtaining a registration error of only 8.5 and 6.7 m on the public testing and private testing dataset, respectively. Usage of pretrained image matching models, robust outlier rejection with RANSAC, and estimating local displacement were common among the top solutions. The results of this challenge provide insight into high-resolution SAR–optical image registration and offer opportunities for future benchmarking in this domain. The baseline algorithm, winning solutions, and datasets are available at https://spacenet.ai/sn9-challenge/.

benchmark datasets↗
NASA NTRS1986

Geological mapping potential of computer-enhanced images from the Shuttle Imaging Radar - Lisbon Valley Anticline, Utah

Computer-enhancement techniques applied to the SIR-A data from the Lisbon Valley area in the northern portion of the Paradox basin increased the value of the imagery in the development of geologically useful maps. The enhancement techniques include filtering to remove image speckle from the SIR-A data and combining these data with Landsat multispectral scanner data. A method well-suited for the combination of the data sets utilized a three-dimensional domain defined by intensity-hue-saturation (IHS) coordinates. Such a system allows the Landsat data to modulate image intensity, while the SIR-A data control image hue and saturation. Whereas the addition of Landsat data to the SIR-A image by means of a pixel-by-pixel ratio accentuated textural variations within the image, the addition of color to the combined images enabled isolation of areas in which gray-tone contrast was minimal. This isolation resulted in a more precise definition of stratigraphic units.

Curlis, J. D.↗
NASA NTRS2011

Scatterometer-Calibrated Stability Verification Method

The requirement for scatterometer-combined transmit-receive gain variation knowledge is typically addressed by sampling a portion of the transmit signal, attenuating it with a known-stable attenuation, and coupling it into the receiver chain. This way, the gain variations of the transmit and receive chains are represented by this loop-back calibration signal, and can be subtracted from the received remote radar echo. Certain challenges are presented by this process, such as transmit and receive components that are outside of this loop-back path and are not included in this calibration, as well as the impracticality for measuring the transmit and receive chains stability and post fabrication separately, without the resulting measurement errors from the test set up exceeding the requirement for the flight instrument. To cover the RF stability design challenge, the portions of the scatterometer that are not calibrated by the loop-back, (e.g., attenuators, switches, diplexers, couplers, and coaxial cables) are tightly thermally controlled, and have been characterized over temperature to contribute less than 0.05 dB of calibration error over worst-case thermal variation. To address the verification challenge, including the components that are not calibrated by the loop-back, a stable fiber optic delay line (FODL) was used to delay the transmitted pulse, and to route it into the receiver. In this way, the internal loopback signal amplitude variations can be compared to the full transmit/receive external path, while the flight hardware is in the worst-case thermal environment. The practical delay for implementing the FODL is 100 s. The scatterometer pulse width is 1 ms so a test mode was incorporated early in the design phase to scale the 1 ms pulse at 100-Hz pulse repetition interval (PRI), by a factor of 18, to be a 55 s pulse with 556 s PRI. This scaling maintains the duty cycle, thus maintaining a representative thermal state for the RF components. The FODL consists of an RF-modulated fiber-optic transmitter, 20 km SMF- 28 standard single-mode fiber, and a photodetector. Thermoelectric cooling and insulating packaging are used to achieve high thermal stability of the FODL components. The chassis was insulated with 1-in. (.2.5-cm) thermal isolation foam. Nylon rods support the Micarta plate, onto which are mounted four 5-km fiber spool boxes. A copper plate heat sink was mounted on top of the fiber boxes (with thermal grease layer) and screwed onto the thermoelectric cooler plate. Another thermal isolation layer in the middle separates the fiberoptics chamber from the RF electronics components, which are also mounted on a copper plate that is screwed onto another thermoelectric cooler. The scatterometer subsystem fs overall stability was successfully verified to be calibratable to within 0.1 dB error in thermal vacuum (TVAC) testing with the fiber-optic delay line, while the scatterometer temperature was ramped from 10 to 30 C, which is a much larger temperature range than the worst-case expected seasonal variations.

McWatters, Dalia A.↗
DOE OSTI2023

Field evaluation of semi‐automated moisture estimation from geophysics using machine learning

Geophysical methods can provide three-dimensional (3D), spatially continuous estimates of soil moisture. However, point-to-point comparisons of geophysical properties to measure soil moisture data are frequently unsatisfactory, resulting in geophysics being used for qualitative purposes only. This is because (1) geophysics requires models that relate geophysical signals to soil moisture, (2) geophysical methods have potential uncertainties resulting from smoothing and artifacts introduced from processing and inversion, and (3) results from multiple geophysical methods are not easily combined within a single soil moisture estimation framework. To investigate these potential limitations, an irrigation experiment was performed wherein soil moisture was monitored through time, and several surface geophysical datasets indirectly sensitive to soil moisture were collected before and after irrigation: ground penetrating radar, electrical resistivity tomography (ERT), and frequency domain electromagnetics (FDEM). Data were exported in both raw and processed form, and then snapped to a common 3D grid to facilitate moisture prediction by standard calibration techniques, multivariate regression, and machine learning. A combination of inverted ERT data, raw FDEM, and inverted FDEM data was most informative for predicting soil moisture using a random regression forest model (one-thousand 60/40 training/test cross-validation folds produced root mean squared errors ranging from 0.025–0.046 cm 3 /cm 3 ). This cross-validated model was further supported by a separate evaluation using a test set from a physically separate portion of the study area. Machine learning was conducive to a semi-automated model-selection process that could be used for other sites and datasets to locally improve accuracy.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

High-resolution system for tropospheric wind and temperature profile measurements

This paper briefly describes the Jimsphere/Jimsonde system and presents some possible applications of the system. As space vehicles became larger and more sophisticated, an improved method for obtaining wind-profile data had to be found. To satisfy this need, the FPS-16 radar/Jimsphere system was developed. The Jimsphere is an aluminized mylar spherical balloon 2 m in diameter. The balloon is under superpressure and is tracked with a high-precision radar system. The development of this detailed wind-profile system was started in 1963, and the present design was established in 1964. To improve the system, a program was initiated in 1965 to obtain high-resolution temperature data simultaneously with the wind-profile data.

Camp, D. W.↗